JP2022090134A - Management device and management method - Google Patents

Abstract

[Problem] It is conceivable to formulate a plan in consideration of the whole. However, a plan that is developed solely by consideration of the whole is not necessarily favorable enough. A demand category is provided. A "demand category" is a classification unit of demand. Demands included in the "demand category" have the same attribute such as contract type, industry type, demand point, and demand generation time. For example, the management device includes a sales income calculation unit that calculates the sales income by supplying the demand using the hourly charge unit price for each demand category and the value of the power consumption, and a predetermined period of the demand category. and a unit price search unit that searches for a unit price that satisfies the constraints based on the comparison result. [Selection drawing] Fig. 16

Description

The present invention generally relates to a management technique relating to at least one of energy demand and supply.

A system is known in which an order is planned from an exchange in order to meet the demand that fluctuates on the date and time of the supply destination. In the system described in Patent Document 1, it is attempted to determine the bid amount and the bid price to the electric power market from the power generation plan created based on the demand estimation data and the power source data. As a result, it is possible to make a bid that uniquely assumes the price in the electric power market.

In addition, a system for conducting transactions in a market where market conditions are constantly changing is known. In Patent Document 2, in order to flexibly and automatically adjust the order quantity according to the market trend in the system that divides the transaction quantity into a plurality of slices and associates each slice with the time frame of the transaction time to automatically execute the order. In addition, it is possible to determine whether or not the change conditions of the ordering schedule set in advance are satisfied based on the market data, and if the change conditions are satisfied, the planned execution rate at the order timing is increased or decreased by a predetermined value. Attempted. As a result, it is possible to carry out a transaction that satisfies the preset total transaction amount.

Japanese Unexamined Patent Publication No. 2007-159239 Japanese Unexamined Patent Publication No. 2008-209987

It is conceivable to formulate a plan considering the whole (for example, the total cost). However, a plan that is formulated based on overall consideration is not always preferable. In addition, there may be issues regarding formulation other than planning.

Therefore, a demand category is prepared. "Demand category" is a division unit of demand. Demand included in the "demand category" is demand having the same attributes such as contract type, industry type, demand point, and demand occurrence time.

The management device according to the first viewpoint has a sales revenue calculation unit that calculates sales revenue by supplying demand by using the hourly rate unit price for each demand category and the value of power usage, and a demand category. A balance forecast spread calculation unit that compares the balance of each of the multiple future amount estimation time series regarding the power consumption in a predetermined period, and a charge unit price search unit that searches for a charge unit price that satisfies the constraint condition based on the comparison result. Be prepared.

The management device according to the second viewpoint has a supply cost calculation unit for each category that calculates the supply cost for each demand category, and a demand category balance calculation that calculates the balance that is the difference between the sales revenue and the supply cost for the predetermined demand category. Based on the balance, a combination of supply sources by time that satisfies the constraint conditions (for example, even if the demand forecast goes wrong or the contract price forecast goes wrong, the start / stop plan result does not hang). It is equipped with a source search unit for searching.

The management device according to the third viewpoint has a charge menu value difference estimation unit that estimates the difference between the payment amount in the charge menu of the change candidate and the payment amount in the charge menu before the change regarding the electricity charge paid by the consumer. , The contract ratio estimation unit for each charge menu that estimates the selection ratio (or the number of contracts) of each charge menu in the future planning period based on the estimated value difference of the charge menu, and the sales income that calculates the sales income based on the payment amount. The contract ratio or the number of contracts becomes a predetermined value based on the calculation unit, the contract ratio constraint condition input unit for each charge menu that specifies the increase / decrease rate of the contract ratio for each charge menu of the demand category, and the specified increase / decrease rate. It is equipped with a charge unit price search unit that determines the charge unit price.

The management device according to the fourth aspect is a demand value of a predetermined demand category, or a demand value of a predetermined demand category, in addition to a balance forecast spread using the first scenario, which is a designated scenario, and a supply and demand value of the first scenario. , Predetermined supply category (Supply category is a unit of supply source division, and the supply sources included in the same "supply category" are power generation fuel type, capacity, power generation time zone, installation point, and products when conducting wholesale power transactions. Balance using the second scenario, which is a scenario in which the value of supply (supply amount, unit price of supply, contract price in the electric power market) from (one of the attributes such as type is the same source) is added or changed. A scenario management unit that calculates the forecast spread, and a demand or supply source additional effect estimation unit that compares and displays the balance forecast spread using the first scenario and the balance forecast spread using the second scenario. To prepare for.

It can contribute to more favorable formulation.

It is a block diagram which shows the structure of the function of the electric power transaction planning apparatus which concerns on 1st Embodiment of this invention. It is a block diagram of the hardware of 1st Embodiment of this invention. It is a sequence diagram of the 1st Embodiment of this invention. It is a linkage diagram which shows the cooperation relationship between the systems in 1st Embodiment of this invention. It is a flowchart which shows the process of 1st Embodiment of this invention. It is a figure which shows the example of the portfolio change of 1st Embodiment of this invention. It is a figure which shows the example of the portfolio change of 1st Embodiment of this invention. It is a figure which shows the example of the portfolio change of 1st Embodiment of this invention. It is a block diagram of the data table of the 1st Embodiment of this invention. It is a block diagram of the target order transition table of the 1st Embodiment of this invention. It is a block diagram of the target order transition table of the 1st Embodiment of this invention. It is a figure which shows the time transition pattern of the data of 1st Embodiment of this invention. It is a figure which shows the candidate pattern of the transition of the future amount of the 1st Embodiment of this invention. It is a figure which shows the frequency distribution of the estimated amount of the future amount of 1st Embodiment of this invention. It is a figure which shows the candidate pattern of the transition of the future amount of the 1st Embodiment of this invention. It is a figure which shows the frequency distribution of the estimated amount of the future amount of 1st Embodiment of this invention. It is a figure which shows the relationship between the measured value of the transition of the prediction of the 1st Embodiment of this invention, and the estimation result of the transition of the predicted value of a variance value. It is a figure for comparing the ordering method in the 1st Embodiment of this invention with a conventional ordering method. It is a figure which shows the supply record and profit result of the seller in 1st Embodiment of this invention. It is a figure which shows the result of the transition of ordering in 1st Embodiment of this invention. It is a block diagram which shows the structure of the function of the transaction planning apparatus which concerns on 5th Embodiment of this invention. It is a block diagram which shows the structure of the function of the transaction planning apparatus which concerns on 6th Embodiment of this invention. It is a block diagram which shows the structure of the function of the transaction planning apparatus which concerns on 7th Embodiment of this invention. It is a block diagram which shows the structure of the function of the transaction planning apparatus which concerns on 8th Embodiment of this invention. An example of the combination result according to the comparative example of the sixth embodiment of the present invention is shown. An example of the search result according to the sixth embodiment of the present invention is shown. It is a figure which shows an example of the screen about STEP1 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 22 is shown. An example of the second part of the information displayed on the screen of FIG. 22 is shown. An example of the third part of the information displayed on the screen of FIG. 22 is shown. An example of the fourth part of the information displayed on the screen of FIG. 22 is shown. An example of the fifth part of the information displayed on the screen of FIG. 22 is shown. An example of the sixth part of the information displayed on the screen of FIG. 22 is shown. It is a figure which shows an example of the screen (execution screen) about STEP2 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 29 is shown. An example of the second part of the information displayed on the screen of FIG. 29 is shown. An example of the third part of the information displayed on the screen of FIG. 29 is shown. It is a figure which shows an example of the screen (result storage screen) about STEP2 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 33 is shown. An example of the second part of the information displayed on the screen of FIG. 33 is shown. An example of the third part of the information displayed on the screen of FIG. 33 is shown. It is a figure which shows an example of the screen (execution screen) about STEP3 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 37 is shown. An example of the second part of the information displayed on the screen of FIG. 37 is shown. An example of the third part of the information displayed on the screen of FIG. 37 is shown. An example of the fourth part of the information displayed on the screen of FIG. 37 is shown. An example of the fifth part of the information displayed on the screen of FIG. 37 is shown. It is a figure which shows an example of the screen (result storage screen) concerning STEP3 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 43 is shown. An example of the second part of the information displayed on the screen of FIG. 43 is shown. An example of the third part of the information displayed on the screen of FIG. 43 is shown. It is a figure which shows an example of the screen (execution screen) which concerns on STEP4 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 47 is shown. An example of the second part of the information displayed on the screen of FIG. 47 is shown. An example of the third part of the information displayed on the screen of FIG. 47 is shown. An example of the fourth part of the information displayed on the screen of FIG. 47 is shown. An example of the fifth part of the information displayed on the screen of FIG. 47 is shown. It is a figure which shows an example of the screen (result storage screen) concerning STEP4 which concerns on 9th Embodiment of this invention. An example of the first part of the information displayed on the screen of FIG. 53 is shown. An example of the second part of the information displayed on the screen of FIG. 53 is shown. An example of the third part of the information displayed on the screen of FIG. 53 is shown.

In the following description, the "interface unit" may be one or more interfaces. The one or more interfaces may include at least a communication interface unit among a user interface unit and a communication interface unit. The user interface unit may be at least one I / O device of one or more I / O devices (for example, an input device (for example, a keyboard and a pointing device) and an output device (for example, a display device)) and a display computer. , Alternatively or additionally, may be an interface device to the at least one I / O device. The communication interface unit may be one or more communication interface devices. One or more communication interface devices may be one or more communication interface devices of the same type (for example, one or more NICs (Network Interface Cards)) or two or more different types of communication interface devices (for example, NIC and HBA (Host Bus)). Adapter)) may be used.

In the following description, the "memory unit" may be one or more memories. The at least one memory may be a volatile memory or a non-volatile memory. The memory unit is mainly used during processing by the processor unit.

Further, in the following description, the "PDEV unit" may be one or more PDEVs. "PDEV" means a physical storage device, typically a non-volatile storage device (eg, auxiliary storage device), such as an HDD (Hard Disk Drive) or SSD (Solid State Drive). The PDEV unit may be a RAID group. "RAID" is an abbreviation for Redundant Array of Independent (or Inexpensive) Disks.

Further, in the following description, the "storage unit" includes at least a memory unit among the memory unit and the PDEV unit.

Further, in the following description, the "processor unit" may be one or more processors. The at least one processor is typically a microprocessor such as a CPU (Central Processing Unit), but may be another type of processor such as a GPU (Graphics Processing Unit). Each of the one or more processors may be single-core or multi-core. Some processors may be hardware circuits that do some or all of the processing.

Further, in the following description, the function may be described by the expression of "kkk unit" (excluding the interface unit, the storage unit, and the processor unit), but the function is such that one or more computer programs are executed by the processor unit. It may be realized by one or more hardware circuits (for example, FPGA (Field-Programmable Gate Array) or ASIC (Application Specific Integrated Circuit)). When the function is realized by executing the program by the processor unit, the specified processing is appropriately performed by using the storage unit and / or the interface unit, so that the function is at least a part of the processor unit. You may. The process described with the function as the subject may be a process performed by a processor unit or a device having the processor unit. The program may be installed from the program source. The program source may be, for example, a program distribution computer or a computer-readable recording medium (eg, a non-temporary recording medium). The description of each function is an example, and a plurality of functions may be combined into one function, or one function may be divided into a plurality of functions.

Further, in the following description, the information may be described by an expression such as "xxx table", but the information may be expressed by any data structure. That is, the "xxx table" can be referred to as "xxx information" in order to show that the information does not depend on the data structure. Further, in the following description, the configuration of each table is an example, and one table may be divided into two or more tables, or all or a part of two or more tables may be one table. good.

Further, in the following description, the "management device" may be composed of one or more computers. Specifically, for example, when a computer has a display device and the computer displays information on its own display device, the computer may be a management device. Further, for example, when the first computer (for example, a server) transmits display information to a remote second computer (display computer (for example, a client)) and the display computer displays the information (the first computer is the second computer). (When displaying information on a computer), at least the first computer among the first computer and the second computer may be a management device. The management device may have an interface unit, a storage unit, and a processor unit connected to them. The computer in the management device "displaying the display information" may mean displaying the display information on the display device of the computer, or the computer may transmit the display information to the display computer. It may be present (in the latter case, the display information is displayed by the display computer). Further, the function as a management device may be provided by executing one or more computer programs in a computer system (for example, a cloud platform) including one or more computers (for example, provided as a kind of cloud computing service). May be).

Hereinafter, a plurality of embodiments will be specifically described with reference to the drawings. In the following, for example, in the first to fourth embodiments, the transaction planning device will be described as an example of the management device. The management device will be described in the fifth and subsequent embodiments.

<< First Embodiment >>

[Constitution]

<< Functional configuration >>

FIG. 1 is a block diagram showing a configuration of a function of a power transaction planning device according to the first embodiment of the present invention. In FIG. 1, the transaction planning device 1 is a device belonging to a sales business system, and includes a future quantity estimation unit 10, an order quantity planning unit 20, and an hourly ordering planning unit 30. The future quantity estimation unit 10 includes a demand fluctuation estimation unit 101, a supply fluctuation estimation unit 102, a market fluctuation prediction unit 103, and a convergence estimation unit 104. The order quantity planning unit 20 includes a transaction position determination unit 201 and a transaction cumulative volume storage unit 202. The hourly ordering planning unit 30 is composed of a transaction ordering time dividing unit 301, a transaction ordering data determination unit 302, a power generation planning processing unit 303, a storage storage demand planning processing unit 304, and a target ordering transition table 305.

The future quantity estimation unit 10 includes a plurality of demand systems (1 to N) 1000, a power generation business system (1) 2000, a market A system (sales business system (2 to L) 4000, and a power generation business system (2 to K) 2000). (Including) 3000, the actual data is acquired from each of the market B system 3100, the future quantity regarding the demand and the business partner in each system is estimated, and the estimated data is output to the order quantity planning unit 20. In particular, the present embodiment includes a convergence estimation unit 104 that estimates an estimated amount of data (for example, variance or likelihood value) related to an error in the future amount estimated from the actual value.

The order quantity planning unit 20 receives the future quantity estimation data regarding the demand and the business partner from the future quantity estimation unit 10, determines the volume of transactions to a plurality of business partners, and determines the determined contents by the hourly order planning unit 30. Accumulation of transactions so far based on the transaction position determination unit 201, the contract data from the market ordering terminal 5000, the power generation plan data from the power generation ordering terminal 5100, and the demand planning data from the aggregator ordering terminal 5200. It is configured to include a transaction cumulative amount storage unit 202 for storing the amount.

The hourly ordering planning unit 30 generates transaction ordering data such as the amount of transaction orders or the amount to be exercised in the planned transaction period, which is a subdivided period in the passage of time during the transaction period in which transactions can be performed. The time division unit 301 generates an order message (message including price and quantity data of buy or sell order) to the market or business partner, and outputs the generated order message (order data) to the market order terminal 5000. Power generation plan processing unit 303 that generates power generation plan data based on the data for each planning period generated by the transaction order data determination unit 302 and the transaction order time division unit 301, and outputs the generated power generation plan data to the power generation order terminal 5100. And the demand planning processing unit 304 for electricity storage, etc., which generates demand planning data based on the data for each planning period generated by the transaction ordering time dividing unit 301 and outputs the generated demand planning data to the aggregator ordering terminal 5200, and the transaction ordering. The configuration includes a target order transition table 305 that stores data for each planning period generated by the time division unit 301.

<< Hardware configuration >>

FIG. 2 is a configuration diagram of the hardware of the transaction planning device 1. In FIG. 2, the transaction planning device 1 includes a storage device 40 for recording programs and data that realize the functions of the future quantity estimation unit 10, the order quantity planning unit 20, and the hourly ordering planning unit 30, a CPU 50, and a main. It includes a memory 60, an input / output interface 70, and a network interface 80, and each part is connected to a bus 90. The input / output interface 70 includes an external communication terminal 71, a keyboard 72, and a display device 73. The network interface 80 is connected to an external system (demand system 1000, power generation business system 2000, etc.) and an ordering terminal such as a market ordering terminal 5000, a power generation ordering terminal 5100, and an aggregator ordering terminal 5200. The input / output interface 70 and the network interface 80 are examples of the interface unit. The storage device 40 is an example of the PDEV unit. The main memory 60 is an example of the memory unit. The CPU 50 is an example of a processor unit.

<< Transaction processing sequence diagram >>

FIG. 3 is a sequence diagram showing a power transaction process (phases Ph1 to Ph6) including a transaction plan process performed by the transaction planning device in the present embodiment and a process of another system that exchanges input / output data of the transaction process.

In FIG. 3, the seller executes the phases (electric power transaction processing) Ph1 to Ph6 using the transaction planning device 1. First, the transaction planning device 1 is based on the information on fuel, futures, adjustment power and transmission right in Market B (Market B system), and the information on middle and base and renewable energy (renewable energy) in the power generation company. The next phase Ph1 is executed, and the monthly phase Ph2 is executed based on the information on the transmission right in the market B and the information on the middle, base and renewable energy in the power generation company. Next, the transaction planning device 1 performs Phase Ph3 10 to 3 days ago based on the information on the negawatt in the market B, the information on the 4-hour product advance in the market A, and the information on the middle and the base in the power generation company. Execute, based on the information about the negative in Market B, the information about the day before the one-frame product and the four-hour product advance in Market A, the information about the aggregator, and the information about the middle and base in the power generation company, the phase Ph4 on the previous day. Run. Next, the transaction planning device 1 is based on the information on the negawatt in the market B, the information on the one-frame product time before and four hours on the market A, the information on the aggregator, and the information on the middle in the power generation company. Execute Phase Ph5 on the day, execute Phase Ph6 during delivery based on the information about the aggregator and the information about renewable energy at the power generation company, send the processing result to the contract consumer, and then process the transaction settlement. To execute. In Phase Ph6, the delivery period of the 30-minute product in the ancillary is being delivered. In addition, the block trade delivery period is the period until the transaction settlement processing, which includes the delivery period of the 30-minute product.

<< System linkage diagram >>

FIG. 4 is a linkage diagram showing a cooperative relationship between the systems according to the present embodiment. In FIG. 4, the systems according to the present embodiment include a plurality of demand systems (1 to N) 1000 belonging to contract consumers, a plurality of demand systems (N + 1 to N + M) 1000 belonging to other consumers, and a sales business system ( 1) 4000, power generation business system (1) 2000, multiple sales business systems (2 to L) 4000 belonging to other electric power companies, and multiple power generation business systems (2 to K) 2000 belonging to other electric power companies. It is composed of a market A system 3000, a market B system 3100, an ancillary system 7000, and an aggregator system 8000, and each system is connected via a network. The sales business system 4000 used by the electric power sales business includes the transaction planning device 1. The sales business system 4000 receives the data from the demand system 1000 via the mediation virtual database (virtual database) 6000 for data mediation managed by the power transmission and distribution business operator. In addition, data related to supply (data on the amount of thermal power that can be generated and controllable, and data on the status of renewable energy generated by solar and wind power) are acquired from the power generation business system 2000 of the power generation company that conducts bilateral transactions. is doing. Further, the sales business system 4000 exchanges data related to each market from the market A system 3000 and the market B system 3100, and exchanges data related to orders and orders with the aggregator system 8000 that performs demand response.

<< Flowchart >>

FIG. 5 is an overall flowchart of the processing performed by the transaction planning apparatus in this embodiment. In FIG. 5, the future quantity estimation unit 10 estimates various future quantities (step S1), and the order quantity planning unit 20 plans the order quantity from the estimation result of the future quantity estimation unit 10 (step S2). The separate ordering planning unit 30 plans the hourly ordering based on the ordering quantity plan, and transmits the ordering data to the market and the business partner based on the planning result (step S3). Hereinafter, the details of the processing in each part will be described.

[Processing of future quantity estimation unit 10]

(Step S101) The demand fluctuation estimation unit 101 estimates the future amount of the demand for electric power consumed by the supplying consumer. Here, the future period is divided into 30-minute units, and the demand amount for each period is estimated. Estimates are based on historical demand data. For example, select a demand curve for similar demand days with similar day, calendar day, and meteorological data, generate a multiple regression prediction model of daily maximum, daily minimum, daily average, or maximum and minimum demand from the weather data, and weather forecast. The daily maximum, daily minimum, daily average, or maximum / minimum demand may be predicted from the data, and the demand curve may be corrected. Alternatively, the time-series forecast may be performed by using the time-series data of the past demand as the time-series data and using the autoregressive model.

(Step S102) The supply fluctuation estimation unit 102 estimates the future amount of data related to the power generation of the power generation company that wholesales the power supplied by the sales company to the consumer to the sales company. This process includes the process of estimating future quantities of renewable energy supplies for solar and wind power. Estimates are made based on past power generation performance data. For example, select a power generation curve for similar demand days with similar meteorological data, generate a multiple regression prediction model from the meteorological data to the daily maximum, daily minimum, daily average, or maximum and minimum power generation, and from the weather forecast data, the daily maximum, The daily minimum, daily average, or maximum / minimum power generation amount may be predicted, and the power generation curve may be corrected to make the prediction. Alternatively, the time fluctuation of the past power generation may be used as time series data, and the time series prediction by the autoregressive model may be performed.

Preferably, the processing of the supply fluctuation estimation unit 102 of the present embodiment is a controllable amount of thermal power generation and pumped storage power generation as data related to power generation data (power generation amount that can be increased within 30 minutes by issuing a control request). And the processing of estimating the future amount of power generation that can be reduced).

(Step S103) The market fluctuation prediction unit 103 estimates the future amount of data of the market price, the number of bids, and the bid power amount in the wholesale market where the seller procures the power to be supplied to the consumer (these data). Is treated as a continuous quantity or a discrete value quantity). Estimates are based on historical market data. For example, select a price curve, bid quantity curve, bid power amount curve for similar days with similar data on day of the week, calendar day, weather, estimated demand, and planned outage generator capacity, and select the daily maximum of each curve. Generate multiple regression prediction models for daily minimum, daily average, or maximum minimum values, and calculate each multiple regression prediction value based on the assumed data of day of the week, calendar day, weather, estimated demand, and planned outage generator capacity. However, it may be predicted by correcting each curve. Alternatively, the time fluctuation of the past data may be used as the time series data, and the time series prediction by the autoregressive model may be performed.

Further, preferably, in the market fluctuation prediction unit 103 of the present embodiment, an estimation unit for the future amount of free capacity of the transmission line related to the transmission of power procured from the power plant, and an adjustment amount power generation right (adjustment) purchased by the transmission company. Estimating the future amount of price and quantity of power trading), Estimating the future amount of price of ancillary service (service to replenish the difference between power generation amount and demand amount) for eliminating imbalance by transmission companies, Negawatt It includes an estimation part of the future amount of trading and an estimation part of the future amount of fuel (market price of LNG and crude oil and future transaction price), and processes the estimation of these future amounts. This allows for transaction planning, including transmission reservation rights, provision of power generation rights to coordinating power, ancillary services, and use of negawatts.

(Step S104) The convergence estimation unit 104 estimates the transition of the error for each estimated future quantity. Here, the future period is divided into 30-minute units, and the error of the estimated amount in each is estimated. Estimates are based on historical performance data. For example, the time fluctuation of the past actual data is used as the time series data, and the time series prediction is performed by the distributed autoregressive model.

Preferably, the past actual data is subdivided into predetermined periods (for example, 24 hours, 48 hours, 1 week, etc.), each of which is subjected to high-speed Fourier transform or wavelet transform, and the features as periodic fluctuations are similar. It is classified by each, and the pattern of periodic fluctuation (calculated by inversely converting the average value of the feature amount) is extracted for each classified group, and the attributes common to each classified group (day, calendar day, temperature, temperature, etc.) An identification tree that identifies the conditions (attributes) in which a pattern occurs from sunshine, other weather data, planned number of generators stopped, free transmission capacity, demand forecast value, etc. is generated by the identification algorithm of CART or ID3, and the identification tree is used in the future. A plurality of pattern candidates that occur in the period may be estimated, and the estimation patterns may be combined to obtain the frequency distribution of the future quantity that will occur. This makes it possible to reasonably estimate future quantities, including irregular fluctuations, for example, called market price spikes, and to change the effective frontier due to the presence of spikes in a transaction plan that takes into account the occurrence of spikes. A transaction plan that takes into consideration) can be carried out.

FIGS. 10 (a) to 10 (f) show extraction examples of patterns 1 to 6 of the time transition of the future amount in the predetermined period thus obtained.

FIG. 11A shows the future during a certain future period 0 to p3 (for example, 0:00 to 24:00 on July 3) at time t included in the phase (electric power transaction processing) Ph2 of the sequence of FIG. It is the figure which plotted the pattern of the candidate of the transition of quantity (here, an example of demand quantity). Three patterns are output as candidates. FIG. 11B is based on information on the certainty (selection ratio in the identification tree) that each of the candidate patterns of FIG. 11A is selected and the candidate pattern (or past measured data that is a sample that generates the candidate pattern). FIG. 11A shows the frequency distribution of the estimated amount (predicted amount) of the future amount at the future time point p2. FIG. 11C shows an example of the future amount (here, the demand amount) in the same future period (July 3, 0:00 to 24:00) performed at the time point t2 in the phase (electric power transaction processing) Ph4 of the sequence of FIG. It is a figure which plotted the candidate pattern of the transition of). Two patterns are output as candidates. FIG. 11D is based on information on the certainty (selection ratio in the identification tree) that each of the candidate patterns of FIG. 11C is selected and the candidate pattern (or past measured data that is a sample that generates the candidate pattern). Similarly, the frequency distribution of the estimated amount (predicted amount) of the future amount at the future time point p2 is shown.

Here, since the timing for executing the estimation is advanced from the time t1 of the phase Ph2 to the time t2 of the phase Ph3, the prediction error is reduced (the base of the frequency distribution is narrowed and the likelihood is increased).

Particularly preferably, in the present embodiment, the value of the error (variance value or likelihood) may be used as time series data, and the change (convergence) of the value may be predicted.

FIG. 12 shows the measured value of the transition of the prediction in each phase in which the future quantity is estimated (predicted) (exemplified by the frequency distribution of Yamagata) and the transition of the predicted value of the variance value (estimated value by the variance autoregressive model). It is a figure which showed an example of the value (exemplified in a box chart) of the estimation result of. In this embodiment, the transition of the predicted value of x at the time p2 in each prediction phase is shown.

[Processing of order quantity planning unit 20]

In the processing of the order quantity planning unit 20 in steps S201 to S202, the estimated value and estimation of the data related to various power generations (thermal power generation, running water power generation, solar power generation) operated by the company under the demand, market, and bilateral contract. From the value error (dispersion and likelihood) data, the order quantity of power procurement required for power supply, the supplier, and the type of ordered product are determined. The details of the processing of the power generation amount planning unit 20 below will be described.

(Step S201) In the transaction position determination unit 201, 30 minutes from the cumulative amount of transactions and the estimated future amount of demand and business partners (wholesale supply power generation business operators, wholesale procurement business operators and markets). Processes the transaction position determination, which is the value of the transaction volume (order volume, order volume) to the business partner for each delivery time. The trading position is determined from the portfolio, which is the planned allocation value of operating funds. A portfolio is the ratio of multiple risk-free assets to operating funds allocated to risky assets. In this embodiment, a portfolio is planned in which the amount of power generated agreed with the partner power plant and the electric power products traded in the market are assets. Here, the effective frontier (the best effective portfolio and also called the efficient frontier) is a feasible portfolio, and (1) supply restrictions such as generator capacity, start-up / start-up time, and minimum. A portfolio that can be realized by satisfying the physical constraints of operational constraints such as downtime and minimum operating time, and (2) has the same risk value, and has the maximum evaluation value of the period profit amount, and (3) profit. A portfolio that meets the three conditions of a portfolio with a lower risk valuation and a period of income equal to or greater than the period of income.

FIG. 6A is a graph relating to each evaluation value of feasible portfolios in the first half of Phase Ph2 (10 days before delivery). Here, the vertical axis is the profit evaluation value by simulation of the execution of the transaction according to the portfolio, and the horizontal axis is the value of VaR (value at risk) of the profit in the simulation. Evaluation values are obtained by performing Monte Carlo simulation in simulation for a feasible portfolio. Pf1, Pf2, Pf3, and Pf4 in the figure are portfolios in which the product composition (power generation composition) of the transaction is different from each other.

The profit evaluation period in this embodiment is one week including the delivery date of electric power to the consumer, and the feasible solution (one-week generator start / stop plan and output allocation execution) within the physical constraints. We are evaluating a portfolio that meets the possible solutions).

Pf1 is a feasible solution obtained as a transaction for each 30-minute frame, and is an in-house contract generator of the total daily supply, 4-hour block power, 30-minute power for the previous day transaction, and 30-minute power for the previous transaction. , Shows one of the portfolios that holds the ratio of investment reserves at a ratio of 6: 1: 1: 1: 1. Similarly, Pf2 has a ratio of 4: 3: 1: 1: 1: 1, Pf3 has a ratio of 1: 6: 1: 1: 1: 1, and Pf4 has a ratio of 1: 2: 2: 4: 1 for one day. Allocating funds.

Instead of this embodiment, the portfolio data may be retained as a distribution ratio related to power generation, power sale, and power purchase at supply kWh.

In the example of FIG. 6A described above, Pf2 and Pf3 are portfolios that satisfy the conditions of the effective frontier in the evaluation in Phase Ph2. The evaluation result is output from the input / output interface 70, and a selection instruction is received as to which portfolio to proceed with the planning process.

The trading position every 30 minutes that realizes the selected portfolio is called from the above simulation result and stored in the data table T1 of FIG. 7. The example of the data table T1 shows the result of a plan to wholesale a product of 4 hours block and wholesale a product of 1 frame for 30 minutes. The amount of wholesale sales is stored as a negative price.

In this embodiment, a simulation including an evaluation value with a negative value as a position is performed. This means placing a sell bid on the market. In the example of the data table T1 of FIG. 7, regarding the delivery from 8:00 start to 12:00 end (11:30 start frame), the scheduled power generation of the contracted power plant and the procurement in the 4-hour block are obtained. Since the demand exceeds the kW, the results of the plan to wholesale to the previous day market and the previous hour market as a 30-minute electric power product are shown. The trading position determined in this way every 30 minutes is output (above step S201).

(Step S202) The transaction cumulative amount storage unit 202 receives the transaction cumulative data that can be executed in the market and the data of the plan conclusion result with the power generation company of the customer and the aggregator company that supplies the negawatt for the transaction position. And record. The recording result is output to the user through the input / output interface 70.

The above is the processing of the order quantity planning unit 20. By this processing, the target value of the amount of electric power procured from the business partner for the supply time is determined for each delivery time zone (each delivery frame) as tagged data that specifies the product type, the business partner, and the power generation type. To.

[Processing of order quantity planning unit 20 and reprocessing by repeated execution in phase]

In the present embodiment, steps S201 and S202 are repeatedly executed in the phases Ph1 to Ph6 shown in FIG. 3 (executed every predetermined period (for example, every 2 hours) even during one phase). As a result, changes in demand and business partner conditions based on transaction plans with markets and business partners in which multiple transactions with different transaction periods are conducted, and data on demand conditions, market conditions, and generator operating conditions that gradually become clear. A transaction plan corresponding to the above can be made.

For example, due to the execution of the process of (step S201) in phase Ph3, unlike the above-mentioned evaluation of the portfolio in phase Ph2 (explained in FIG. 6A above), the figure is based on the data received in the new data. The portfolio of 6B is calculated in the same manner as in the process of step S201 described above.

At this time, in step S201, if the effective frontier for which the portfolio should be selected matches the previous execution time, the processing is not changed. When the effective frontier is different from the previous execution time (for example, it is different in FIG. 6A and FIG. 6B), it is characterized by processing the change of the portfolio selection.

In the example shown in FIG. 6B of the present embodiment, the weather forecast data for the day of delivery changes from "cloudy" to "sunny and sometimes cloudy / wind speed" four days before the delivery of Phase Ph3.

"The market price declines due to the increase in the supply of renewable energy from solar power, and the increase in the number of bids for the 30-minute product to sell the thermal power to the market in advance for the power generation event person who has a margin of supply capacity. And the increase in bids for renewable energy generation, which is highly dependent on the weather, will lead to an increase in the diversification of market prices. " Under the new market estimator, the portfolio that meets the conditions for a portfolio on the effective frontier is the aforementioned Pf4.

Further, in the example shown in FIG. 6C of the present embodiment, the weather forecast data for the delivery day changes from "cloudy" to "rain" (a large amount of middle layer clouds) 4 days before the delivery of Phase Ph3.

"The supply of renewable energy from solar power has decreased, and the supply capacity has decreased. The market price has risen due to the reduction of selling bids to the spot for 30 minutes, and the location of power generation is biased. Reflecting the fact that the diversification value of the market price will increase due to the occurrence of market division due to the congestion of the power flow due to the increase and the increase in the frequency of the open interest purchase phenomenon in the wholesale market. " , Each future quantity estimate has been updated. Estimator for this new market In Nomoto, the portfolio that meets the conditions for a portfolio on the effective frontier is Pf1 mentioned above.

In a preferred embodiment of the invention, the evaluation result of the po-photofolio records the current and future evaluation values of the portfolio estimated from the error estimation data in the convergence estimation. Further, the simulation result of the effective frontier at each time (and each phase in FIG. 3) may be output.

In the output at the input / output interface for portfolio selection, the current evaluation of the portfolio (power generation composition ratio and procurement composition ratio of electric power products) and the evaluation of the portfolio that will occur in the future phase (from the effective frontier in Fig. 6A). , The occurrence of an effective frontier in Fig. 6B or Fig. 6C is expected due to weather changes), and Phase Ph6, which allocates 60% of operating funds to forward power, is the weather data due to expected weather changes. In the original evaluation, it is displayed that the profit is low, and the user is alerted.

In the present embodiment, preferably, in step S201, when the difference between the total transaction volume with all the business partners and the future demand amount deviates by a predetermined value or more, the transaction with one of the business partners is preferred. Increase or decrease the transaction volume.

In addition, if the estimated value of the transaction price with a certain business partner is cheaper than the transaction price related to the cumulative transaction of all transactions, the transaction quota with that business partner is increased and the transaction with a certain business partner is increased. If the estimated value of the transaction price of is expensive, an update process is performed to reduce the transaction allocation amount with the relevant business partner.

In addition, the update process is performed to reduce the transaction volume allocation to the business partner whose transaction price error data value has increased and to increase the transaction volume allocation to the business partner whose transaction price error data has decreased.

In addition, the combination of transactions is calculated based on the effective frontier calculated from the expected income from the transaction and the risk of the expected income, and the effective frontier in the latter half of the transaction is calculated from the data in the range where the future expected income or the expected income variance changes in the latter half of the transaction period. To determine the combination of transactions with multiple business partners so that the portfolio near the effective frontier (ratio of procurement and sales of power generation and electric power products) can be changed to the portfolio near the late effective frontier. Alternatively, the combination of transactions with a plurality of business partners is determined based on the data of the intersection of the effective frontier and the late effective frontier, or the point on the predetermined neighborhood of the intersection. In particular, by determining the trading position from the portfolio near the intersection, it is possible to obtain an effective plan in both cases where various fluctuations occur and when they do not occur. For example, in a transaction plan for a supply date where extreme fluctuations in market prices are likely to occur, it becomes possible to carry out a transaction plan that is effective in both cases where price fluctuations occur and when they do not occur.

[Processing of hourly order planning unit 30]

In the processing of the hourly order planning unit 30 in steps S301 to S304, the electric power can be traded with the business partner or the market (because the electric power is continuously and continuously supplied to the consumer). The transaction divides the time zone into predetermined intervals (for example, 30 minutes or 4 hours), and trades the power generation and negative watts provided for the power supply in each time zone in the predetermined period before the actual power supply time zone. Period (for example, from 17:00 on the day before delivery to 1 hour before delivery time, from 48 hours to 24 hours before, from 24 hours to 1 hour before, from 10 days to 3 In (traded as) up to the day before), the transaction order data related to the ordering to the business partner and the instruction of the order is generated. Orders are placed in stages in a plurality of planned transaction periods in which the transaction period is subdivided, and an economical ordering plan can be made in response to fluctuations in market prices during the transaction period. Hereinafter, the details of the processes of steps S301 to S304 will be shown.

(Step S301) The transaction ordering time division unit 301 receives the value of the above-mentioned transaction position, and sets the target amount of the procurement (finished position) of the product of each business partner or market in the transaction period as the product toward the position. Divide so that the transaction volume (contracted electric energy (kW)) is even.

The divided values are stored in the target order transition table T2 shown in FIG. 8 or the target order transition table T3 shown in FIG. The target order transition table T2 in FIG. 8 contains an example of data for a 30-minute product wholesaled in the pre-hour market. The target is -300 kW (indicating a position where the sell is 300 kW) as the finish position with 7:00 on July 3 as the finish time, and each of the planned lots divided into 15 will be (-300/15) kW. The target value is to execute the corresponding transaction. In the example of FIG. 8, the transaction period is subdivided into transaction planning periods every 30 minutes, but the transaction planning period is not limited to this, and may be, for example, in increments of 10 minutes. It may be longer in 2 hour increments. The divided ordering unit is called a planned lot. A planned lot may be created for each of the power products. As a result, it is possible to streamline the management of transaction plans and transaction results by shortening the planned transaction period for products with a small number of bids and shortening the planned transaction period for products with a large number of bids.

Instead of this embodiment, division may be performed so that the transaction amount is even. Further, the weighted sum of the transaction quantity and the variance value of the transaction quantity may be divided so as to be equal. Further, the weighted sum of the transaction amount and the variance value of the transaction amount may be divided so as to be equal.

Preferably, it is related to the ordering in the planned trading period in which the trading period is subdivided, and the value of each order data in the planned trading period is corrected by increasing or decreasing depending on the magnitude of the error of the future quantity estimation which is the value of the convergence estimation related to the planned trading period. do. As a result, it is possible to execute preferentially in the planned transaction period with less error, and it becomes possible to plan a transaction that realizes the target transaction volume and transaction profit more stably.

It is also preferable to calculate the degree of disagreement of each valid frontier (or trading position) at each time point of the trading period calculated in step 201 (for example, the distance of the center of gravity of the points (portfolio) included in the set of valid frontiers). ), If the discrepancy is large, the transaction volume during the planned transaction period will be reduced in the future. As a result, when the effective frontier fluctuates in the latter half of the plan, it is not possible to change the procurement composition of power generation and electric power products, and it is possible to obtain transaction results that avoid the occurrence of uneconomical transactions.

(Step S302) The transaction order data determination unit 302 is involved in the ordering in the planned transaction period, refers to the target order recommendation table T2, and determines the value of the transaction order data for procurement of the market product in the planned transaction period. Then, a process of transmitting data to the market ordering terminal 5000 is performed. When the target value M of the transaction quantity to be executed is given, the price data X and the bid quantity O data are generated as in (Equation 1).

Here, M is a variable that specifies the bid quantity (electric energy to be opened), R is a variable that specifies the target contract ratio, P and σ are variables that indicate the market conditions (conditions), and P is the expected transaction price. The value and σ are variables that indicate the variance of the transaction price. The function f refers to a numerical table (for example, a t distribution table) showing the statistical properties related to the market, and sets the price X at which the transaction can be concluded (contracted) at the ratio of R from the confidence interval determined from the distribution of the contracted price. It is a function to give (for example, the confidence interval for being executed at 95% is (P ± 1σ), and if you buy, you can expect 95% of the execution in that period if you specify the price of P + σ). R is a value specified by the user through the input / output interface, for example, 0.1 to 0.9.
(Step S303) The power generation plan processing unit 303 performs a process of simulating a power generation operation plan known as a generator start / stop plan and a load distribution plan for a contracted power generation company. When the result that the operation is possible is obtained by the simulation, the data is transmitted to the power generation ordering terminal 5100. When a simulation result indicating inoperability is obtained, an alert display is output to the input / output interface 70.

(Step S304) The electricity storage demand planning processing unit 304 performs a process of simulating a power saving plan in the contracted DR aggregator. When the result that the operation is possible is obtained by the simulation, the data is transmitted to the aggregator ordering terminal 5200. When a simulation result indicating inoperability is obtained, an alert display is output to the input / output interface 70.

[Effect of this embodiment]

FIG. 13 shows the order results when the transaction plan shown in the embodiment of the present invention was performed and when it was not performed. FIG. 13A is a conventional example in which an order is evenly divided. FIG. 13B shows the result of ordering by the transaction planning apparatus 1 of the present invention. By using the transaction planning device 1, the option of early ordering is given in the time limit (delivery frame, delivery time) where there is no demand error, cheap supply capacity can be used, and early ordering is also permitted according to the convergence rate. Will be done. In the period when there is no demand error, the same applies to the rate of convergence of price and the rate of convergence of photovoltaic power generation, not the amount of demand.

FIG. 15 shows the transition of the order result of the electric power product and the power generation having the supply time T1 when the transaction plan shown in the embodiment of the present invention is performed. FIG. 15 (a) in the figure shows the approximately quantitative and uncontracted quantitative results of the ordering when the fluctuation of the future quantity estimated amount that occurs during the trading period is small. The unfilled amount is increasing in proportion to the remaining trading time (the fixed amount is decreasing).

FIG. 15 (b) shows the approximately quantitative and uncontracted quantities as a result of ordering when the fluctuation of the future quantity estimated amount that occurs during the trading period is large. The unfilled amount has increased exponentially with respect to the remaining trading time (the fixed amount has decreased). This is due to the fact that orders have been postponed due to uncertain future market conditions and the magnitude of demand (the magnitude of fluctuations in the estimated future quantity).

A contract is a successful bid (sending of a telegram) to a market (also called a market), or the delivery of electric power to a power generation company or a negawatt supplier (aggregator). An agreement has been reached on the offer and an agreement has been reached on the offer for commercial transactions.

FIG. 14 shows the result (a) of the profit of the seller and the amount of discrepancy between the demand amount and the supply amount (imbalance amount) when the transaction plan according to the embodiment of the present invention is performed and when the transaction plan is not performed. Is an example of the occurrence result (b). FIG. 14 (a) shows a histogram of the rate of return from the first week to the 52nd week of the target year, and FIG. 14 (b) relates to the imbalance that occurred from the first week to the 52nd week of the target year. Shows a histogram. The dotted line shows the result of the conventional equal ordering, and the solid line shows the result of the transaction plan in the embodiment of the present invention.

Conventionally (dotted line), as shown in Fig. 11B, the order is fixedly placed from the initial stage of the entire transaction without considering the occurrence of multiple errors as shown in Fig. 11B, so the profit and imbalance are balanced. The amount and the skirts are spread and dispersed in many peaks. In the transaction plan of the embodiment of the present invention, the error between the profit and the imbalance amount is reduced.

According to this embodiment, it is possible to execute a transaction plan in response to market trends, fluctuations in demand, and operating conditions of business partners, and determine the amount and timing of orders placed with business partners and markets based on the results. It will be possible.

<< Second embodiment >> << Modification example: Time arbitrage >>

The transaction planning apparatus 1 of the present embodiment is based on a future quantity estimation unit 10 including a demand control quantity estimation unit that generates an estimation quantity of quantity or time data related to a change in the occurrence of demand, and a value of the demand control quantity ( It is provided with an order quantity planning unit 20 provided with a demand control limiting unit for adding / subtracting data of transaction positions (values of positions of transactions having different delivery times).

The transaction plan makes it possible to plan a transaction in consideration of demand response and demand induction by storage control.

Also, increase the demand for cheap time (storage, etc.) and reduce the demand for high time. However, the amount that can be traded can be limited to the amount that can be absorbed by charging and discharging the storage battery and the shift time width.

<< Third Embodiment >> << Modification: Reservation transaction of power transmission right >>

The transaction planning device 1 of the present embodiment includes a supply estimation unit that estimates the future amount of supply of renewable energy power generation, and a future amount estimation unit 10 that includes a demand estimation unit that estimates the future amount of demand of contract consumers. It is provided with an order quantity planning unit 20 including a transaction position determination unit 201 that sells power generation according to an amount of renewable energy power generation exceeding the demand amount.

With such a transaction plan, a transaction plan that enables the generated power generation to be supplied can be made.

Further, the transaction planning device 1 of the present embodiment includes a future amount estimation unit 20 including an estimation unit for estimating the future amount of free capacity of the transmission line and the interconnection line, and a transmission line utilization plan for creating a transmission line utilization plan. It is provided with an hourly ordering planning unit 30 including a unit.

With such a transaction plan, the occurrence of a business that stops the power generation of renewable energy due to the saturation of the transmission line is avoided, and the generated power generation is made available for supply through the transmission line and the interconnection line. It will be gained. This will result in transactions that also reflect the economic value of reducing sunk costs incurred by shutting down renewable energy.

<< Fourth Embodiment >> << Coordination Power Transaction >>

The transaction planning device 1 of the present embodiment includes a future amount estimation unit 10 including an estimation unit for estimating a future amount estimation amount (for example, the price of the adjustment power transaction and an estimated amount in the transaction quantity) related to the adjustment power transaction. It is provided with an order quantity planning unit 20 including a transaction position determination unit 201 that determines the amount to be provided to the adjustment power, updates data related to the demand amount according to the adjustment power provision amount, and calculates a transaction position. ..

Such a transaction plan makes it possible to plan transactions, including transactions related to adjustment power that are difficult to buy back, as promised to be provided when externally needed.

Further, the transaction planning device 1 of the present embodiment calculates a convergence estimation value for estimating an estimated amount of data (for example, variance or likelihood value) related to an error in the future amount estimated from the actual value, and performs an order quantity planning or an order quantity plan. You can also do a time division plan.

The above description can be summarized as follows, for example.

(1) The management device according to one embodiment includes a transaction position determination unit that receives cumulative amount of transactions and estimated data of future amount regarding demand and business partners and determines the amount of transactions to a plurality of business partners. It is characterized by having an order quantity planning department.

This makes it possible to plan transactions according to the ever-changing future volume.

(2) The order quantity planning unit of the management device of the above (1) is characterized by having a data table capable of taking positive and negative values as data related to each of a plurality of transactions.

As a result, it becomes possible to carry out a sell transaction and a buy transaction at the same time for products having the same delivery period (delivery date and period for continuing to provide services). Preferably, the energy delivered over several hours is bought in the wholesale transaction according to the peak supply, and the residual supply generated outside the peak supply time is sold and provided in the wholesale transaction to promote the efficient use of the energy. It will be possible.

(3) The management device according to the embodiment is an order price (for example, a buy bid price, a sell bid) related to a transaction order in a planned transaction period, which is a subdivided period in the passage of time during the transaction period in which a transaction can be made. It is characterized by having an hourly order planning unit including a transaction order data determination unit that generates transaction order data including data on the price) or order quantity.

This makes it possible to efficiently plan transactions in each time section of the transaction period.

(4) The management device according to one embodiment includes a future quantity estimation unit including a convergence estimation unit that estimates an estimated amount of data (for example, variance or likelihood value) related to an error in the future quantity estimated from actual values. There is.

This makes it possible to plan transactions (for example, planning the order quantity and planning the time division of the order processing) according to the situation of whether the estimation accuracy of the future quantity is good or bad.

(5) When the difference between the total transaction volume with all business partners and the future demand volume is more than a predetermined value, the order volume planning unit of the management device according to the embodiment (transactions). It is provided with a trading position determination unit characterized by increasing or decreasing the trading volume with any of the trading partners (based on the trading price with each of the above or the estimated value of the trading volume).

(6) Preferably, when the estimated value of the transaction price with a certain customer is cheaper than the transaction price related to the cumulative transaction of all transactions, the transaction position determination unit allocates the transaction with the customer. It is characterized by increasing the amount and decreasing the transaction quota with a certain business partner when the estimated value of the transaction price with the business partner becomes expensive.

(7) More preferably, the trading position determination unit reduces the transaction volume allocation to the trading partner whose data value regarding the transaction price error (diversification or likelihood) of each trading partner has increased, and the data regarding the error decreases. It is characterized by increasing the transaction volume allocation to the business partners.

This makes it possible to place orders that meet demand with economic rationality. Preferably, it is possible to place an order with reduced losses that may occur due to various fluctuations in future quantities.

(8) The order quantity planning unit of the management device according to the embodiment calculates the combination of transactions based on the effective frontier calculated from the expected profit from the transaction and the risk of the expected profit (for example, the value of the diversification of the expected profit). However, the effective frontier of the latter half of the transaction is calculated from the data in the range where the expected future profit or expected profit diversification changes in the latter half of the transaction period, and the latter half is calculated from the portfolio near the effective frontier (ratio of procurement and sales of power generation and electric power products). It is characterized by having a trading position determination unit that determines the combination of transactions with multiple trading partners so that it can be changed to a portfolio near the effective frontier.

As a result, the estimation related to the future amount (for example, the demand amount on the day of supply, the estimated amount of the market transaction price of the transaction related to the time, and the estimated amount of these dispersion values (convergence estimated amount)) is initially set. Even if the target planning result changes from the result of the optimal trading plan at the initial time point to the result of the optimal trading plan at the late time point when it is expected that the estimation of It will be possible to carry out transactions throughout.

More preferably, the larger the evaluation value over time of the convergence of the estimated value related to the future quantity, the later the ordering time is characterized.

This makes it possible to trade according to the most economical portfolio even when the amount of change in the effective frontier in the latter period is large.

(9) The management device according to one embodiment includes an hourly ordering planning unit including a transaction ordering time dividing unit that divides the ordering amount to each of the business partners into the target value related to the time transition of the ordering during the trading time. It is characterized by that.

As a result, even if the estimated value of the future quantity cannot be determined, the transaction plan is to efficiently secure the quantity to be finally supplied to the customer by sequentially changing the order quantity to the customer. Can be done.

(10) Preferably, the management device of the present invention is involved in an order in a planned transaction period in which the transaction period is subdivided, and each plan is based on the magnitude of the error (dispersion or probability) of future quantity estimation related to the planned transaction period. It is characterized by having an hourly transaction planning unit that increases or decreases the value of order data during the transaction period.

As a result, transactions with less error can be executed preferentially, and it becomes possible to plan a transaction that realizes a target transaction volume and transaction profit more stably.

(11) The management device according to the embodiment preferably has data on the target transaction quantity in each of the planned transaction periods at predetermined intervals generated based on the data on the target order transition (for example, from 48 hours before the delivery time). Divide the trading period of the product whose trading period is up to 24 hours ago, set the planned trading period every 10 minutes, and set the target value of the trading volume to be completed in each trading period). Hourly ordering including a transaction order data determination unit, which comprises creating transaction order data including a weighted addition of an estimated transaction price and an estimated transaction price error according to the difference between the target transaction volume and the actual transaction volume. It has a planning department.

This makes it possible to make a transaction plan to complete the transaction of the required transaction quantity.

For example, when it is desired to secure the quantity to be procured or sold for the gate closing of the trading market, the bid price is determined by this method. When collecting the quantity of procurement as a buyer, it is possible to determine the bid price as follows in the bidding by this method. For the expected price P and its dispersion σ, if you buy and bid the bid price with the value of P + σ (P), you can make a successful bid with a 95% probability, and if you bid with the value of P-σ (P), you can make a successful bid with a 95% probability. Based on the statistical trends that can be made, determine the bid price that can execute the required quantity. More preferably, the bid price can be set to a low value at the initial stage of the transaction in which the contracted amount is small, and can be appropriately changed to a high value such as the bid price P + σ at the stage where the transaction quantity is required. In the case of a power generation seller, the bid price will be higher at a good time when the contracted amount is small, and the bid price will be set to P-σ so that the bid price will be sold more when the cooked power generation is to be sold out according to the generator stop constraint. It is possible to obtain an appropriate change to a lower value in the morning.

(12) The management device according to one embodiment includes a transaction order data determination unit that generates data on transaction amounts to be performed in a planned transaction period at predetermined intervals based on estimated future quantity data and creates transaction order data. It is characterized by.

Preferably, it is provided with an hourly order planning unit including a transaction order data determination unit that generates transaction order data from transaction amount data obtained by adding or subtracting a value obtained by multiplying an estimated error of an estimated future quantity by a coefficient from the above transaction amount. ..

As a result, even if the future volume fluctuates during the full year of the transaction period (for example, fluctuations in transaction prices or fluctuations in demand), the transaction cost leveling effect will not cause the payment amount to become excessive. You will be able to plan transactions.

More preferably, the transaction amount to be performed during the planned transaction period at predetermined intervals is planned so that the transaction amount after risk allocation (the value obtained by subtracting the value obtained by multiplying the variance value ρ by the coefficient from the expected transaction amount Q) is equal. It is characterized by that. With such a transaction plan, it is possible to carry out a transaction plan in which the amount to be exercised is large when the error in the estimated amount of the transaction price or quantity is small, and the transaction amount is small when the error is large (the market risk is large). Efficient trading can be performed regardless of market risk.

(13) In the management device according to the embodiment, the delivery time (supply time) overlaps (as a result, the actual supply is offset), and the order quantity for the purchase of the product and the order quantity for the sale are restricted. It is characterized by having an order quantity planning unit that determines a trading position within a range.

By limiting the order quantity, it is possible to plan a transaction that matches the actual supply without increasing the transaction volume without limitation.

For example, it is possible to determine arbitrage transactions and their appropriate amounts when the trading partners and trading markets are different. If the same electric power products (for example, electric power products that can be used for supply in the same time zone) are different, the price will be different in the pull market (when (one item, two prices) occurs, procure in the cheap market and sell in the high market. If the arbitrage transaction is carried out without an upper limit, the loss realized when the predicted price deviates becomes an issue and the business operation is hindered. However, according to the transaction plan of the present invention, the realized loss is allowed. It will be possible to plan transactions that remain within range.

For example, in a transaction in which a 4-hour block of power generation is bought and a 30-minute spot is sold (double-decker), the upper limit of the opposite position is limited so that the transaction volume does not increase without an upper limit due to the double-decker. For example, the evaluation is performed using the profit after risk allocation. Alternatively, an upper limit of a predetermined value is set, or an upper limit is set with a predetermined N times the actual supply as the transaction upper limit.

(14) The management device according to one embodiment includes data on prices during a transaction period (for example, closing price in market transactions and weighted average price (WACC)) and data related to convergence (dispersion value and convergence speed of distribution value). ) Is calculated, the magnitude relation with the seller's bid price in the market is compared, and the transaction order data determination unit for generating the transaction order data is included.

Based on this transaction plan, the overall rationality is to promptly respond to the purchase of products that other businesses urgently need at a high price and the offer (bid) for power interchange at a low price for the remaining products through the market. It will be possible to plan transactions with sex and economic rationality for trading companies.

<< Fifth Embodiment >>

FIG. 16 is a block diagram showing a configuration of functions of a management device according to a fifth embodiment of the present invention.

The management device 1601 includes a sales revenue calculation unit 1611, a balance forecast spread calculation unit 1612, and a charge unit price search unit 1613.

The sales revenue calculation unit 1611 calculates the sales revenue by supplying the demand by using the hourly rate unit price for each demand category and the value of the electric power usage. "Demand category" is a division unit of demand. Demand included in the "demand category" is demand having the same attributes such as contract type, industry type, demand point, and demand occurrence time. Information for each demand category is stored in the demand category table 1621. The demand category table 1621 stores, for example, attributes common to the demand category for each demand category, an hourly rate unit price, and a value of electric power usage (hourly usage amount and contract maximum amount). The sales revenue calculation unit 1611 can calculate sales revenue for each demand category based on the demand category table 1621. The sales revenue calculation unit 1611 stores the calculated sales revenue for each demand category in the demand category table 1621.

The balance forecast spread calculation unit 1612 is used to display a plurality of futures regarding the power consumption (demand), the contract price of the market, and the supply amount for a predetermined period (for example, 1 day, 1 week, 1 month, 3 months, 1 year) of the demand category. Compare the balance (sales revenue and supply cost (cost required for supply)) in each of the quantity estimation time series. The "future amount" is the future amount of electricity used, the contract price, the power source, and the amount of supply from the market estimated by the future amount estimation unit 10. The future quantity includes the future value of the unit price when the unit price for each demand category is automatically generated. The estimated future quantity may be at least one of demand, contract price and supply. The demand category table 1621 stores, for example, a plurality of future quantity estimation time series for each demand category. From this table 1621, a plurality of future quantity estimation time series can be found for each demand category. In addition, for each future quantity estimation time series, the supply cost can be calculated based on the future quantity at each date and time. The "predicted spread" is an index showing the magnitude of the variation in the value of the result obtained by performing the calculation (simulation) of the forecast under different conditions. In this embodiment, the value of the difference between the prediction result having the largest value and the prediction result having the smallest value is used.

The charge unit price search unit 1613 searches for a charge unit price that satisfies the constraint condition for each demand category based on the result of comparison by the balance forecast spread calculation unit 1612. For example, for each demand category, the hourly rate can be increased or decreased based on the difference between the sales revenue and the cost required for supply. The constraint condition table 1622 shows the relationship between the constraint condition and the charge unit price for each constraint condition, and the charge unit price search unit 1613 may search the charge unit price based on the table 1622.

By making such a transaction plan, it is possible to set an appropriate unit price. It can contribute to the formulation of transaction plans that take into account the balance of individual categories and the range of fluctuations in the balance.

Preferably, the charge unit price search unit 1613 includes an input unit 1614. The input unit 1614 is (a) data on the upper and lower limits of the sales revenue amount of each demand category, and (b) the balance forecast spread which is the difference between the balances calculated in each of the plurality of future scenarios (time transition of the future amount). Enter one of the constraints of the upper limit data. Contractors in the demand category decrease or diverge when the amount of charges to be paid is relatively high compared to others, but this makes it possible to set a unit price that does not cause a decrease or divergence. It is also possible to set a unit price that does not cause an increase in contracts that exceeds the amount that can be supplied. Furthermore, according to the constraint condition of (b), since there is an upper limit of the difference in income and expenditure, stable supply is obtained by obtaining an appropriate fee income in which the fluctuation of income and expenditure is within a predetermined range regardless of any of multiple future scenarios. Can be maintained. The input unit 1614 stores the constraint conditions in the constraint condition table 1622. The stored constraint condition is associated with the demand category (for example, the constraint condition ID is stored in the demand category table 1621). In addition, at least one "future scenario" may include time transitions of demand, market, and weather in addition to time transitions of future quantities. If the unit price is generated to prevent the separation of consumers, the unit price will change in the future, and such a unit price may be included in the future quantity. Further, the information representing the plurality of future scenarios is stored in the future scenario table 1623, which stores the information for each future scenario.

Preferably, the sales revenue of the demand category is in the range of predetermined values. The hourly unit price allocation ratio is adjusted, for example, by the charge unit price search unit 1613. By making such a transaction plan, the charge amount of the demand category is specified at the same level as other electric power companies, and the ratio of the daytime unit price and the nighttime unit price is changed to minimize the fluctuation of the balance against the fluctuation of the future scenario. Is possible.

The functions 1611 to 1614 and the tables 1621 to 1623 described above are stored in the storage device 40.

<< 6th Embodiment >>

FIG. 17 is a block diagram showing a configuration of functions of the management device according to the sixth embodiment of the present invention.

The management device 1701 can function as a power generation and procurement adjustment device having the maximum balance. For example, the management device 1701 includes a supply cost calculation unit 1711 for each category, a balance calculation unit 1712 for each demand category, and a supply source search unit 1713.

The supply cost calculation unit 1711 for each category sets the supply cost for each demand category (for example, the period unit price obtained by weighting and averaging the supply unit price of each supply source used at each time by the supply amount, and the demand value at each time of the demand category. The product is totaled in a predetermined period). The supply unit price and the supply amount for each supply source are stored in, for example, the supply source table 1721 for storing the information of the supply source for each supply source. Further, each time demand value for each demand category is stored in the demand category table 1621. Based on these tables 1721 and 1621, the supply cost calculation unit 1711 for each category can calculate the supply cost for each demand category. A specific example of the "supply source" is the above-mentioned power generation business system 2000 (see, for example, FIG. 1). Further, the power generation business system included in the market system A3000 and the negawatt of the market system B3100 are also specific examples of the supply sources.

The balance calculation unit 1712 for each demand category calculates the balance of a predetermined demand category (the difference between the sales revenue of the demand category and the supply cost).

The source search unit 1713 searches for a combination of sources for each time that satisfies the constraint condition based on the balance (and the source table 1721 and the constraint condition table 1622).

Preferably, the source search unit 1713 includes an input unit 1714. The input unit 1714 inputs the data of the constraint condition that the supply cost for the predetermined demand category or the balance value due to the supply to the predetermined demand category is set to the minimum or the maximum. do. Alternatively, the input unit 1714 inputs the data of the constraint condition of the upper limit value and the lower limit value for either the cost or the balance. By making such a transaction plan, in addition to reducing the total supply cost for all demand categories, the supply cost for a predetermined demand category (for example, a demand category that is important as a management issue) can be reduced. Can also be achieved. The input constraint condition is stored in the constraint condition table 1622.

Preferably, the management device 1701 further includes a category balance estimation unit 1715 and a demand category forecast balance spread calculation unit 1716 in addition to the functions 1711 and 1712. The category balance estimation unit 1715 transfers the supply cost for a predetermined demand category (for example, the product of the period unit price and the total demand value of the demand classified in the demand category to the total in a predetermined period) and the demand category. Calculate the category balance including the calculation with the income value from the supply of. The forecast balance spread calculation unit 1716 for each demand category compares the balance for each of a plurality of future scenarios (for example, time transition of demand, market, and weather) for each demand category. In place of or in addition to the above search, the source search unit 1713 determines that the forecast balance spread (multiple balances corresponding to multiple future scenarios) is the minimum or less than a predetermined value for each demand category. Search for a combination. The "period unit price" is the contract price of the delivered power in the market, the procurement unit price from the power generation system under the bilateral contract, or the weighted average value thereof. The "period" is the delivery period (in a narrow sense, one frame of market A (for example, 30 minutes) is sufficient).

The combination of sources (unit commitment) cannot be changed significantly once it is decided. For this reason, it is difficult for the source search unit 1713 to find a candidate for a feasible solution (combination of sources) that satisfies the constraint conditions in any future. Therefore, U = [u1, u2, u3, u4, u5] ^t , which gives a combination of supply sources necessary for a predetermined demand, and ui = [di (1), di (2), di (3) ,. .. .. , Di (46), di (47), di (48)] (where i is the unit number of the source. Di (j) is purchased when i is activated in the j period or as a market product. In the case of 1, there is a variable that becomes 0 if it is stopped or not purchased as a market product). Let Φ (U) be the set of U that can be changed from U.

Further, let U (D1) be the executable U for the scenario D in the future. A "feasible U" is, for example, a combination of sources capable of fulfilling contracted demand and supply to the market.

Included in Φ (U (D1)) ∩Φ (U (D1)) ∩Φ (U (D3)) of the product set of feasible solutions for multiple future scenarios (eg D1, D2, D3) Search for U * as the planned value.

As one embodiment, Φ (U (D1)), Φ (U (D2)), and Φ (U (D3)) may be searched for by brute force.

In one embodiment, the time series of the predicted value of the supply amount (the sum of the supply to the contracted customer and the sale to the market) is D1, and the predicted value D1 of the supply amount is given a predetermined weight of 1 or more. Search for feasible sources U (D1), U (D2), U (D3) for multiple supplies, such as D2 multiplied and D3, the predicted value of supply D1 multiplied by a weight of 1 or less. do. At that time, the search is performed by setting a constraint so that there is no difference in the start-up units between the supply sources, for example, so that the number of start-ups and stops in an arbitrary time section is constant. At this time, the optimization calculation may be performed so that the difference in cost for each of the supply sources U (D1), U (D2), and U (D3) is minimized.

Specifically, the minimization term in the "optimization calculation" is (X1) the supply source cost for supply (specifically, the fuel cost consumed for supply or the contract price for market transactions for power procurement). , (X2) The sum of the deviations of the supply source costs in each scenario M (Equation 2) or the dispersion V (Equation 3) may be used to set the weighted average of (X1) and (X2). (Here N is the number of future scenarios, in one example N = 3).

Using such a minimization term, it is possible to create a plan in which the cost of supply does not increase sharply when weather conditions, demand, or market contract prices fluctuate. This is because (X2) acts as a penalty term in the optimization calculation, and a solution that does not touch the cost is searched.

In addition, as the maximization term in the optimization calculation, (Y1) and (Y2) are calculated by using the sum or variance of (Y1) the balance between supply and sales and (Y2) the deviation of the balance in each scenario. It may be set by weighted average. By using such a maximization term, it is possible to create a plan in which the balance does not change suddenly when the weather conditions, demand, or market contract price fluctuates.

Further, the predetermined demand category K, the future scenario is Di, and the supply cost for each demand category is SC (K, Di). The deviation or variance in each scenario of SC (K, Di) and SC (K, Di) may be added to the minimization term. As a result, it is possible to prevent the supply cost for the predetermined demand category K from becoming large, or the supply cost from changing sharply when the weather conditions, the demand, or the contracted market price fluctuates.

In addition, the balance P (K, Di) is defined by demand category. Deviations or variances in each P (K, Di) scenario may be added. As a result, it is possible to prevent the supply cost from changing sharply when the balance between sales and supply in a predetermined demand category K fluctuates due to weather conditions, demand, or market contract price. Further, P (K, Di) may be added to the maximization term. It is possible to avoid future source costs increasing relative to sales revenue to demand category K.

The future scenario may be generated not only by multiplying D1 by a fixed value, but also by multiplying it by a value corresponding to the size of the forecast spread of the weather forecast at the future time. The number of future scenarios is not limited to three. For example, when creating a future scenario by generating forecast time series of future temperature and sunshine by weather numerical forecast simulation and further generating forecast values of demand, renewable energy generation amount, and contract price, meteorological numerical forecast. In the simulation, the initial conditions are set by adding the initial perturbations to the meteorological observation values and the simulation is performed. When this initial perturbation is generated over 20 ways, for example, 20 scenarios can be generated in the future.

(Explanation of effect)

In FIG. 20 (FIG. 20A, 20B, 20C), the supply source search device (an example of the management device) of the present embodiment is not used, and the cost for supply is the minimum for each of D1, D2, and D3. The combination result of the supply sources when the optimization calculation (minimum cost method) for finding the combination of the supply sources is performed is shown.

FIG. 21 (FIG. 21A, FIG. 21B, FIG. 21C) shows the search results using the source search device of the present embodiment.

The horizontal axis of the figure is the delivery time, which indicates "10A" from 10:00 to 10:30 and "10B" from 10:30 to 11:00. The vertical axis is the machine number that identifies the supply source. The dark color in the table indicates that the source is operating or purchased as a market item.

In addition, future scenario D1 is a future scenario that uses the median value of demand and market contract price forecasts for power delivery at each time. The future scenario D2 is a future scenario in which the sales volume (demand) has increased due to an increase in sales to the market due to a higher market contract price than in the case of D1. The future scenario D3 is a future scenario in which the market contract price remains lower than that of D1 and the sales volume (demand) decreases due to a decrease in sales to the market.

In the plan based on the minimum supply cost method that does not use the method according to this embodiment, it is planned that Units 5 and 6 will not be operated and Unit 4 will be operated in future scenario D1 (Fig. 20A). ). In the plan for future scenario D2, Unit 6 which is not scheduled to be operated in the case of future scenario D1 is being operated due to the increase in demand from 16:00 to 18:00 than in the case of D1 (Fig. 20B). .. In the future scenario D3, the demand from 17:00 to 18:00 is less than that of D1, so Unit 4 with a rated capacity larger than Unit 5 will not operate in the first place, but instead will operate Unit 5. It is planned (Fig. 20C).

In this way, in the plan by the minimum cost method, the future scenario D1, D2, and D3 each have the minimum cost, but the future scenario changes (the output of the future quantity estimation unit changes when the weather forecast is updated). It is not possible to operate an actual power generation system that needs to be prepared to have operators from the previous day under any future scenario because the generators and supply sources that are operated every time change.

On the other hand, according to the method according to the present embodiment, as shown in FIGS. 20A, 20B, and 20C, Unit 4 is not operated in any of the future scenarios D1 to D3. If the demand increases from 16:00 to 18:00, it can be dealt with by the operational impact of Unit 6 (Fig. 20B). In addition, it can be seen that if the demand from 17:00 to 18:00 decreases, it can be dealt with by shortening the operating time of Unit 5 (Fig. 20C).

Plan by shortening or extending the operating time of a source that can respond to specific preparations for any future scenario without changing the preparation of the power generation system operator to be deployed from the previous day or the fuel preparation. It can be seen that driving along can be realized.

The search process of the unit price search and the combination search of the supply source in the present embodiment is realized by the interior point method for searching the solution based on the constraint condition, the Karmarkar method, the branch-and-bound method, or the constraint programming method. .. In addition, a brute force method may be used to search the table data of solution candidates arbitrarily specified by the user. The present invention is not limited to these, and heuristic methods such as genetic algorithms and reinforcement learning methods may be searched.

The functions 1711 to 1716 and the table 1721 described above are stored in the storage device 40.

<< 7th Embodiment >>

FIG. 18 is a block diagram showing a configuration of functions of the management device according to the seventh embodiment of the present invention.

The management device 1801 can function as a contract transition rate estimation device. For example, the management device 1801 includes a charge menu value difference estimation unit 1811, a charge menu-specific contract ratio estimation unit 1812, a sales revenue calculation unit 1813, a charge menu-specific contract ratio constraint condition input unit 1814, and a charge unit price search unit 1815. ..

The charge menu value difference estimation unit 1811 describes the payment amount in the charge menu of the candidate for change (the payment amount after the provisional change) and the payment amount in the charge menu before the change (before the change) with respect to the electricity charge paid by the consumer. Estimate the difference from the payment amount). This estimation may be made by demand category or by consumer. Further, this estimation may be performed based on the charge menu table 1821. The charge menu table 1821 stores information about a plurality of charge menus. The table 1821 may store information on the charge menu before and after the change for each charge menu. Further, which consumer corresponds to which charge menu can be specified based on the consumer table 1822 that stores information for each consumer.

The contract ratio estimation unit 1812 for each charge menu estimates the selection ratio of each charge menu in the future planning period based on the charge menu value difference estimation amount (estimated difference). The contract ratio estimation unit 1812 for each charge menu calculates, for example, the switch rate (contract change rate) from the logistic regression curve to the next planning period, and selects each charge menu in the future planning period based on the calculated switch rate. The percentage can be estimated. For example, the estimation unit 1812 changes the contract to another charge menu when x% of the consumers as a set classified into the demand category have a difference in the monthly payment amount of y yen (presented by another company). In the case of a change to the current rate menu, it is possible to make an estimation of "separation"). Although it is deterministically treated as a "ratio" here, it may be stochastically treated as a "possibility" of change from an individual perspective.

The sales income calculation unit 1813 calculates the sales income for each demand category based on the payment amount. Specifically, the sales revenue calculation unit 1813 calculates the sales revenues of the payment amount before the change and the payment amount after the change. More specifically, for example, usually, after the charge unit price search unit 1815 makes a proposal for changing the charge unit price by the process described later, the sales revenue calculation unit 1813 calculates each sales income (furthermore, For example, processing to visualize those sales revenues in a comparable manner) is performed.

The contract ratio constraint condition input unit 1814 for each charge menu specifies an increase / decrease rate of the contract ratio for each charge menu of the demand category (an example of the constraint condition for the contract ratio for each charge menu).

The charge unit price search unit 1815 determines the charge unit price at which the contract ratio or the number of contracts becomes a predetermined value based on the designated increase / decrease rate. The unit price is determined from, for example, a logistic regression curve. For example, it is assumed that the rate of increase / decrease follows the logistic regression curve of (Equation 4). The rate of increase / decrease Y is calculated using the price difference (estimated amount of price menu value difference) X and the coefficients a, b, and c. The coefficients a, b, and c may be determined from the past data by the estimation process of logistic regression.

The functions 1811 to 1815 and the tables 1821 to 1822 described above are stored in the storage device 40.

<< Eighth Embodiment >>

FIG. 19 is a block diagram showing a configuration of functions of a management device according to an eighth embodiment of the present invention.

The management device 1901 can function as an evaluation device for the acquisition value. For example, a scenario management unit 1911 and an additional effect estimation unit 1912 of a demand or supply source are provided. The target of "acquisition" is at least one of the following,
・ Sales rights to demand,
・ The right to receive supply from the power generation system (purchase right), the power generation system itself, and
・ Purchase and sales rights for other products (transmission rights, fuel, negawatt usage rights) handled in Market B,
It's fine. The target of the acquisition may be a company (for example, a new electric power company), and it is possible to acquire sales rights and purchase rights by acquiring the company. In addition, "scenario" may be synonymous with future scenario. However, in this embodiment, the generation of future scenario candidates is different from the above-described embodiment. Specifically, the demand increased by the acquisition and the amount of the supply source increased by the acquisition are added (the above-described embodiment is a scenario of an uncontrolled phenomenon in which the demand increases because the temperature rises, and the scenario of the present embodiment. Is the scenario when controlling (acquiring)).

The scenario management unit 1911 determines the balance forecast spread using the first scenario (designated scenario), the second scenario (the value of supply and demand in the first scenario, and the value of demand in a predetermined demand category). Alternatively, a balance forecast spread using a scenario in which the supply values of a predetermined supply category are added or changed) is calculated. Information about the scenario (for example, the value of supply and demand of the scenario) is stored in the scenario table 1921 for storing the information for each scenario, for example. The demand value or the supply value of a predetermined demand category is stored in, for example, the demand category table 1621. The scenario management unit 1911 can calculate the balance forecast spread using the first scenario and the balance forecast spread using the second scenario based on the tables 1921 and 1621. Further, the "supply category" is a division unit of a supply source (a division unit according to the classification of attributes). Sources included in the same "supply category" are sources with the same attributes such as power generation fuel type, capacity, power generation time zone, installation point, and product type when conducting wholesale power trading.

The additional effect estimation unit 1912 of the demand or supply source compares and displays the balance forecast spread using the first scenario and the balance forecast spread using the second scenario.

The functions 1911 to 1912 and the table 1921 described above are stored in the storage device 40.

<< Ninth Embodiment >>

It corresponds to the summary of the fifth to eighth embodiments (which may include at least one of the first to fourth embodiments). The summary may include matters not described above.

The processor unit of the management device displays the screens exemplified in FIGS. 22, 29, 33, 37, 43, 47, and 53 (for example, GUI (Graphical User Interface)). Specifically, for example, the processor section of the management device is described in STEP 1: Consumer grouping and visualization of monetization structure.
STEP2: Formulation of rate contracts,
STEP3: Formulation of power supply configuration and
STEP4: Creating a weekly plan (the period may not be limited to a week),
Take or support such steps. The information displayed on these screens is displayed based on at least a part of the information managed by the management device. That is, the information displayed on these screens is stored in, for example, a storage unit (for example, a memory unit) in the management device, and the information is displayed on the following screen based on the information.

The processor unit of the management device displays the screen 2200 exemplified in FIG. 22 for STEP1. Specifically, FIG. 22 shows the overall configuration of the toll revenue simulator screen 2200. The information portions 2201 to 2206 shown in FIGS. 23 to 28 are displayed on the screen 2200, respectively. Specifically, it is as follows.
(Fig. 23: Information part 2201) Outputs the result of processing to classify the collected time-series data of demand into demand categories (display part of "customer grouping" on the upper left).
(Fig. 24: Information part 2202) Outputs the calculation results of income and expenditure, supply cost, and sales revenue for each demand category (display part of "Revenue evaluation" at the lower left).
(Fig. 25: Information part 2203) The value of the charge unit price related to the sales revenue is input, and the input charge unit price is displayed. The charge unit price is saved by specifying the charge menu name (upper center of the screen). The charge menu is saved by adding the conditions of the consumers who can subscribe and the attributes of the demand categories that can be subscribed. (Middle of the center of the screen). These are the input and display of charge menu settings. (Upper half of the center of the screen).
(Fig. 26: Information part 2204) Set the trial calculation conditions for the supply cost. (I / O section of "Power generation / procurement cost setting" at the bottom center of the screen). Here, the ratio of power generated by the in-house generator to the power supplied, the ratio of power generation from the power generation system contracted with each other, the ratio of market procurement from each market (the ratio of the spot market, the ratio of the pre-hour market). ) Accepts the input of the default value and displays the input result. Assumed values of each power generation cost and market contract price are stored in a database (not shown).
(Fig. 27: Information part 2205) The charge menu in (3) above is displayed as the charge menu name, charge unit price (basic charge and metered charge), and subscription conditions (display part of "charge menu display" on the upper right of the screen). .. Of the charge unit prices, the unit price that differs for each hour (unit price for each time zone of the metered charge) is displayed as a graph with the time zone as the good axis and the unit price value as the vertical axis.
(Fig. 28: Information part 2206) A display unit of "power generation / procurement cost display" at the lower right of the screen that displays time-series values for a predetermined period (for example, one year) for the trial calculation conditions related to the supply cost).

The processor unit of the management device displays the screen 2900 exemplified in FIG. 29 regarding the execution of STEP2. Specifically, FIG. 29 shows the overall configuration of the rate contract formulation screen 2900. The information portions 2901 to 2903 shown in FIGS. 30 to 32 are displayed on the screen 2900, respectively. Specifically, it is as follows.
(FIG. 30: Information part 2901) The charge unit price is replaced with the value input by the user, and the charge unit price that satisfies the specified condition is searched (the search is executed by applying the execute button in FIG. 30). .. The search conditions for the unit price are the future scenario (variation between the estimated demand value and the estimated demand value), the value of the charge menu contracted by each customer (customer attribute), the hourly ratio of the power supply (procurement), and the illustration. It can be specified by reading from a database that is not. In addition, in the charge unit price search, options for minimizing the balance and cost related to a specific demand category (displayed as "demand group" in the screen example) and minimizing the fluctuation of the balance and cost can be specified. (The above is the input / output section of "condition setting" on the left side of the screen in FIG. 29).
(Fig. 32: Above information part 2903) Estimated values for power procurement and sales are read from the database, and the horizontal axis is time (displayed in quarters or one year), and the upper half of the vertical axis is procured. Volume (displaying the ratio of power supply and power procured from the market as a bar graph for each delivery time), supply volume at each delivery time corresponding to the lower half (sales to own customers and sales to the market) ) Is displayed as a bar graph (display section of "power supply configuration" on the upper right of FIG. 29).
(FIG. 31: Information portion 2901 and FIG. 32: Below the information portion 2903) The searched charge unit price satisfying the search condition is displayed in the display unit (center of the screen of FIG. 29) of the "charge agreement". The balance, sales revenue, and supply cost at the searched unit price are displayed by demand category. (Display section of "Balance evaluation by group" at the lower right of FIG. 29).

By applying the result save button of FIG. 30, the search result is saved after the search is executed by designating the search conditions. Each of the saved results is posted on the "simulation result" screen 3300 (FIG. 33). The screen 3300 shown in FIG. 33 displays, for example, information portions 3301 to 3303 (FIGS. 34 to 36) showing simulation results 1 to 3.

The processor unit of the management device displays the screen 3700 exemplified in FIG. 37 regarding the execution of STEP3. Specifically, FIG. 37 shows the overall configuration of the power supply configuration formulation screen 3700. The information portions 3701 to 3705 shown in FIGS. 38 to 42 are displayed on the screen 3700, respectively. Specifically, it is as follows.
(Fig. 38: Information part 3701) Enter the conditions for searching the power source configuration (the ratio of power generation and market procurement sources at each delivery time, which is a condition for setting the power generation / procurement cost). As a search condition, it is possible to specify whether to minimize the total cost of power generation or to maximize the balance of sales and supply. In addition, it is possible to specify to reduce the cost of a specific demand category (as another embodiment, a checkbook may be provided to specify to suppress cost fluctuation). Also, as search conditions, specify the cost characteristics of the generator (fuel cost per hour), estimated demand, estimated market price, and price agreement (unit price) (for example, use the information part 3704 in FIG. 41). Read from the database (input / output section of "condition setting" on the left side of Fig. 37).
(Fig. 39: Information part 3702) The numerical values (demand, market price, fuel cost) related to the read search conditions and the future and past re-energy amount stored in the database are displayed (Fig. 37, upper center, "medium-term assumed value"). ").
(Fig. 40: Information part 3703) By applying the "Execute" button in Fig. 38, the power supply configuration of the searched results and its supply (sales) are displayed on the horizontal axis in time (quarterly or one year). (Display), the upper half of the vertical axis is the procurement amount (the ratio of power supply and power procured from the market is displayed in a bar graph for each delivery time), and the lower half is the supply amount at each delivery time (to the customer of the company). (Sales and volume of sales to the market) are displayed in a bar graph (display section of "power supply configuration" in the lower center of FIG. 37).
(Fig. 42: Information part 3705) The sales revenue (“charge revenue”), cost (“power generation procurement cost”), and balance (“profit”) for each demand category in the search results are output. (Lower right of FIG. 37, "Balance evaluation by group" display section).

When the result save button of FIG. 38 is applied, each search result is saved in the database and posted on the screen 4300 (FIG. 43) of the simulation result of power supply configuration formulation. The screen 4300 shown in FIG. 43 displays, for example, information portions 4301 to 4303 (FIGS. 44 to 46) showing simulation results 1 to 3.

The processor unit of the management device displays the screen 4700 exemplified in FIG. 47 regarding the execution of STEP4. Specifically, FIG. 47 shows the overall configuration of the weekly plan formulation screen 4700. The information portions 4701 to 4705 shown in FIGS. 48 to 52 are displayed on the screen 4700, respectively. Specifically, it is as follows.
(Fig. 48: Information part 4701) Searches for charge unit price (charge menu) and power supply configuration, accepts input selected by the user (processed on a screen not shown), and under this condition, power for one week. Plan a transaction. In the selection of the power supply configuration, it is input which search condition is desirable for the user (executed in FIGS. 37 and 43). The specified search condition is posted on the weekly plan formulation screen as the default value of the "planning purpose setting" check box (Fig. 47, right center).
(Fig. 48: Information part 4701) The generator characteristics, the forecast value of demand (recreated at any time based on the weekly weather forecast and stored in the database), and the forecast value of the market price used in the weekly plan are read and specified. (In addition, the predicted value of the amount of renewable energy generated is updated and stored at any time according to the update of the weather forecast, and is read for the weekly system formulation). (Left side of FIG. 47).
(Fig. 49: Information part 4702) The numerical values (demand, market price, fuel cost) related to the read search conditions and the future and past re-energy amount stored in the database are displayed (Fig. 47, upper center "weekly forecast"). value").
(Fig. 50: Information part 4703) By applying the "Execute" button in Fig. 48, the results of the searched weekly power supply configuration and its supply (sales) are shown on the horizontal axis by time (quarterly or one year period). (Display), the upper half of the vertical axis is the procurement amount (the ratio of power supply and power procured from the market is displayed in a bar graph for each delivery time), and the lower half is the supply amount at each delivery time (to the customer of the company). (Sales and the amount of sales to the market) are displayed in a bar graph (display part of "weekly plan" in the lower center of Fig. 47).
(Fig. 52: Information part 4705) The sales revenue (“charge revenue”), cost (“power generation procurement cost”), and balance (“profit”) for each demand category in the search results are output. (Lower right of FIG. 47, "Balance evaluation by group" display section).

When the result save button of FIG. 48 is applied, each search result is saved in the database and posted on the screen 5300 (FIG. 53) of the simulation result of power supply configuration formulation. The screen 5300 shown in FIG. 53 displays, for example, information portions 5301 to 5303 (FIGS. 54 to 56) showing simulation results 1 to 3.

The present invention is not limited to the above-described embodiment, and includes various modifications. Further, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Further, it is possible to add / delete / replace a part of the configuration of each embodiment with another configuration.

1601, 1701, 1801, 1901 ... Management device

Claims (8)

An estimation unit that estimates future quantities, which are the quantities of demand and / or supply, for each of one or more delivery periods.
For each of the one or more delivery periods, the estimated future amount for the delivery period, the source cost for the supply, the sales revenue from the supply, or the revenue from the supply, to the business partner for the delivery period. A management device characterized by having a first planning unit that determines the transaction volume of. The source cost for supply is the source cost for supply in the demand category,
The management device according to claim 1. Revenue from supply is revenue from supply in the demand category,
The management device according to claim 1 or 2, wherein the management device is characterized by the above. Sales revenue from supply is sales revenue from supply in the demand category,
The management device according to any one of claims 1 to 3. For each of the one or more delivery periods, the transaction volume determined for the delivery period determines the transaction volume in the planned transaction period among the plurality of transaction volumes distributed to each of the plurality of planned transaction periods. Second planning department,
The management device according to any one of claims 1 to 4, further comprising. The estimation unit repeatedly estimates an error in the future quantity for each of the one or more delivery periods based on the actual value for the delivery period.
For each of the one or more delivery periods, the plurality of planned transaction periods are a plurality of periods in which the transaction period, which is a period prior to the delivery period and can be traded, is subdivided.
For each of the one or more delivery periods, the second planning unit has the planned transaction period of the plurality of transaction volumes in which the transaction volume determined for the delivery period is distributed to the plurality of planned transaction periods. The trading volume in is corrected based on the estimated error related to the planned trading period.
The management device according to claim 5. A sales revenue calculation unit that calculates sales revenue by supplying demand by demand category using the unit price and power consumption for each demand category with the same demand attribute.
A category-specific supply cost calculation unit that calculates the supply cost, which is the cost required to supply electric power, by demand category based on the supply unit price and supply amount for each supply source.
A demand category balance calculation unit that calculates the balance between sales revenue and supply costs by demand category,
The balance by demand category is calculated by calculating the balance forecast spread, which is an index showing the magnitude of the variation in the balance predicted by simulation in each of multiple future scenarios regarding the power consumption in a predetermined period of the demand category. A claim characterized by having a forecast spread calculation unit, a balance forecast spread for each demand category, and a source search unit for searching a combination of sources satisfying a constraint condition based on the balance for each demand category. The management device according to any one of 1 to 6. The computer estimates the future quantity, which is the quantity of demand and / or supply, for each of one or more delivery periods.
For each of the one or more delivery periods, the computer determines the delivery period from the estimated future amount for the delivery period, the source cost of the supply, the sales revenue from the supply, or the revenue from the supply. Determine the volume of transactions with business partners,
A management method characterized by that.

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