JP7608782B2 - Calculation device, calculation method, program, power storage system, power generation system, and grid - Google Patents

Description

The present invention relates to a technology for optimizing the efficiency of grid energy usage.

The introduction of distributed power sources, such as photovoltaic (PV) systems, is being promoted in order to reduce dependence on fossil fuels and address environmental issues. PV systems convert the electricity generated by solar panels from direct current to alternating current using an inverter circuit in a power control device.

The following Patent Document 1 discloses a technique for controlling a second power conversion means in a power storage type photovoltaic power generation system so that the received power detected by the received power detection means does not fall below a predetermined power when both the generated power of a distributed power source and the power from the power storage means are output, thereby preventing the power from the power storage means from flowing back into the power grid.

Patent No. 4765162

A grid equipped with energy storage devices can absorb and make up for power surpluses and shortages by charging and discharging if the energy storage devices have sufficient surplus capacity. When surplus power is stored by charging, surplus capacity refers to the available capacity for charging. When a power shortage is made up for by discharging, surplus capacity refers to the available capacity for discharging.

When performing calculations to optimize the efficiency of grid energy utilization, if the charge state of the energy storage device is determined solely based on the power supply and demand forecast for the current section, there are cases where the energy storage device is unable to secure sufficient spare capacity at the start of the next section to absorb any power surplus or shortage that occurs in the next section and beyond.

A calculation device that optimizes the energy utilization efficiency of a grid that is connected to an electric power system and equipped with a power storage device determines the range of the final state of charge of the power storage device for a prediction target section based on a power supply and demand forecast for the next section and thereafter, and evaluates whether the final state of charge of the prediction target section matches the range in an optimization calculation of the energy utilization efficiency of the prediction target section.

The above aspect can be applied to a calculation method for optimizing the energy utilization efficiency of a grid that is connected to a power system and equipped with a power storage device. It can also be applied to a program that performs optimization calculations.

At the start of the next section, the power storage device can be provided with surplus capacity to absorb any power surplus or shortage that may occur in the next section and beyond.

Microgrid Block Diagram Microgrid Block Diagram Graph showing correlation characteristics between solar radiation and generated power A graph showing the trends in predicted power generation and power consumption A simplified block diagram of a microgrid Graph showing the progress of the battery charge state Graph showing the progress of the battery charge state A diagram showing the number of candidates for receiving power A diagram showing the number of candidates for receiving power Diagram showing an example of dividing the forecast period A graph showing the electricity supply and demand for each section Calculation process flow chart FIG. 11 is an enlarged view of a part of FIG. Microgrid Block Diagram

A calculation device that optimizes the energy utilization efficiency of a grid that is connected to an electric power system and equipped with a power storage device determines the range of the final state of charge of the power storage device for a prediction target section based on a power supply and demand forecast for the next section and thereafter, and evaluates whether the final state of charge of the prediction target section matches the range in an optimization calculation of the energy utilization efficiency of the prediction target section.

In this configuration, the range of the final charge state of a section is determined based on a forecast of power supply and demand for the next section and beyond. Since the final charge state of a section is the starting charge state of the next section, by making the final charge state of the section match the determined range, it is possible to ensure that at the start of the next section, the storage device has a surplus capacity to absorb any power surplus or shortage that occurs in the next section and beyond.

Based on the power supply and demand forecast for the next section and onward, the amount of surplus power in a first period in which the supply of power exceeds the demand for the next section and onward may be calculated, and the upper limit value of the final state of charge for the prediction section may be determined to be a value obtained by subtracting a numerical value corresponding to the amount of surplus power from the upper limit of the usage range of the storage device. With this configuration, at the start of the next section, the storage device can be secured with a surplus capacity (free capacity) for charging the surplus power from the grid. This makes it possible to reduce energy loss.

A minimum amount of surplus energy for the first period may be calculated based on the power supply and demand forecast for the next section and thereafter, and an upper limit value of the final state of charge for the prediction section may be determined to be a value obtained by subtracting a numerical value corresponding to the minimum amount of surplus energy from an upper limit of a usage range of the power storage device. With this configuration, it is possible to ensure in the power storage device a surplus capacity (available capacity) for charging at least the minimum amount of surplus energy at the start of the next section.

The amount of power shortage caused by the supply of power falling short of the demand may be calculated for a second period from the start of the next period to the first period, and the lower limit of the final state of charge for the prediction period may be determined to be a value obtained by adding a numerical value corresponding to the amount of power shortage to the lower limit of the usage range of the storage device. With this configuration, it is possible to ensure in the storage device a surplus capacity for discharging the grid power shortage at the start of the next period. This allows for efficient use of energy.

The maximum amount of energy shortage in the second period may be calculated based on the power supply and demand forecast for the next section and thereafter, and the lower limit of the final state of charge in the prediction section may be determined to be a value obtained by adding a numerical value corresponding to the maximum amount of energy shortage to a lower limit of a usage range of the storage device. With this configuration, it is possible to ensure in the storage device a spare capacity for discharging the maximum amount of energy shortage at the start of the next section.

<Embodiment 1>
1. Description of the Microgrid S1 The microgrid S is a small-scale power system connected to the power system 1, and includes at least a distributed power source, a power storage device, and a load. The power system 1 may be that of a power company, or may be an independent power system consisting of the isolated operation output of a large power conditioner.

Figure 1 is a block diagram of the microgrid S1. The microgrid S1 is composed of a photovoltaic power generation panel 10, which is a distributed power source, a storage battery 15, which is a power storage device, a power conditioner 20, which is a power control device, and a load L.

The power conditioner 20 includes a first converter circuit 21, a second converter circuit 23, a DC link unit 25, a bidirectional inverter circuit 31, a relay 37, a control device 50, a DC voltage detection unit 27, an output current detection unit 33, and an output voltage detection unit 35.

The solar power generation panel 10 is connected to the first converter circuit 21. The first converter circuit 21 is a DC/DC converter that boosts and outputs the output voltage (direct current) of the solar power generation panel 10. The first converter circuit 21 may be a chopper.

The second converter circuit 23 is connected to the storage battery 15. The storage battery 15 is, for example, a secondary battery. The second converter circuit 23 is a bidirectional DC/DC converter that discharges and charges the storage battery 15. The second converter circuit 23 may be a bidirectional chopper.

The solar panel 10 and the storage battery 15 are connected in parallel to the DC link section 25 via the first converter circuit 21 and the second converter circuit 23.

The DC link section 25 is located between the connection point 24 of the converter circuit and the bidirectional inverter circuit 31. The DC link section 25 is provided with an electrolytic capacitor C1. The electrolytic capacitor C1 is provided to stabilize the voltage Vdc of the DC link section 25.

The DC voltage detection unit 27 detects the voltage Vdc of the DC link unit 25. The voltage Vdc of the DC link unit 25 detected by the DC voltage detection unit 27 is input to the control device 50.

The bidirectional inverter circuit 31 is a bidirectional conversion circuit that selectively performs reverse conversion (inverter) that converts DC to AC, and forward conversion (converter) that converts AC to DC. The bidirectional inverter circuit 31 is connected to the DC link unit 25, and during reverse conversion operation, it converts the DC power input from the DC link unit 25 into AC power and outputs it. In detail, the bidirectional inverter circuit 31 receives power equivalent to the voltage increase from the reference value in the DC link unit 25 due to power generation by the solar power generation panel 10. Therefore, the power equivalent to the voltage increase from the reference value is converted from DC to AC and output from the bidirectional inverter circuit 31.

The storage battery 15 can store surplus electricity from the solar power generation panel 10 via the second converter circuit 23. When the power generated by the solar power generation panel 10 is insufficient, the storage battery 15 can discharge the power via the second converter circuit 23 to make up for the shortage of generated power.

The bidirectional inverter circuit 31 is connected to the power system 1, which uses the system power supply 2 as an AC power source, via a relay 37.

Relay 37 is installed for interconnection with power grid 1. By closing relay 37, microgrid S1 can be interconnected with power grid 1.

The output current detection unit 33 detects the output current Iinv of the bidirectional inverter circuit 31. The output voltage detection unit 35 is located on the output side of the bidirectional inverter circuit 31 and detects the output voltage Vinv of the bidirectional inverter circuit 31.

The output current Iinv of the bidirectional inverter circuit 31 detected by the output current detection unit 33 and the output voltage Vinv of the bidirectional inverter circuit 31 detected by the output voltage detection unit 35 are input to the control device 50. The control device 50 calculates the output power (active power) Pinv of the bidirectional inverter circuit 31 based on the output current Iinv and output voltage Vinv of the bidirectional inverter circuit 31. The output power Pinv is "positive" during inverse conversion and "negative" during forward conversion.

A load L, which is a demand facility, is connected to the power line (main line) 5 that connects the bidirectional inverter circuit 31 and the power system 1 via a branch line 4. Power can be supplied to the load L from both the power conditioner 20 and the power system 1.

The power receiving point 3 is the point where power is supplied by the power grid 1, and as shown in Figure 1, it is the boundary between the power grid 1 and the premises (microgrid S1).

The power system 1 is provided with an external measuring instrument 40 such as an external transducer as a meter for detecting power at the power receiving point 3.

The external measuring instrument 40 has a receiving current detection unit 41 and a system voltage detection unit 43. The external measuring instrument 40 is installed corresponding to the receiving point 3, and the receiving current detection unit 41 detects the receiving current at the receiving point 3. The system voltage detection unit 43 detects the system voltage of the power system 1.

The external measuring instrument 40 calculates the received power (active power) P _RCV based on the received current and the system voltage. The received power P _RCV detected by the external measuring instrument 40 is input to the control device 50. The received power P _RCV can be used to determine the state of power flow (hereinafter simply referred to as power flow). The external measuring instrument 40 is a measuring instrument that measures the received power P _RCV at the power receiving point 3.

With regard to the received power P _RCV , forward flow (Figure 1: the flow of electricity from power grid 1 to microgrid S1) is considered to be "positive" and reverse flow (Figure 2: the flow of electricity from microgrid S1 to power grid 1) is considered to be "negative."

The control device 50 has a CPU 51 and a memory 53. The memory 53 stores a program for predicting the supply and demand of electricity in the microgrid S1 and a program for performing optimization calculations to optimize the energy utilization efficiency of the microgrid S1. The control device 50 is an example of the "computation device" of the present invention.

The control device 50 can control the switching between forward conversion operation and reverse conversion operation by giving commands to the bidirectional inverter circuit 31. It can control the output of the bidirectional inverter circuit 31, i.e., the output power Pinv. The output power Pinv can be controlled by adjusting the output current Iinv.

The control device 50 can control the connection/disconnection of the solar power generation panel 10 to the DC link unit 25 by turning the first converter circuit 21 on and off. The control device 50 can control the connection/disconnection of the storage battery 15 to the DC link unit 25 by turning the second converter circuit 23 on and off. The control device 50 can control switching between charging and discharging the storage battery 15 via the second converter circuit 23. The control device 50 can control the charging current and discharging current of the storage battery 15 via the second converter circuit 23.

2. Power Generation Prediction and Load Prediction of the Microgrid S1 The control device 50 predicts the power generation [kW] of the photovoltaic power generation panel 10 and the power consumption [kW] of the load L.

As shown in Fig. 3, the power generation power _PPV of the photovoltaic power generation panel 10 is correlated with the amount of solar radiation X. The predicted value of the power generation power _PPV can be obtained from a prediction data providing center 70 via the network NW. The prediction data providing center 70 may be a providing center of the supplier of the power conditioner 20 or a providing center of the power generation company. The power generation power _PPV of the photovoltaic power generation panel 10 is converted to AC by the bidirectional inverter circuit 31. The conversion efficiency η is the conversion efficiency of the inverter circuit 31 when converting direct current DC to alternating current AC.

The power consumption P _LOAD of the load L can be predicted from past data. For example, the power consumption for the next day can be predicted by statistically processing the data of the power consumption P _LOAD for several days.

The power consumption P _LOAD of the load L can be calculated from the received power P _RCV at the receiving point 3 and the output power Pinv of the bidirectional inverter circuit 31. In the case of forward power flow (P _RCV > 0), the power consumption P _LOAD of the load L is the sum of the output power Pinv and the received power P _RCV . In the case of reverse power flow (P _RCV < 0), the power consumption P _LOAD of the load L is the difference between the output power Pinv and the received power P _RCV .

P _LOAD = Pinv + P _RCV (A)

Figure 4 is a graph showing the results of power generation prediction and load prediction for microgrid S1. The dashed line indicates the predicted value of power generation of microgrid S1, and the solid line indicates the predicted value of power consumption of microgrid S1. In this example, the prediction period T is set to one day, and power generation prediction and load prediction are performed every hour, and the predicted value is a step-like waveform whose value changes every hour. Power generation prediction and load prediction for microgrid S1 may be performed by the control device 50, or predicted data may be obtained from a separate device.

3. Optimization Calculation for Optimizing Energy Efficiency of the Microgrid Figure 5 is a simplified block diagram of the microgrid S1.
The control device 50 performs an optimization calculation to optimize the energy utilization efficiency of the microgrid S1. The optimization calculation is to obtain an optimal value of the target value of the received power P _RCV (hereinafter, the target value P _{RCVref of the received power) that minimizes the objective function F of the formula 1, based on the power generation prediction and the load prediction (FIG. 4} ).

Equation 1 is an objective function for evaluating the energy utilization efficiency of the microgrid S1.

The first and second terms of the objective function F are terms that evaluate the usage restriction period of the storage battery 15. The third and fourth terms are terms that evaluate the electricity rate of the microgrid S1.

There are two usage limit periods: a charging limit period _TMAX and a discharging limit period _TMIN . The charging limit period _TMAX is a period during which charging is limited, for example, when the SOC of the storage battery 15 is at the upper limit of the usage range (when fully charged). The discharging limit period _TMIN is a period during which discharging is limited, for example, when the SOC of the storage battery 15 is at the lower limit of the usage range.

In this example, _k1 > _k2 > _k3 > _k4 , and in evaluating the energy utilization efficiency of the microgrid S1, priority is given to the evaluation of the usage restriction period of the storage battery 15. It is also possible that _k1 = _k2 and k3=k4.

When performing a calculation to optimize the receiving power target value P _RCVref , there are two constraints: an upper and lower limit of the receiving power target value P _RCVref (Formula 2) and an upper and lower limit of the output power [kW] of the storage battery 15 (Formula 3).

The SOC (State Of Charge) is a ratio of the charge amount to the rated capacity of the storage battery 15. The SOC is an example of the "state of charge" of the storage battery 15. In order to calculate the objective function F, it is necessary to estimate the SOC of the storage battery 15. Below, a method of simulating the SOC of the storage battery 15 and the estimated value of the received power P _RCVt will be described.

A method for calculating the charge limited period T _MAX and the discharge limited period T _MIN at the time slice t will be described.
<STEP 1>
From Equation 4 and Equation 5, a provisional output power prediction value P _BATtmpt of the storage battery 15 at the time slice t is calculated.

<STEP 2>
A provisional predicted state of charge value SOC _{tmp t} of the storage battery 15 at the time slice t is calculated using Equations 6 to 9.
(a) When t = 0

(b) When t≠0

<STEP 3>
The presence or absence of a deviation from or agreement with the upper and lower limits at time slice t is determined, and a predicted state of charge value SOC _t of the storage battery 15, the output power P _BATt of the storage battery, the charge limit period T _MAX , and the discharge limit period T _MIN are determined.
(a) When SOC _tmpt ≧ SOCMAX

(b) If SOC _tmpt ≦ SOCMIN

(c) If SOCMIN < SOC _tmpt < SOCMAX

Next, the initial value (when t=0) of the predicted charge amount Wh _BATt of the storage battery 15 can be calculated from Equations 16 and 17.

Next, for each time slice (t≠0), a predicted value Wh _BATt of the charge amount of the storage battery 15 can be calculated using Equation 18. A predicted value SOC _t of the SOC of the storage battery 15 can be calculated using Equation 19.

The received power prediction value P _RCV at the time slice t can be calculated by Equations 20 and 21.

The peak received power prediction value P _PEAK in the prediction target period T can be calculated by Equation 22.

From Equations 4 to 19, if the received power target value P _RCVreft is determined for the predicted generated power value P _PVt ×η and the predicted power consumption value P _LOADt of the load L, the SOC _t of the storage battery 15 can be estimated.

The control device 50 estimates the SOC _t of the storage battery 15 at each time slice t using the received power target value P _RCVreft as a variable, and calculates the four terms of the objective function F from the result.

Such calculations are performed for the prediction target period T (if the prediction target period T is one day and the calculation cycle is one hour, 24 cycles are performed). Then, by comparing the value of the objective function F for the combination patterns of the receiving power target value P _RCVreft , it is possible to determine a combination of receiving power target values that minimizes the objective function F, that is, the receiving power target value P _RCVreft for each time slice t for the prediction target period T.

Figures 6 and 7 are graphs with the horizontal axis representing time [h], the left vertical axis representing power [kW], and the right vertical axis representing SOC [%]. Y1 (bold line) represents the trend in received power [kW], and Y2 represents the trend in generated power [kW]. Y3 represents the trend in power consumption [kW] of the load, Y4 represents the trend in output power [kW] of the storage battery, and Y5 (dashed line) represents the trend in SOC [%] of storage battery 15.

6 shows a case where the received power target value P _RCVref is determined empirically, and FIG. 7 shows a case where the received power target value P _RCVref is determined based on the objective function F. In FIG.

When the receiving power target value P _RCVref is determined empirically ( FIG. 6 ), the SOC of the storage battery 15 is maintained at approximately 100% during the time period from 16:00 to 18:00. Therefore, it is necessary to limit the acceptance of charge by the storage battery 15 during the time period from 16:00 to 18:00.

When the receiving power target value P _RCVref is determined based on the objective function F ( FIG. 7 ), the SOC of the storage battery 15 varies with a margin relative to the SOC upper limit line Lim1 (SOCMAX=100[%]) and the SOC lower limit line Lim2 (SOCMIN=10[%]), and both charging and discharging are always possible. In other words, compared to the case where the receiving power target value P _RCVref is determined empirically, the SOC is kept low during the time period from 16:00 to 18:00 (part A), and there is an improvement in that charging during this time period is not restricted.

4. Power Control of Microgrid The control device 50 performs power control of the microgrid S1 so that the received power P _RCV of the microgrid S1 follows the received power target value P _RCVref calculated using the objective function F.

For example, when the power receiving point 3 has a forward power flow and the inverter circuit 31 is performing an inverse conversion operation, if the measured value of the received power P _RCV is lower than the received power target value P _RCVref , the difference between the measured value of the received power P _RCV and the received power target value P _RCVref is reduced by reducing the output power of the storage battery 15. If the measured value of the received power P _RCV is higher than the received power target value P _RCVref , the output power of the storage battery 15 is increased to reduce the difference between the measured value of the received power P _RCV and the received power target value P _RCVref .

As described above, by adjusting the output of the storage battery 15 in accordance with the difference between the measured value and the target value of the received power P _RCV , the received power P _RCV of the microgrid S1 can be made to follow the received power target value P _RCVref calculated using the objective function F.

5. Method for reducing calculation load To determine the optimal value of the receiving power target value P _RCVref , it is necessary to estimate the SOC of the storage battery 15 and the like for the number of candidates for the receiving power target value P _RCVref for each time slice t of the prediction target period T, and calculate each term of the objective function F. For example, when the prediction target period T is one day and the number of time slices is 24, if the receiving power target value P _RCVref is changed in increments of 1 kW within the range of 0 to 10 kW, the total number of candidates for the receiving power target value P _RCVref is 11 ²⁴ = 9.85 × 10 ²⁴ , and the calculation load increases in proportion to the total number of candidates.

The computational load of the optimization calculation can be reduced by using the following two methods.
(A) Constraints on the range of change in the target value of received power (B) Division of the prediction target period T

Let us explain (A).
It is desirable for the change in the received power P _RCV to be as small as possible because the change in the received power P RCV may affect the power quality of the power system 1. Therefore, as shown in Equation 23, a constraint is placed on the change in the received power target value P _RCVref per time slice t.

8A and 8B are diagrams showing combinations of candidates for the receiving power target value P _RCVreft . Fig. 8A shows a case where no constraint is placed on the range of change in the receiving power target value P _RCVref , and Fig. 8B shows a case where the maximum range of change in the receiving power target value P _RCVref is set to ±2 [kW].

The number of candidates for the power receiving power target value P _RCVref per time slice t is "11" when no constraint is placed on the range of change in the power receiving power target value P _RCVref (as in FIG. 8A ). On the other hand, when the maximum value of the range of change in the power receiving power target value P _RCVref is set to ±2 [kW] (as in FIG. 8B ), the number is "5."

By restricting the range of change of the receiving power target value P _RCVref in this way, the number of candidates for the receiving power target value P _RCVref per time slice t can be reduced, and the calculation load can be significantly reduced. The impact on the power grid 1 can be reduced, and the quality of electricity can be maintained.

Let us explain (B).
B1. Division of intervals The prediction target period T is divided into multiple intervals ΔT. Then, each divided interval ΔT is treated as one prediction target period, and the control device 50 performs optimization calculations to optimize the energy efficiency of the microgrid S1. In other words, the optimal value of the received power target value P _RCVref for each time slice t is determined using the objective function F.

For example, when the prediction period T is one day, it is divided into four intervals ΔT, _ΔT1 to _ΔT4 , as shown in Fig. 9. Then, with each interval ΔT being treated as one prediction period, the control device 50 uses the objective function F to find the optimal value of the receiving power target value P _RCVref .

In this case, the received power target value P _RCVref for the entire prediction period T is obtained by connecting, in chronological order, the received power target values P _RCVref for each time slice t of each interval ΔT determined as the optimal value.

By dividing the prediction target period T, the receiving power target value P _RCVref for the entire prediction target period T is calculated in multiple times. Therefore, the number of combinations of candidates for the receiving power target value P _RCVref per time is reduced, and the calculation load can be significantly reduced.

The number of divisions N of the prediction target period T may be any number other than four, such as three. The number of time slices in each section ΔT may be the same or different. It is preferable that each section ΔT is longer than the period of the power generation prediction and the load prediction. In the example of FIG. 9, ΔT=6 hours, and the period of the power generation prediction and the load prediction=1 hour.

B2. Ensuring reserve capacity of storage battery at the start of the next section Fig. 10 is a graph showing a power supply and demand forecast for a forecast target period T. Power supply and demand forecast can be made from the forecast value of power generation by the photovoltaic power generation panel 10, the forecast value of power consumption by the load L, and the target value of power received from the power grid 1. Y1 in Fig. 10 indicates the target value of power reception (minimum), Y2 indicates the forecast value of power generation, and Y3 indicates the forecast value of power consumption.

When the prediction target period T is divided and optimization calculations are performed for each interval ΔT, if the calculations are performed taking into account only the supply and demand forecast within that interval _ΔTn , there are cases where the battery 15 is unable to secure the surplus capacity to absorb the power surplus or shortage in the next interval ΔTn ₊₁ at the start of the next interval ΔTn ₊₁ . Therefore, there is a problem as to how to secure the surplus capacity of the battery 15 at the end of the interval _ΔTn in anticipation of the power supply and demand forecast for the next interval ΔTn ₊₁ . The surplus capacity is the available capacity for charging when the surplus power is charged and stored. It is the capacity that can be discharged when the power shortage is compensated for by discharging.

In order to solve the above problem, the control device 50 of the power conditioner 20 calculates the range of the final SOC of the storage battery 15 in the section ΔT _n based on the prediction of power supply and demand in the next section ΔT _n+1 .

Since the final SOC of the section ΔT _n = the start SOC of the next section ΔT _n+1 , by matching the final SOC of the storage battery 15 for the section ΔT _n with the calculated range, it is possible to ensure a margin of power for the storage battery 15 at the start of section ΔT _n+1 . In other words, it becomes possible to operate the storage battery 15 with a margin relative to the upper limit SOCMAX and the lower limit SOCMIN of the usage range, and any excess or shortage of power can be absorbed and compensated for by charging and discharging. Fig. 11 is a flowchart of the calculation process for calculating the SOC range.

(S10) Calculation of Upper Limit Value SOC _UPPER of Final SOC The control device 50 calculates the upper limit value SOC _UPPER of the final SOC of the storage battery 15 in the section ΔT _n from the surplus energy WC in the next section ΔT _n+1 .

The surplus energy WC is a value obtained by accumulating the surplus power in the first period _(A1 in FIG. 10 ) during which the difference between the predicted power generation value _PPVt of the photovoltaic power generation panel 10, which is a distributed power source, and the predicted power consumption value _PLOADt of the load L is continuously positive in the next section ΔTn+1.

The surplus power is the generated power _PPV plus the difference between the consumed power _PLOAD and the received power _PRCV . The surplus power depends on the magnitude of the received power _PRCV supplied from the power grid 1, and is smaller as the received power _PRCV is smaller.

If the storage battery 15 does not have a capacity to charge at least the minimum surplus energy WC, energy loss will occur. Therefore, in this example, the minimum surplus energy WC for the next interval ΔT _n+1 is calculated based on the predicted power generation value P _PVt , the predicted power consumption value P _LOADt , and the minimum receiving power target value P _{RCVrefmin t} .

The minimum receiving power target value P _{RCVrefmin t} for the next interval ΔT _n+1 can be obtained by subtracting the maximum change range set in (A) for each time slice from the final receiving power predicted value P _{RCV tend} for the interval ΔT _n .

The surplus energy WC may be calculated across a plurality of intervals, such as ΔT _n+1 and ΔT _n+2 (for example, for 6 to 8 hours).

In order to ensure free capacity for charging the surplus energy WC in the first period A1, the upper limit SOC UPPER of the final SOC of the storage battery 15 in the section _ΔTn is calculated by subtracting the SOC equivalent to the surplus energy WC from the _upper limit SOCMAX of the usage range of the storage battery 15. The surplus energy WC may be a minimum value or any other value.

12, "Lim1" indicates the upper limit SOCMAX of the usage range, and "Lim3" indicates the upper limit SOC _UPPER of the final SOC. "Y5" is the SOC of the storage battery 15. The upper limit SOCMAX of the usage range is the limit value on the charging side of the SOC (the value above which charging is not possible).

In the microgrid S1, depending on the balance between power supply and demand, power may be insufficient as well as in surplus. If the final SOC of the storage battery 15 is near the lower limit SOCMIN of the usage range, the storage battery 15 may not be able to discharge in the next section from the start of the section to the time cross section t _cross where power is oversupplied. Therefore, the control device 50 calculates the lower limit SOC _LOWER of the final SOC so as to leave a surplus capacity for discharge.

(S20) Calculation of Lower Limit Value SOC _LOWER of Final SOC The lower limit value SOC _LOWER of the final SOC of the storage battery 15 in the section ΔT _n is calculated by calculating the amount of power shortage WD for the second period A2 from the start of the next section ΔT _n+1 to the first period A2 (until the time cross section t _cross where oversupply occurs). The amount of power shortage WD is a value obtained by accumulating the power shortage for the second period A2.

The power shortage is the power consumption _PLOAD minus the generated power _PPV and the received power _PRCV . The power shortage depends on the magnitude of the received power _PRCV supplied from the power grid, and is larger as the received power _PRCV is smaller.

If the storage battery 15 has a margin of discharge for the maximum amount of power shortage WD, the minimum receiving power can be maintained, and the energy utilization efficiency is high. Therefore, in this example, the maximum power shortage WD is calculated for the second period A2 of the next interval ΔT _n+1 based on the predicted power generation value P _PVt , the predicted power consumption value P _LOADt of the load L, and the minimum receiving power target value P _RCVrefmint .

If the discharge amount of the storage battery 15 exceeds the power shortage WD, a reverse power flow will occur, and since this will result in a reverse power flow from the storage battery 15 to the grid, it is not acceptable for the power shortage WD to be exceeded.

The lower limit SOC _LOWER of the final SOC in the section ΔT _n is obtained by adding the SOC equivalent to the energy deficit WD to the lower limit SOCMIN of the usage range of the storage battery 15 so as to ensure a capacity capable of discharging the energy deficit WD. The energy deficit WD may be a maximum value or may be other than the maximum value. In FIG. 12, "Lim2" indicates the lower limit SOCMIN of the usage range, and "Lim4" indicates the lower limit SOC _LOWER of the final SOC. Y5 is the SOC of the storage battery 15. The lower limit SOCMIN of the usage range is the limit value on the discharge side of the SOC (the value beyond which the battery cannot be discharged).

(S30) Penalty for Deviation From the above, it is possible to determine range Z (see FIG. 12) with SOC _LOWER as the lower limit and SOC _UPPER as the upper limit for the final SOC of the storage battery 15 in section _ΔTn .

If the final SOC of the storage battery 15 deviates from the range Z, that is, does not match, a penalty is calculated. If it does not deviate from the range Z, that is, matches, no penalty is calculated.

Equation 27 is an objective function E in which penalty evaluation terms are added to four items in the objective function F. The optimal value of the receiving power target value P _RCVref is calculated using the objective function E with the interval ΔT as one prediction target period.

When performing optimization calculations for each interval ΔT _n , the final SOC of the storage battery 15 in the interval ΔT _n is set as the initial SOC _INI of the storage battery 15 in the next divided interval ΔT _n+1 , and steps S10 to S30 are repeated the number of times equal to the number of intervals. Then, when all intervals are completed, an optimal solution for the received power target value P _RCVref that optimizes the energy utilization efficiency of the microgrid S1 for the prediction target period T can be obtained.

By adding a penalty evaluation term to the objective function E, a solution with no or small penalty can be obtained as the optimal solution, so that it is possible to prevent the final SOC of the section ΔT _n from not matching the range Z.

The magnitude relationship between the coefficients _k5 and _k6 that determine the penalty weight and the other coefficients may be _k1 > _k2 > _k3 > _k4 >k5>k6, or _k5 > _{k6 >k1>k2 > k3 > k4} . The magnitude relationship between the two coefficients may be _k5 > _k6 or _{k5 <k6 .}

6. Effects The storage battery 15 charges the microgrid S1 with surplus power and discharges it when there is a power shortage, thereby compensating for the power shortage. If the use of the storage battery 15 is restricted, the surplus power cannot be stored, resulting in a loss of energy, and the energy utilization efficiency of the microgrid S1 decreases.

In this configuration, the usage restriction period of the storage battery 15 can be minimized by finding an optimal value of the receiving power target value P _RCVreft based on the objective function E and the objective function F. Therefore, from the viewpoint of the utilization efficiency of the storage battery 15, the utilization efficiency of the energy of the microgrid S1 can be optimized.

In this configuration, the prediction target period T is divided into multiple intervals ΔT, and optimization calculations are performed to optimize the energy usage efficiency of the microgrid S1. This reduces the calculation load and shortens the time required to calculate the optimal solution.

In this configuration, the range Z of the final SOC of the section ΔT _n is determined based on a prediction of power supply and demand for the next section ΔT n _{+ 1} and thereafter. Since the final SOC of the section ΔT is the start SOC of the next section ΔT n+1, by making the final SOC of the section ΔT _n coincide with the range Z, it is possible to ensure in the storage battery 15 at the start of the next section ΔT _n+1 that the surplus or shortage of power for the next section ΔT _n+1 and thereafter.

In this configuration, the amount of surplus energy WC in the first period A1, in which the supply of power exceeds the demand, is calculated based on a power supply and demand forecast for the next period ΔT _n+1 and thereafter. Then, the upper limit value SOC _UPPER of the final SOC of the storage battery 15 in the period ΔT _n is determined to be a value obtained by subtracting the SOC equivalent to the amount of surplus energy WC from the upper limit SOCMAX of the usage range. In this configuration, at the start of the next period ΔT _n+1 , the storage battery 15 can be secured with a surplus capacity for charging the surplus energy of the microgrid S1. This makes it possible to suppress energy loss.

In this configuration, the energy deficit WD is calculated for the second period A2 from the start of the next period ΔT _n+1 to the first period A1. Then, the lower limit SOC _LOWER of the final SOC of the storage battery 15 for that period ΔT _n is determined to be a value obtained by adding the SOC equivalent to the energy deficit WD to the lower limit SOCMIN of the usage range. In this configuration, at the start of the next period ΔT _n+1 , it is possible to ensure in the storage battery 15 a surplus capacity for discharging the power deficit of the microgrid S1. This allows for efficient use of energy.

<Other embodiments>
The present invention is not limited to the embodiments described above and illustrated in the drawings, and the following embodiments, for example, are also included within the technical scope of the present invention.

(1) In the first embodiment, a grid having a linear power line (main line) 5 is shown as an example of the microgrid S1, but a grid having a circular power line (main line) may also be used. The microgrid S2 shown in FIG. 13 has a circular power line 100. A solar power generation panel 110 and a wind power generator 120 are connected to the power line 100 via power converters 115 and 125. A load 130 and a storage battery 140 are connected to the power line 100. The power line 100 of the microgrid S2 is connected to the power system 1 via an interconnection line 105.

The microgrid S2 includes a control device 150. The control device 150 divides the prediction target period T into a plurality of sections, performs optimization calculations to optimize the energy utilization efficiency of the microgrid S2, and calculates an optimal solution for the receiving power target value P _RCVref . The control device 150 performs power control of the microgrid S2 so that the receiving power at the receiving point 3 follows the calculated receiving power target value P _RCVref . Specifically, the control device 150 monitors the receiving power P _RCV at the receiving point 3 based on the output of a meter 160 provided at the receiving point 3. Then, when there is a difference with respect to the receiving power target value P _RCVref , the control device 150 reduces the difference by charging or discharging the storage battery 140 via the power converter 145. In this way, the receiving power P _RCV can be made to follow the calculated target value P _RCVref , and the energy utilization efficiency of the microgrid S2 can be optimized. The control device 150 is an example of a "computing device" of the present invention.

The distributed power source is a general term for small-scale power generation facilities that are distributed and installed adjacent to demand areas. The distributed power source may be, for example, a biomass power generation device in addition to the solar power generation panel 10 or the wind power generator 120. The distributed power source may be a power source that uses renewable energy or a power source that uses fossil fuels.

(2) In the first embodiment, a calculation was performed to optimize the energy utilization efficiency of the microgrid S1 using the target value of received power as a variable. A calculation may also be performed to optimize the energy utilization efficiency of the microgrid using the SOC of the storage battery 15 as a variable. This technology is not limited to microgrids (small-scale power systems) and can be applied to any grid (power system) that is linked to another power system and includes a storage device. In the first embodiment, the storage battery 15 is exemplified as the storage device, but the storage device may be a capacitor or the like.

(3) In the first embodiment, the objective function F is a function that is composed of four terms, the first term to the fourth term, and that multiplies and adds the four terms by the weighting coefficients k ₁ to k _4. In the first embodiment, the magnitude relationship of the weighting coefficients is k ₁ > k ₂ > k ₃ > k ₄ , but it may be k ₃ > k ₄ > k ₁ > k _2. By reversing the magnitude relationship of the weighting coefficients, it is possible to prioritize the evaluation of the electricity fee of the microgrid, and therefore it is possible to optimize the energy utilization efficiency of the microgrid from the viewpoint of the electricity fee. The objective function F may be only the first and second terms that evaluate the usage restriction period of the storage battery 15, or only the third and fourth terms that evaluate the electricity fee of the microgrid. The objective function F may be any other function as long as it optimizes the energy utilization efficiency of the microgrid. The same applies to the objective function E.

(4) In the first embodiment, the optimization calculation for optimizing the energy utilization efficiency of the microgrid is performed by the control device 51 of the power conditioner 20. The subject of the calculation is not limited to the power conditioner 20, and may be a calculation device provided separately from the power conditioner 20.

(5) In the first embodiment, a calculation example was given for optimizing the energy utilization efficiency of the microgrid using objective functions E and F, but the calculation may also be performed using, for example, AI.

(6) In the first embodiment, the upper limit SOC _UPPER and the lower limit SOC _LOWER of the final SOC in the section ΔT _n are calculated. For example, in the next section ΔT _n+1 , if there is no second period A2 in which power is insufficient before the first period A1, the upper limit SOC _UPPER of the final SOC may be calculated based on the surplus power WC in the first period A1, and the lower limit of the final SOC may be set to the lower limit SOCMIN of the usage range. Conversely, in the next section ΔT _n+1 , if there is only a period in which power is insufficient, the lower limit SOC _LOWER of the final SOC may be calculated based on the amount of power shortage WD, and the upper limit of the final SOC may be set to the upper limit SOCMAX of the usage range.

(7) In the first embodiment, the SOC [%] of the storage battery 15 is evaluated in the calculation for optimizing the energy utilization efficiency of the microgrid. Instead of the SOC [%], the remaining capacity [Ah] of the storage battery 15 may be evaluated. In other words, the range of the final remaining capacity of the prediction target section ΔT _n of the storage battery 15 may be determined based on a power supply and demand prediction for the next section and thereafter, and in the calculation for optimizing the energy utilization efficiency of the prediction target section ΔT _n , it may be evaluated whether or not the final remaining capacity of the section ΔT _n matches the determined range. The SOC and remaining capacity are examples of the "state of charge" of the storage battery.

(8) In the first embodiment, the prediction period T is divided into multiple intervals in order to reduce the load of the optimization calculation. This technology can be applied when performing optimization calculations for any prediction interval, regardless of whether the prediction period is divided or not.

1 Power system 2 System power source 3 Power receiving point 10 Photovoltaic power generation panel (an example of the "distributed power source" of the present invention)
15 Power storage device 20 Power conditioner (an example of the “computing device” of the present invention)
21 First converter circuit 23 Second converter circuit 31 Inverter circuit 40 External measuring instrument 50 Control device S1, S2 Microgrid

Claims (12)

A calculation device that optimizes energy utilization efficiency of a grid that is connected to a power system and has a power storage device,
A computing device that determines the range of the final state of charge of the storage device for a prediction target section based on a supply and demand forecast of electricity for the next section and thereafter, and evaluates whether the final state of charge of the prediction target section matches the range in an optimization calculation of energy utilization efficiency for the prediction target section. 2. The computing device of claim 1,
Calculating an amount of surplus power in a first period in which the supply of power exceeds the demand in the next section and thereafter based on a supply and demand forecast of power in the next section and thereafter;
A calculation device that determines an upper limit value of the final state of charge of the prediction section to be a value obtained by subtracting a numerical value corresponding to the amount of surplus power from an upper limit of a usage range of the power storage device. 3. A computing device as claimed in claim 2, comprising:
Calculating a minimum amount of surplus power in the first period based on a forecast of power supply and demand for the next section and thereafter;
A calculation device that determines an upper limit value of the final state of charge of the prediction section to be a value obtained by subtracting a numerical value corresponding to the minimum amount of surplus power from an upper limit of a usage range of the power storage device. A computing device according to claim 2 or claim 3,
Calculating an amount of power shortage resulting from the supply of power falling short of the demand for a second period from the start of the next section to the first period;
a calculation device that determines a lower limit of a final state of charge of the prediction section to be a value obtained by adding a numerical value corresponding to the amount of power shortage to a lower limit of a usage range of the power storage device. 5. A computing device according to claim 4, comprising:
Calculating a maximum energy shortage amount for the second period based on a power supply and demand forecast for the next section and thereafter;
a calculation device that determines a lower limit of the final state of charge of the prediction section to be a value obtained by adding a numerical value corresponding to the maximum amount of energy shortage to a lower limit of a usage range of the power storage device. A computing device according to any one of claims 1 to 5,
A computing device that optimizes energy utilization efficiency by calculating an optimal value of a target value of received power in a forecast target section of the grid based on a power demand forecast. A computing device according to any one of claims 6 , further comprising:
A computing device that adjusts an output of the power storage device in accordance with a difference between a measured value of received power of the grid and the target value of received power. A calculation method for optimizing energy utilization efficiency of a grid that is connected to a power system and has a power storage device, comprising:
A calculation method comprising: determining a range of the final state of charge of the storage device for a prediction target section based on a power supply and demand forecast for the next section and thereafter; and evaluating whether the final state of charge of the prediction target section matches the range in an optimization calculation of energy utilization efficiency for the prediction target section. A program for optimizing energy utilization efficiency of a grid that is connected to a power grid and has a power storage device,
A process of determining a range of a final state of charge of the power storage device in a prediction target section based on a supply and demand prediction of power in a next section and thereafter,
and evaluating whether or not a final state of charge of the prediction target section matches the range in an optimization calculation of energy utilization efficiency of the prediction target section. A power storage system connected to a power grid,
A computing device according to any one of claims 1 to 7;
A power storage system including a power storage device. A power generation system interconnected with an electric power grid,
A computing device according to any one of claims 1 to 7;
A power generation system comprising: A grid connected to a power system,
A computing device according to any one of claims 1 to 7;
A power storage device;
A grid including a distributed generation system.

Images