JP2009250454A - Operation program deciding system - Google Patents

Abstract

An operation plan determination system capable of quickly determining the optimum number of operating units and the amount of heat supplied for each heat source device is provided.
In an operation plan determination system 10A, characteristic coefficient data of each heat source device 15-19 and first heat demand data for each hour in a daily unit of a heat source equipment 11 are input to a controller 13. The controller 13 applies the first mathematical programming method to the characteristic coefficient data and the first demand heat quantity data, and the second demand heat quantity second per hour of the heat source equipment 11 enabling the optimum operation of the heat source devices 15 to 19. The second mathematical programming method is applied to the demand heat quantity second data calculating means for calculating the data, the characteristic coefficient data, the demand heat quantity first data, and the demand heat quantity second data, and the heat source devices 15 to 19 are arranged at predetermined time intervals. Operating condition calculating means for calculating the optimum operating number and supplied heat amount, and operating condition output means for outputting the calculated operating number and supplied heat amount of the heat source devices 15 to 19 every predetermined time.
[Selection] Figure 1

Description

  The present invention relates to an operation plan determination system that determines the optimum number of operating heat sources and the amount of supplied heat for each predetermined time in a daily unit of heat source equipment.

  Establish a simulation model of equipment such as refrigerators and pumps that make up the air conditioning equipment, and based on the simulation model, determine the optimal control target value that has a predetermined constraint condition and minimizes or maximizes the evaluation function, There is an air conditioning equipment control system that operates air conditioning equipment according to the optimum control target value (see Patent Document 1). The optimal control target value is calculated by an optimal calculation computer. The computer for optimum calculation includes a communication means for communicating with devices connected to a communication network, a database storing characteristic parameters of air conditioning equipment used for simulation of air conditioning equipment, simulation parameters such as resistance counts of pipes and ducts, and a database Air conditioning equipment simulator that simulates air conditioning equipment using various data of the above, optimization means that calculates the optimal control target value of air conditioning equipment using air conditioning equipment simulator, and piping based on measurement data of temperature sensor and humidity sensor And a parameter identification means for identifying the simulation parameter of the resistance coefficient of the duct.

The air conditioning equipment simulator calculates the temperature sensor and humidity sensor measurement values, cooling water temperature control target values, cooling water flow rate control target values, cold water temperature control target values, and air conditioner blowout temperature control target values. When input to the computer, the running cost, which is the overall evaluation function, is calculated using a database of air conditioner characteristic data and a simulation model. The optimization means calculates the control target value of the cooling water flow rate, the control target value of the chilled water temperature, and the control target value of the blowout temperature of the air conditioner that minimize the running cost, which is an evaluation function, using an air conditioning equipment simulator. In this air conditioning equipment control system, the air conditioning equipment is operated based on the calculated control target values.
JP 2004-293844 A

  In the air conditioning equipment control system disclosed in Patent Document 1, it is necessary to construct a simulation model of the entire air conditioning equipment in advance, but in an actual air conditioning equipment, heat demand according to the weather conditions and the calendar of the air conditioning equipment, The operating characteristics of each air conditioner differ depending on the layout status, air conditioner operating conditions, accumulated operating time of the air conditioner, etc., and the simulation model needs to be adjusted in detail to approximate the actual air conditioner operation status. Therefore, time and labor are consumed, and it takes a long time to calculate the control target value. Further, in this air conditioning equipment control system, each air conditioner is operated based on each control target value in the effective period of the constructed simulation model, but the control target value is not calculated every predetermined time, and one day. It is not possible to determine the optimum number of operating air conditioners and the amount of supplied heat for each predetermined time in the unit.

  An object of the present invention is to provide an operation plan determination system that can quickly determine the optimum number of operating heat sources and the amount of supplied heat without requiring time and labor. Another object of the present invention is to determine the optimum number of operating units and the amount of supplied heat for each heat source device every predetermined time in a day unit, and to realize efficient operation of these heat source devices and heat storage tanks. An object is to provide an operation plan determination system capable of constructing a detailed operation plan.

  The premise of the present invention for solving the above-mentioned problems was stored by a heat source facility formed of a demand structure that demands cold or hot heat and a plurality of heat source devices that supply cold or hot heat to the demand structure, and a heat storage operation Operation plan decision provided with a heat storage tank that radiates and supplies cold heat or heat to the heat source equipment and bears the heat demand of the heat source equipment, and a controller that determines the amount of heat supplied from the heat source equipment and the heat storage tank. System.

  As a feature of the present invention based on the premise, the controller receives the characteristic coefficient data of the heat source devices and the first heat demand data for each predetermined time in the unit of the heat source facility, and the controller receives the characteristic coefficient data and Heat source equipment that enables optimum operation of heat source equipment by applying the first mathematical programming method to the first heat demand data and deriving a solution that minimizes the predetermined objective function in the first mathematical programming method Second heat demand second data calculating means for calculating second heat demand data for each predetermined time, characteristic coefficient data, first heat demand data, and second heat demand data calculated by the second demand heat data calculating means. By applying the mathematical programming method of 2 and deriving a solution that minimizes the predetermined objective function in the second mathematical programming method, the predetermined time of those heat source devices conforming to the second heat demand data is obtained. Operating condition calculating means for calculating the optimum number of operating units and the optimum supply heat quantity for each predetermined time of the heat source equipment, the operating number of the heat source equipment for each predetermined time calculated by the operating condition calculating means, and the predetermined number of the heat source equipment And operating condition output means for outputting the amount of heat supplied every hour.

  As an example of the present invention, the controller is a heat source device operating unit that operates the heat source devices based on the number of operating units of the heat source devices calculated by the operating condition calculating unit per predetermined time and the amount of heat supplied per predetermined time of the heat source devices. And a heat storage tank operating means for operating the heat storage tank while adjusting the amount of heat supplied from the heat storage tank for each predetermined time of the cold or hot heat supplied from the demand heat quantity second data.

  As another example of the present invention, meteorological data on the operation plan decision date and heat demand condition data of the heat source facility on the operation plan decision date are input to the controller, and the controller receives the first demand heat amount from the past to the present. Predetermined data on the operation plan decision date of the heat source facility based on the first data storage means for storing data, the meteorological data and heat demand condition data on the operation plan decision date, and the first heat demand data stored by the first data storage means Demand heat quantity prediction data generation means for generating demand heat quantity prediction data for predicting demand heat quantity for each hour. The second demand heat quantity data calculation means includes a first mathematical programming method for the characteristic coefficient data and the demand heat quantity prediction data. Is applied to derive the solution that minimizes the predetermined objective function in the first mathematical programming method, thereby enabling optimum operation of the heat source equipment. Source to calculate a demand heat second data for each predetermined time facilities.

  As another example of the present invention, in the operation plan determination system, the predetermined time can be set in a range of 5 minutes to 120 minutes.

  As another example of the present invention, the objective function in the first mathematical programming is represented by {(Σ load on heat source device at a certain time (t) ÷ characteristic coefficient of heat source device) × energy intensity unit} A characteristic coefficient of the heat source device is calculated by (output of the heat source device ÷ input of the heat source device), and the constraint condition in the objective function is (1) load on the heat source device at a certain time (t) = a certain time (t) Demand of heat source equipment + heat storage amount of the heat storage tank at a certain time (t)-heat radiation amount of the heat storage tank at a certain time (t), but at least one of the heat storage amount of the heat storage tank and the heat radiation amount of the heat storage tank 0, (2) 0 ≦ heat storage amount of heat storage tank at a certain time (t) ≦ maximum heat storage amount per unit time, (3) 0 ≦ heat dissipation amount of the heat storage tank at a certain time (t) ≦ maximum heat dissipation amount per unit time (4) 0 ≦ Σ heat storage amount ≦ maximum capacity of the heat storage tank.

  As another example of the present invention, the objective function in the second mathematical programming method is represented by {(Σ heat source equipment output ÷ heat source equipment characteristic coefficient) × energy intensity unit}, and the heat source equipment characteristic coefficient is Calculated as (heat source device output ÷ heat source device input).

As another example of the present invention, the energy intensity is any one of heat source equipment operating cost, primary energy conversion amount, supplied heat amount, and CO ₂ emission amount.

  As another example of the present invention, the characteristic coefficient of the heat source device is obtained based on one of the product specification of the heat source device and the past operation results of the heat source device.

  According to the operation plan determination system according to the present invention, the second heat demand data for each predetermined period in the daily unit of the heat source equipment that enables the optimum operation of each heat source device using the first mathematical programming method first. Next, the optimum heat quantity for each predetermined period in the daily unit of the heat source equipment and the optimum supplied heat quantity for the predetermined period in the daily unit of the heat source equipment are calculated. Since the operation condition calculation means to calculate is executed, the operation plan of the heat source equipment and the operation plan of each heat source equipment can be performed independently, and each heat source equipment does not require adjustment work and takes time and labor. It is possible to quickly calculate the optimal number of operating units and the amount of heat supplied. In this operation plan determination system, an operation plan of a heat source facility for each predetermined period in a day unit is determined through the second calorie demand data calculation means, and the optimum for each predetermined time of each air conditioner is determined through the operation condition calculation means. Because the number of operating units and the amount of heat supplied are determined, the number of units operating and the amount of heat supplied for each heat source device can be adjusted every predetermined time according to the determined number of units operated and the amount of heat supplied. A detailed operation plan for realizing the operation can be established. This operation plan determination system can achieve an operation in accordance with the purpose of the heat source facility using the heat storage tank by determining the optimal number of operating units and the optimal amount of supplied heat for each predetermined time of the heat source devices.

  The controller operates the heat source devices based on the number of operating heat source devices calculated by the operating condition calculation means and the amount of heat supplied to the heat source devices, and the controller supplies the heat from the heat storage tank based on the second heat demand data. Alternatively, an operation plan determination system that operates a heat storage tank while adjusting the amount of heat supplied from a heat source does not rely on manual control of the heat source equipment or the heat storage tank, and the heat source equipment that exactly matches the operation plan by the controller that forms the system. The heat storage tank can be operated, and control errors of the heat source device and the heat storage tank due to manual intervention can be prevented. Since this operation plan determination system does not involve manpower in controlling the number of operating heat source devices, controlling the amount of heat supplied, and controlling the amount of heat supplied to the heat storage tank, it is possible to greatly reduce labor.

  Based on first data storage means for storing first demand heat quantity data from the past to the present, meteorological data and heat demand condition data on the operation plan decision date, and first demand heat quantity data stored by the first data storage means. The operation plan determination system including the demand heat amount prediction data generation means for generating the demand heat amount prediction data that predicts the demand heat amount for each predetermined time on the operation plan determination date of the heat source facility, the meteorological data, the heat demand condition data, the demand heat amount Based on one data, heat demand forecast data for each heat source equipment is generated every predetermined time, and using the heat demand prediction data approximated to the actual heat demand, the optimal number of units and supply for each heat source equipment at a given time The amount of heat can be calculated quickly. This operation plan determination system uses the characteristic coefficient data and the demand heat quantity prediction data to calculate the second heat demand data of the heat source equipment that enables the optimum operation of the heat source equipment. It is possible to construct a detailed operation plan for realizing efficient operation of the heat source device and the heat storage tank while omitting.

  The operation plan determination system that can set the predetermined time in the range of 5 minutes to 120 minutes calculates the optimal number of operating heat source devices and the optimal amount of heat supplied from the heat source devices every predetermined time. A detailed operation plan for realizing efficient operation of the heat storage tank can be reliably constructed. Since this operation plan determination system can select a predetermined time from 5 minutes to 120 minutes, the heat demand according to the calendar of the heat source facility, the operation conditions of each heat source device, the past operation time of each heat source device, the heat source device The predetermined time can be freely selected in consideration of various conditions such as the type of the heat storage tank and the like, and wasteful heat consumption in the heat source device and the heat storage tank can be prevented by setting an appropriate time.

The operation plan determination system whose energy intensity is any one of the heat source equipment operating cost, primary energy conversion amount, supply heat amount, and CO ₂ emission amount is the heat demand according to the calendar of the heat source equipment and the operating conditions of each heat source equipment. The type of energy intensity can be selected in consideration of the past operation time of each heat source device, the type of heat source device and heat storage tank, and the like. This operation plan determination system selects the optimum energy intensity according to various conditions, and obtains second heat demand data for each predetermined period in a day unit of the heat source equipment that enables the optimum operation of each heat source device. It is possible to determine the optimal number of operating units and the optimal amount of supplied heat for each predetermined time of the heat source devices, and it is possible to achieve an operation that matches the purpose of the heat source facility using the heat storage tank.

  An operation plan determination system in which the characteristic coefficient of a heat source device is obtained based on one of the product specifications of the heat source device and the past operation results of the heat source device can accurately determine the characteristic coefficient of the heat source device. It is possible to use the characteristic coefficient and determine the second heat demand data for each predetermined period in the daily unit of the heat source equipment that enables the optimum operation of each heat source apparatus, and to determine the optimum heat source apparatus for each predetermined time By determining the number of units to be operated and the optimal amount of heat to be supplied, an operation plan that matches the actual conditions of each device can be made.

  The details of the operation plan determination system according to the present invention will be described with reference to the accompanying drawings. FIG. 1 is a configuration diagram of an operation plan determination system 10A shown as an example. This operation plan determination system 10A is formed of a heat source facility 11, a heat storage tank 12, and a controller 13, and the optimum operation number and supplied heat amount for each predetermined time in a day unit of the heat source devices 15, 16, 17, 18, and 19. To decide. In addition, the determination time interval of the number of operating units and the amount of supplied heat can be freely set within a range of 5 to 120 minutes.

  The heat source facility 11 is formed of a demand facility 14 (demand structure) that demands cold or warm heat and a plurality of heat source devices 15, 16, 17, 18, and 19. The demand facility 14 includes all buildings such as office buildings, factories, offices, work places, general houses, halls, gymnasiums, indoor stadiums, and music halls. The demand facility 14 cools the facility by demanding cold in the summer, and heats the facility by demanding the heat in the winter. In this system 10 </ b> A, various heat source devices 15 to 19 are operated, and cold heat or heat from the heat source devices 15 to 19 is supplied to the demand facility 14, and the heat storage tank 12 is operated, and the heat storage tank 12 is cooled or heated. Is supplied to the demand facility 14.

  These heat source devices 15 to 19 are formed of device main bodies 15A, 16A, 17A, 18A, 19A and cold / hot water pumps 15B, 16B, 17B, 18B, 19B. Thermometers (not shown) are installed in the device main bodies 15A to 19A. The temperature of cold water or hot water in the heat source devices 15 to 19 can be changed by adjusting a temperature adjusting device (not shown) of the device main bodies 15A to 19A. Further, by adjusting the outputs of the pumps 15B to 19B, it is possible to change the supply amount of cold water or hot water supplied from the heat source devices 15 to 19 (the supply amount of cold or hot heat). Although five heat source devices 15 to 19 are illustrated in FIG. 1, the number of devices is not particularly limited, and the number of devices may be less than five or six or more. As the heat source devices 15 to 19, not only one of the cold heat source device and the heat source device can be used, but also a composite heat source system that effectively combines them can be adopted.

  A chilling unit, a turbo refrigerator, a screw refrigerator, a vapor compression refrigerator, an absorption refrigerator, an adsorption refrigerator, or the like can be used as the cold heat source device. Electric water heaters, gas instantaneous water heaters, round boilers, cast iron sectional boilers, furnace flue boilers, water tube boilers, cold / hot water generators, heat pumps, air conditioners, etc. can be used as heat source equipment . In addition, the said cold heat source apparatus and the said heat source apparatus are only illustrations, In this system 10A, not only all kinds of heat source apparatuses currently used but all kinds of heat source apparatuses used in the future can be used. it can.

  The heat storage tank 12 uses low-priced energy such as late-night power and radiates and supplies the heat or heat stored in the heat storage operation to the heat source equipment, thereby bearing the heat demand of the heat source equipment 11. The heat storage tank 12 is used for the purpose of energy saving of the device capacity of the heat source devices 15 to 19 corresponding to the processing at the peak of one day (24 hours). Moreover, when the light load driving | running of the heat-source equipment 15-19 is anticipated for a long time, it utilizes for the objective of aiming at the economical driving | operation of the heat-source equipment 15-19. Further, in order to avoid the operation of the heat source devices 15 to 19 during the peak time period of power demand, it is used as an alternative machine that supplies cold heat or heat to the heat source facility 11 instead. Although one heat storage tank 12 is illustrated in FIG. 1, the number of heat storage tanks is not particularly limited, and two or more heat storage tanks may be installed.

  Cold and hot water pumps 20 and 21 are connected to the heat storage tank 12, and a thermometer (not shown) and a temperature adjusting device (not shown) are installed. By adjusting the temperature adjusting device of the heat storage tank 12, the temperature of cold water or hot water in the heat storage tank 12 can be changed. Further, by adjusting the output of the pumps 20 and 21, the supply amount of cold water or hot water supplied from the heat storage tank 12 (the supply amount of cold or hot heat) can be changed. The heat storage tank 12 includes a temperature stratified heat storage tank, an open heat storage tank, a multi-purpose heat storage tank, a single heat storage tank, a single heat storage tank, a dual heat storage tank, a sealed heat storage tank, a connected heat storage tank, a connection A fully mixed heat storage tank or the like can be used. In addition, the said heat storage tank is only an illustration, In this system 10A, not only all kinds of heat storage tanks currently used but all kinds of heat storage tanks used in the future can be used.

  The controller 13 is a computer having a central processing unit (CPU or MPU) and a memory (large capacity hard disk). Although not shown, the controller 13 is connected to an input device such as a mouse and a keyboard and an output device such as a display and a printer via an interface. The memory of the controller 13 stores an operation plan determination application for causing the controller 13 to execute predetermined means. The central processing unit of the controller 13 activates the operation plan determination application from the memory based on the control by the operating system stored in the memory, and executes the following means according to the application.

  The central processing unit of the controller 13 executes a first required heat amount transition table creating means for creating a first required heat amount transition table that represents a change in heat amount for each predetermined time in a day based on first demand heat amount data to be described later. Then, using the mathematical programming method (first mathematical programming method), the second heat demand amount data indicating the heat demand amount for each predetermined time of the heat source equipment 11 enabling the optimum operation of the heat source devices 15 to 19 is calculated. The demand heat amount second data calculating means is executed. The central processing unit executes a second required heat amount transition table creating means for creating a second required heat amount transition table that represents a transition of the heat amount change for each predetermined time in a day based on the second demand heat amount data, and the mathematical programming method Utilizing (second mathematical programming), the optimal number of operating heat source devices 15 to 19 for each predetermined time and the optimal supply of these heat source devices 15 to 19 for each predetermined time based on the second demand heat data An operating condition calculating means for calculating the amount of heat is executed. The central processing unit executes an operating condition output unit that outputs the number of operating units of the heat source devices 15 to 19 calculated for each predetermined time and the amount of heat supplied to the heat source devices 15 to 19 for each predetermined time calculated by the operating condition calculating unit.

  When only the heat source devices 15 to 19 are operating, cold or hot heat flows from the devices 15 to 19 through the pipes via the pumps 15 </ b> B to 19 </ b> B into the header pipe 22. Flows into the demand facility 14. The cold or warm heat demanded at the demand facility 14 flows into the header pipe 23 and then flows into the heat source devices 15 to 19 again. When only the heat storage tank 12 is in operation, cold or hot heat flows from the heat storage tank 12 through the pipes into the header pipe 22 via the pumps 20 and 21, and cold or hot heat is supplied from the header pipe 22 to the demand facility 14. Flow into. The cold or warm heat demanded in the demand facility 14 flows into the header pipe 23 and then flows into the heat storage tank 12 again.

  When the heat source devices 15 to 19 and the heat storage tank 12 are in operation, the cooling pipes or the heat from the devices 15 to 19 and the heat storage tank 12 through the pumps 15B to 19B, 20, and 21 pass through the pipelines and header piping. The cold heat or hot heat flows into the demand facility 14 from the header pipe 22. The cold or warm heat demanded at the demand facility 14 flows into the header pipe 23 and then flows into the heat source devices 15 to 19 and the heat storage tank 12 again. By operating only the heat storage tank 12 or the heat source equipments 15 to 19 and the heat storage tank 12, the heat storage tank 12 can bear all or part of the heat demand demanded at the demand facility 14. It is possible to save energy of 19 device capacities.

  FIG. 2 is a diagram illustrating an example of processing in the controller 13, and FIG. 3 is a flowchart illustrating an example of an execution procedure of each unit of the controller 13. FIG. 4 is a diagram of a first required heat amount transition table showing a time-series transition of demand heat quantity first data, and FIG. 5 is a second required heat amount transition showing a time-series transition of demand heat amount second data. FIG. FIG. 6 is a diagram illustrating an example of the number of operating heat source devices 15 to 19 and the amount of supplied heat calculated by the controller 13. 4 and 5, the supply heat quantity (kWh) is displayed on the vertical axis, and the time (h) is displayed on the horizontal axis. In FIG. 5, the transition of the hourly heat amount change in the first day of the demand heat quantity first data is indicated by a dotted line, and the change of the hourly heat amount change in the day of the demand heat amount second data is indicated by a solid line.

  When the switch of the controller 13 is turned on, the operation plan determination application is activated, and an initial screen (not shown) is displayed on the display connected to the controller 13. An operation plan calculation button, an operation condition setting button, and a close button are displayed on the initial screen. When the operating condition setting button is clicked, the date input area, time interval input area, characteristic coefficient input area for each heat source device, demand heat amount first data input area, input execution button, cancel button, and clear button are displayed on the display. The An operation plan decision date (usually the next day) is input to the date input area via a mouse or keyboard, and a time interval (range of 5 to 120 minutes) is input to the time interval input area. In this system, it is assumed that 1 hour (60 minutes) is input as the time interval. Furthermore, the characteristic coefficient data of the heat source devices 15 to 19 are input to the characteristic coefficient input area, and the first heat demand data for each hour of the heat source facility 11 is input to the first heat demand data input area ( S-1).

  When the input execution button is clicked after inputting them, the controller 13 associates the serial numbers of the heat source devices 15 to 19 with the operation plan determination date, stores the operation plan determination date in the internal address file of the memory, The serial number and the operation plan decision date are associated with the time interval, and the time interval is stored in the internal address file. Further, the serial number and the operation plan decision date are associated with the characteristic coefficient data, the characteristic coefficient data are stored in the internal address file of the memory, the serial number and the operation plan decision date are associated with the demand heat quantity first data, and the demand The first amount of heat data is stored in the internal address file. When these operating conditions are stored in the controller 13, the screen returns to the initial screen. If the clear button is clicked, the input data is cleared and the operation conditions are input again. Clicking the Cancel button cancels the operating condition settings and returns to the initial screen.

  The characteristic coefficient data of the heat source devices 15 to 19 can be obtained based on the product specifications of the heat source devices 15 to 19 or the past operation results of the heat source devices 15 to 19. When setting the characteristic coefficient according to the product specifications, the characteristic coefficient is obtained by using the apparatus characteristics described in catalogs, product specifications, instruction manuals, etc. issued by the manufacturers and distributors of the respective devices 15 to 19. As an example, after analyzing the appropriate input / output of each of the devices 15 to 19 from the device characteristics, the characteristic coefficient is calculated by using the analyzed input / output (output of the heat source device ÷ input of the heat source device). Moreover, when setting a characteristic coefficient by the past driving | operation track record, the past input and the output track | truck of each apparatus 15-19 are employ | adopted, and a characteristic coefficient is calculated | required from those input / output relationships. As an example, the input / output of each device 15 to 19 from the past to the present is extracted, the input and output are analyzed using a statistical regression method, and then the characteristic coefficient ( Heat source equipment output ÷ heat source equipment input).

  Note that the controller 13 can also calculate the characteristic coefficients of the heat source devices 15 to 19. In this case, when the inputs and outputs of the heat source devices 15 to 19 are input to the input / output input area of the characteristic coefficient input area, the controller 13 uses these inputs and outputs to calculate the characteristic coefficient (the output of the heat source device). ÷ input of heat source device), the serial number of each of the heat source devices 15 to 19 and the operation plan determination date are associated with the characteristic coefficient data, and the characteristic coefficient data is stored in the internal address file of the memory. Since this system 10A obtains the characteristic coefficient of the heat source devices 15 to 19 based on the product specifications of the devices 15 to 19 or the past operation results of the devices 15 to 19, the accurate characteristic coefficient of the heat source devices 15 to 19 is obtained. Can be reflected in the operation plan.

  When various operation conditions are input to the controller 13 and an operation plan calculation button on the initial screen is clicked, an operation plan calculation date input area, a plan calculation execution button, and a cancel button are displayed on the display. After inputting the operation plan calculation date (operation plan determination date) in the operation plan calculation date input area, when the plan calculation execution button is clicked, the controller 13 extracts the first heat demand data at the operation plan calculation date from the memory, As shown in FIG. 4, based on the first data, a first required heat amount transition table representing a change in heat amount for every hour of the first day of demand heat amount first data is created (a first required heat amount transition table is created). Means) (S-2), the serial number and the operation plan decision date of the heat source devices 15 to 19 are associated with the created first required heat amount transition table, and the first required heat amount transition table is stored in the internal address file of the memory. (First required heat amount transition table storing means).

  Next, the controller 13 extracts the characteristic coefficient data from the memory, applies the first mathematical programming method to the characteristic coefficient data and the first heat demand data, and minimizes a predetermined objective function in the mathematical programming method. Calculating the second heat demand data for each hour of the heat source equipment 11 that enables the optimum operation of the heat source devices 15 to 19 by deriving the solution (demand heat second data calculation means) (S-3) . The controller 13 associates the serial numbers and operation plan determination dates of the heat source devices 15 to 19 with the calculated second demand heat quantity data, and stores the second demand heat quantity data in the internal address file of the memory (second demand heat quantity data). Storage means). After calculating the second heat demand data, the controller 13, as shown in FIG. 5, based on the second data, the second request representing the hourly change in the heat power for one day of the second heat demand data. A heat quantity transition table is created (second required heat quantity transition table creating means) (S-4), and the serial number and operation plan decision date of the heat source devices 15 to 19 are associated with the created second required heat quantity transition table. 2 The required heat amount transition table is stored in the internal address file of the memory (second required heat transition table storage means).

  The objective function in the first mathematical programming is represented by {(Σ load on heat source device at certain time (t) ÷ characteristic coefficient of heat source device) × energy intensity unit}. The constraints in the objective function are (1) load on heat source equipment at a certain time (t) = heat demand of heat source equipment at a certain time (t) + heat storage amount in a heat storage tank at a certain time (t) − Heat release amount of heat storage tank at time (t), where at least one of heat storage amount of heat storage tank and heat release amount of heat storage tank is 0, (2) 0 ≦ heat storage amount of heat storage tank at a certain time (t) ≦ Maximum heat storage amount per unit time, (3) 0 ≦ heat release amount of heat storage tank at a certain time (t) ≦ maximum heat release amount per unit time, (4) 0 ≦ Σ heat storage amount ≦ maximum capacity of heat storage tank.

The energy consumption rate in the objective function employs the operating costs of the heat source devices 15-19. As the energy intensity, any one of the primary energy conversion amount, the supply heat amount, and the CO ₂ emission amount can be adopted in addition to the operation cost. This system 10A includes heat demand according to the calendar of the heat source equipment 11, operating conditions of the heat source devices 15 to 19, past operation times of the heat source devices 15 to 19, types of the heat source devices 15 to 19 and the heat storage tank 12, and the like. The type of energy intensity can be freely selected in consideration of

  The controller 13 applies the second mathematical programming method to the characteristic coefficient data, the first demand heat amount data, and the calculated second demand heat amount data, and obtains a solution that minimizes a predetermined objective function in the second mathematical programming method. By deriving, the optimum number of hourly operation of the heat source devices 15 to 19 and the optimum supply heat amount of each hour of the heat source devices 15 to 19 based on the second demand heat amount data are calculated (operating conditions). Calculation means) (S-5). The controller 13 associates the serial numbers and operation plan determination dates of the heat source devices 15 to 19 with the calculated number of operating units and the amount of supplied heat, and stores the number of operating units and the amount of supplied heat in the internal address file of the memory (operating condition storage means). . The objective function in the second mathematical programming method is expressed as {(Σ heat source device output ÷ heat source device characteristic coefficient) × energy intensity unit}. The energy intensity is the same as that of the objective function in the first mathematical programming.

  When requesting the output of the number of operating heat source devices 15 to 19 and the supply heat amount on the operation plan calculation date via the keyboard, the controller 13 of the heat source devices 15 to 19 on the operation plan determination date is shown in FIG. The number of operating units for each hour and the amount of heat supplied for each hour are displayed on the display and output via a printer (operating condition output means) (S-6). In the operation condition list output from the printer, as shown in FIG. 6, 24 hours a day are divided every hour, and the number of operating heat source devices 15 to 19 and one of the heat source devices 15 to 19 to be operated are set. The amount of heat supplied per hour is displayed.

  The operator of the system 10A operates the heat source devices 15 to 19 to be operated among the heat source devices 15 to 19 according to the number of operating heat source devices 15 to 19 and the amount of supplied heat. The temperature of the heat source devices 15 to 19 is adjusted, and the pumps 15B to 19B of the heat source devices 15 to 19 to be operated are adjusted to match the supply heat amount of the devices 15 to 19 with the output heat amount. Further, the temperature of the heat storage tank 12 is adjusted, and the amount of heat supplied to the heat source facility 11 from the heat storage tank 12 is adjusted by adjusting the pumps 20 and 21 of the heat storage tank 12. This operation is performed at set time intervals (every hour).

  For example, at 0 o'clock, the devices 15 and 16 among the heat source devices 15 to 19 are operated, and the devices 17, 18 and 19 are not operated. Further, the amount of heat supplied to the device 15 is adjusted to 8.7 (kWh), and the amount of heat supplied to the device 16 is adjusted to 8.8 (kWh). At 1 o'clock after 1 hour has elapsed, the amount of heat supplied to the device 15 is adjusted to 6.1 (kWh), and the amount of heat supplied to the device 16 is adjusted to 8.0 (kWh). At 7 o'clock, the device 17 is operated in addition to the devices 15 and 16, the supply heat amount of the device 17 is 4.7 (kWh), the supply heat amount of the device 16 is 11.1 (kWh), and the supply heat amount of the device 15 Is adjusted to 10.6 (kWh). At 10 o'clock, all the devices 15 to 19 are operated, the supply heat amount of the device 15 is 7.1 (kWh), the supply heat amount of the device 16 is 7.4 (kWh), and the supply heat amount of the device 17 is 3.9 (kWh) ), The amount of heat supplied to the device 18 is adjusted to 4.2 (kWh), and the amount of heat supplied to the device 19 is adjusted to 7.1 (kWh).

  This operation plan determination system 10A first uses the first mathematical programming method, and the second heat demand data for each hour in the daily unit of the heat source equipment 11 that enables the optimum operation of each of the heat source devices 15-19. The second calculation unit for demand heat amount for calculating the heat source device 15 and the optimum number of operating units per hour in the daily unit of the heat source devices 15 to 19 and one hour in the daily unit of the heat source devices 15 to 19 Since the operation condition calculation means for calculating the optimum supply heat quantity for each is executed, the operation plan for the heat source equipment 11 and the operation plans for the respective heat source devices 15 to 19 can be performed independently, and each of them can be performed via the controller 13. The optimal number of operating heat source devices 15 to 19 and the amount of supplied heat can be quickly calculated.

  The operation plan determination system 10A determines an operation plan of the heat source facility 11 for each hour in a unit of day via the demand heat amount second data calculation means, and each heat source device 15 for each hour via the operation condition calculation means. Since the optimum number of operating units and the amount of supplied heat are determined, the operating number of units and the amount of supplied heat of each of the heat source devices 15 to 19 can be adjusted every hour according to the determined number of operating units and the amount of supplied heat. A detailed operation plan for realizing efficient operation of 15 to 19 and the heat storage tank 12 can be constructed. This system 10 </ b> A determines the optimal number of operating units and the optimal amount of supplied heat for each hour of the heat source devices 15 to 19, thereby achieving an operation that matches the purpose of the heat source facility 11 using the heat storage tank 12. it can.

  FIG. 7 is a configuration diagram of an operation plan determination system 10 </ b> B shown as another example, and FIG. 8 is a diagram showing another example of processing in the controller 13. FIG. 9 is a flowchart illustrating another example of the execution procedure of each unit of the controller 13. The operation plan determination system 10A is different from that shown in FIG. 1 in that the temperature control devices, pumps 15B to 19B, and thermometers of the heat source devices 15 to 19 are connected to the controller 13 via the interface 24. The adjustment device, the pumps 20 and 21, and the thermometer are connected to the controller 13 through the interface 24. In this system 10B, the temperature control of the heat source devices 15 to 19, the output control of the pumps 15B to 19B, the temperature control of the heat storage tank 12, and the output control of the pumps 20 and 21 are performed by the controller 13, and the controller 13 does not involve human intervention. Thus, the system 10B is automatically operated. Since other configurations in the system 10B are the same as those in FIG. 1, the same reference numerals as those in the system 10A in FIG. 1 are used to omit the description of the other configurations in the system 10B.

  The controller 13 adjusts the temperature adjusting device of the device main bodies 15A to 19A, and adjusts the temperature of cold water or hot water in the heat source devices 15 to 19. Moreover, the output of the pumps 15B to 19B is adjusted, and the supply amount of cold water or hot water supplied from the heat source devices 15 to 19 (the supply amount of cold or warm heat) is adjusted. The controller 13 adjusts the temperature adjusting device of the heat storage tank 12 to adjust the temperature of the cold water or the hot water in the heat storage tank 12. Furthermore, the output of the pumps 20 and 21 is adjusted, and the supply amount of cold water or hot water supplied from the heat storage tank 12 (the supply amount of cold or hot heat) is adjusted.

  The central processing unit of the controller 13 not only executes the first required heat amount transition table creating means, the demand heat amount second data calculating means, the second required heat amount transition table creating means, and the operating condition output means, but also includes the following means: Execute. The central processing unit executes first data storage means for storing the first demand heat quantity data from the past to the present, and obtains demand heat quantity prediction data in which the demand heat quantity for each predetermined time on the operation plan decision date of the heat source facility 11 is predicted. The generated demand heat quantity prediction data generating means is executed. The central processing unit operates the heat source devices 15 to 19 based on the number of operating units of the heat source devices 15 to 19 calculated for each predetermined time and the amount of heat supplied for each predetermined time of the heat source devices 15 to 19 calculated by the operating condition calculation unit. The heat storage device operation means is executed, and the heat storage tank operation means is operated to adjust the supply heat amount for each predetermined time of the cold or hot heat supplied from the heat storage tank 12 based on the second demand heat amount data. To do.

  When the system 10B is activated, the controller 13 is activated, and the heat source devices 15 to 19 and the heat storage tank 12 are activated. An initial screen (not shown) is displayed on the display connected to the controller 13. An operation plan calculation button, an operation condition setting button, and a close button are displayed on the initial screen. When the operation condition setting button is clicked, the display shows a date input area, a time interval input area, a characteristic coefficient input area for each heat source device 15-19, a weather data input area, a heat demand condition data input area, an input execution button, and a cancel button. Button and clear button are displayed. The first heat demand data from the past to the present is already stored in the internal address file of the memory in a state associated with the serial numbers of the heat source devices 15 to 19 and the operation plan determination date (first data storage means). (S-10). An operation plan decision date (usually the next day) is input to the date input area via a mouse or keyboard, and a time interval (range of 5 to 120 minutes) is input to the time interval input area. In this system 10B, it is assumed that 1 hour (60 minutes) is input as the time interval, as in FIG.

  Characteristic coefficient data of the heat source devices 15 to 19 is input to the characteristic coefficient input area. When the inputs and outputs of the heat source devices 15 to 19 are input to the input / output input area of the characteristic coefficient input area, the controller 13 uses these inputs / outputs to calculate the characteristic coefficient (output of the heat source device / heat source device output). Input). The controller 13 can obtain the characteristic coefficient data of the devices 15 to 19 based on the product specifications of the heat source devices 15 to 19 or the past operation results of the heat source devices 15 to 19. Next, weather data such as temperature and humidity at the date of operation plan decision is entered in the weather data input area, and heat demand such as calendar heat demand or past heat demand record or heat demand set value is entered in the heat demand condition data entry area. Demand condition data and the like are input (S-11). Since this system 10B calculates | requires the characteristic coefficient of the heat-source equipment 15-19 based on the product specification of the equipment 15-19, or the past driving | operation performance of the equipment 15-19, it calculates | requires the exact characteristic coefficient of the heat-source equipment 15-19. Can be reflected in the operation plan.

  When the input execution button is clicked after inputting them, the controller 13 associates the serial numbers of the heat source devices 15 to 19 with the operation plan determination date, stores the operation plan determination date in the internal address file of the memory, The serial number and the operation plan decision date are associated with the time interval, and the time interval is stored in the internal address file. The controller 13 associates the serial numbers and operation plan determination dates of the heat source devices 15 to 19 with the calculated characteristic coefficients of the devices 15 to 19, stores these characteristic coefficients in an internal address file of the memory, and determines the serial number and the operation plan. Associate the day with weather data and store the weather data in the internal address file. Further, the serial number and the operation plan determination date are associated with the heat demand condition data, and the heat demand condition data is stored in the internal address file. When these operating conditions are stored in the controller 13, the screen returns to the initial screen.

  When various operation conditions are input to the controller 13 and an operation plan calculation button on the initial screen is clicked, an operation plan calculation date input area, a plan calculation execution button, and a cancel button are displayed on the display. When an operation plan calculation date (operation plan decision date) is entered in the operation plan calculation date input area and then a plan calculation execution button is clicked, the controller 13 causes the demand heat amount first data, weather data, and heat demand on the operation plan calculation date. The condition data is extracted from the internal address file of the memory, and the demand heat quantity per hour on the operation plan calculation date (operation plan decision date) of the heat source equipment 11 is calculated based on the first demand heat quantity data, weather data, and heat demand condition data. Predicted demand heat quantity prediction data is generated (demand heat quantity prediction data generation means) (S-12). The controller 13 associates the serial numbers and operation plan determination dates of the heat source devices 15 to 19 with the generated demand heat amount prediction data, and stores the demand heat amount prediction data in the internal address file of the memory. (Demand heat quantity forecast data storage means).

  The controller 13 extracts the demand heat quantity prediction data from the memory, and creates a first required heat quantity transition table indicating the transition of the heat quantity change every hour in the day of the demand heat quantity prediction data based on the prediction data (first). (Required heat amount transition table creation means) (S-13), the serial number and operation plan determination date of the heat source devices 15 to 19 are associated with the created first required heat amount transition table, and the first required heat amount transition table is stored in the memory. Store in the address file (first required heat amount transition table storage means). In addition, the 1st requirement calorie | heat amount transition table created in this system 10B uses FIG. 4, and the illustration is abbreviate | omitted.

  Next, the controller 13 extracts characteristic coefficient data from the memory, applies the first mathematical programming method to the characteristic coefficient data and the demand heat quantity prediction data, and minimizes a predetermined objective function in the mathematical programming method. By deriving the solution, the second heat demand amount data of the heat source equipment 11 that enables the optimum operation of the heat source devices 15 to 19 is calculated (second demand heat amount data calculating means) (S-14). The controller 13 associates the serial numbers and operation plan determination dates of the heat source devices 15 to 19 with the calculated second demand heat quantity data, and stores the second demand heat quantity data in the internal address file of the memory (second demand heat quantity data). Storage means). After calculating the demand heat quantity second data, the controller 13 creates a second required heat quantity transition table that represents the transition of the heat quantity change for each hour of the demand heat quantity second data on the basis of the second data ( (Second required heat amount transition table creating means) (S-15), the serial number of the heat source devices 15 to 19 and the operation plan decision date are associated with the created second required heat amount transition table, and the second required heat amount transition table is stored in the memory. In the internal address file (second required heat transition table storage means).

In addition, the 2nd request | requirement calorie | heat amount transition table created in this system 10B uses FIG. 5, and the illustration is abbreviate | omitted. The objective function in the first mathematical programming method is the same as that of the system 10A in FIG. As the energy intensity, any one of primary energy conversion amount, supply heat amount, and CO ₂ emission amount is adopted in addition to the operating cost. This system 10B includes the heat demand according to the calendar of the heat source facility 11, the operating conditions of the heat source devices 15 to 19, the past operation time of the heat source devices 15 to 19, the types of the heat source devices 15 to 19 and the heat storage tank 12, and the like. The type of energy intensity can be freely selected in consideration of

  The controller 13 applies the second mathematical programming method to the characteristic coefficient data, the demand heat quantity prediction data, and the demand heat quantity second data, and derives a solution that minimizes a predetermined objective function in the second mathematical programming method. Thus, the optimal number of operating units per hour of the heat source devices 15 to 19 and the optimal amount of heat supplied per hour of the heat source devices 15 to 19 based on the second heat demand data are calculated (operating condition calculating means). (S-16). The controller 13 associates the serial numbers and operation plan determination dates of the heat source devices 15 to 19 with the calculated number of operating units and the amount of supplied heat, and stores the number of operating units and the amount of supplied heat in the internal address file of the memory (operating condition storage means). . The objective function and the energy unit in the second mathematical programming are the same as those of the objective function in the first mathematical programming.

  When requesting the output of the number of operating heat source devices 15 to 19 and the supply heat amount on the operation plan calculation date via the keyboard, the controller 13 operates the number of operating heat source devices 15 to 19 for each hour on the operation plan determination date and The amount of heat supplied for each time is displayed on a display and output via a printer (operation condition output means). The operating condition output from the printer uses FIG. 6 and its illustration is omitted. The controller 13 operates the heat source devices 15 to 19 based on the number of hourly operating units of the heat source devices 15 to 19 calculated by the operating condition calculation means and the amount of heat supplied to the heat source devices 15 to 19 per hour ( (Heat source equipment operation means) (S-17), operating the heat storage tank 12 while adjusting the amount of heat supplied from the heat storage tank 12 based on the demanded second heat data (heat storage tank operation means) (S -17). Specifically, the controller 13 operates the heat source devices 15 to 19 to be operated among the heat source devices 15 to 19 and adjusts the temperature control device of the heat source devices 15 to 19 to be operated. The pumps 15B to 19B of the heat source devices 15 to 19 are adjusted to adjust the supply heat amount of the devices 15 to 19 to the output heat amount. Further, the amount of heat supplied from the heat storage tank 12 to the heat source facility 11 is adjusted by adjusting the pumps 20 and 21 of the heat storage tank 12 while adjusting the temperature control device of the heat storage tank 12.

  The controller 13 adjusts the temperature control device of the heat source devices 15 to 19 to change the temperature every hour and adjusts the pumps 15B to 19B of the heat source devices 15 to 19 to output the pumps 15B to 19B every hour. change. Moreover, while adjusting the temperature control apparatus of the heat storage tank 12 every hour and changing temperature, the pumps 20 and 21 of the heat storage tank 12 are adjusted every hour and the output of the pumps 20 and 21 is changed. In addition, when the time interval for determining the number of operating units and the amount of supplied heat is set to 10 minutes, the temperature control device of the heat source devices 15 to 19 is adjusted every 10 minutes to change the temperature, and the heat source devices 15 to 15 are changed every 10 minutes. The 19 pumps 15B to 19B are adjusted to change the outputs of the pumps 15B to 19B. Further, the temperature control device of the heat storage tank 12 is adjusted every 10 minutes to change the temperature, and the pumps 20 and 21 of the heat storage tank 12 are adjusted every 10 minutes to change the output of the pumps 20 and 21.

  For example, as shown in FIG. 6, in the case of 0 o'clock, the controller 13 operates the devices 15 and 16 among the heat source devices 15 to 19 and does not operate the devices 17, 18, and 19. Further, the amount of heat supplied to the device 15 is adjusted to 8.7 (kWh), and the amount of heat supplied to the device 16 is adjusted to 8.8 (kWh). In the case of 1 o'clock after one hour has elapsed, the controller 13 adjusts the amount of heat supplied to the device 15 to 6.1 (kWh) and adjusts the amount of heat supplied to the device 16 to 8.0 (kWh). In the case of 7 o'clock, the controller 13 activates the device 17 in addition to the devices 15 and 16, the supply heat amount of the device 17 is 4.7 (kWh), the supply heat amount of the device 16 is 11.1 (kWh), The supply heat amount of the device 15 is adjusted to 10.6 (kWh). In the case of 10 o'clock, the controller 13 operates all the devices 15 to 19, the supply heat amount of the device 15 is 7.1 (kWh), the supply heat amount of the device 16 is 7.4 (kWh), and the supply heat amount of the device 17 is 3.9 (kWh), the supply heat amount of the device 18 is adjusted to 4.2 (kWh), and the supply heat amount of the device 19 is adjusted to 7.1 (kWh).

  This operation plan determination system 10B has the following effects in addition to the effects it has in FIG. The system 10B generates demand heat amount prediction data for each predetermined time of the heat source facility 11 based on weather data, heat demand condition data, and first heat demand data from the past to the present, and the demand approximated to the actual heat demand. Using the heat amount prediction data, it is possible to quickly calculate the optimum number of operating units and the amount of supplied heat for each predetermined time of each of the heat source devices 15 to 19. Since this system 10B uses the characteristic coefficient data and the demand heat quantity prediction data to calculate the second demand heat quantity data of the heat source equipment 11 that enables the optimum operation of the heat source devices 15 to 19, the demand heat quantity data is input. A detailed operation plan for realizing efficient operation of the heat source devices 15 to 19 and the heat storage tank 12 can be constructed while saving time and effort.

  In the operation plan determination system 10B, the temperature control of the heat source devices 15-19, the output control of the pumps 15B-19B, the temperature control of the heat storage tank 12, and the output control of the pumps 20, 21 are performed by the controller 13, and the system 10B is controlled by the controller 13. Therefore, without relying on manual control of the heat source devices 15 to 19 and the heat storage tank 12, the heat source devices 15 to 19 and the heat storage tank that exactly match the operation plan by the controller 13 forming the system 10B. 12 can be performed, and control errors of the heat source devices 15 to 19 and the heat storage tank 12 due to manual intervention can be prevented. Since this system 10B does not involve human intervention in the control of the number of operating heat source devices 15 to 19, the control of the amount of heat supplied, and the control of the amount of heat supplied to the heat storage tank 12, it can greatly reduce labor. The system 10 </ b> B reliably operates in accordance with the purpose of the heat source facility 11 using the heat storage tank 12 by operating the heat source devices 15 to 19 and the heat storage tank 12 that exactly match the operation plan by the controller 13. be able to.

  In the system 10A of FIG. 1, the controller 13 applies the first mathematical programming method to the characteristic coefficient data and the first demand heat quantity data, and the hourly operation of the heat source equipment 11 that enables the optimum operation of the heat source equipment 15-19. 7, the controller 13 calculates the operation plan decision date of the heat source facility 11 based on the first demand heat data, the weather data, and the heat demand condition data as in the system 10B of FIG. A heat source that generates heat demand prediction data that predicts the heat demand per hour and applies the first mathematical programming method to the characteristic coefficient data and the heat demand prediction data to enable optimum operation of the heat source devices 15-19. The second heat demand amount data of the facility 11 may be calculated. In this case, the controller 13 stores first heat demand data from the past to the present, and weather data and heat demand condition data are input to the controller 13. Further, in the system 10A of FIG. 1, the operator operates the heat source devices 15-19 and the heat storage tank 12 according to the number of operating heat source devices 15-19 and the amount of supplied heat output from the controller 13, but the system 10B of FIG. Similarly to the above, it is possible to cause the controller 13 to operate the heat source devices 15 to 19 and the heat storage tank 12.

  In the system 10B of FIG. 7, the controller 13 generates demand heat quantity prediction data in which the demand heat quantity for each hour on the operation plan decision date of the heat source facility 11 is predicted based on the first demand heat quantity data, weather data, and heat demand condition data. Then, by applying the first mathematical programming method to the characteristic coefficient data and the demand heat quantity prediction data, the second demand heat quantity data for each hour of the heat source equipment 11 enabling the optimum operation of the heat source equipment 15 to 19 is calculated. However, similarly to the system 10A of FIG. 1, the controller 13 applies the first mathematical programming method to the characteristic coefficient data and the first demand heat quantity data, thereby enabling the heat source equipment 15 to 19 to operate optimally. The second heat demand amount data of the facility 11 may be calculated. Further, in the system 10B of FIG. 7, the controller 13 operates the heat source devices 15 to 19 and the heat storage tank 12, but the operation of the heat source devices 15 to 19 output from the controller 13 is performed as in the system 10A of FIG. The operator can also operate the heat source devices 15 to 19 and the heat storage tank 12 according to the number and the amount of heat supplied.

The block diagram of the driving plan determination system shown as an example. The figure which shows an example of the process in a controller. The flowchart which shows an example of the execution procedure of each means of a controller. The figure of the 1st requirement calorie | heat amount transition table showing the time-sequential transition of demand calorie | heat amount 1st data. The figure of the 2nd request | requirement calorie | heat amount transition table showing the time-sequential transition of demand calorie | heat amount 2nd data. The figure showing an example of the operating number of each heat-source apparatus calculated by the controller, and supplied heat amount. The block diagram of the driving plan determination system shown as another example. The figure which shows another example of the process in a controller. The flowchart which shows another example of the execution procedure of each means of a controller.

Explanation of symbols

10A Operation plan decision system 10B Operation plan decision system 11 Heat source equipment 12 Heat storage tank 13 Controller 14 Demand facility 15 Heat source equipment 15A Equipment body 15B Cold / hot water pump 16 Heat source equipment 16A Equipment body 16B Cold / hot water pump 17 Heat source equipment 17A Equipment body 17B Cold / hot water Pump 18 Heat source equipment 18A Equipment main body 18B Cold / hot water pump 19 Heat source equipment 19A Equipment main body 19 Cold / hot water pump 20 Cold / hot water pump 21 Cold / hot water pump

Claims (8)

A heat source facility formed from a demand structure that demands cold energy or heat, and a plurality of heat source devices that supply cold energy or heat to the demand structure, and the heat source facility radiates and supplies cold heat or heat stored by a heat storage operation, In the operation plan determination system comprising a heat storage tank that bears the heat demand of the heat source facility, and a controller that determines the amount of heat supplied from the heat source device and the cold or hot heat supplied from the heat storage tank,
The controller receives the characteristic coefficient data of the heat source devices and the first demand heat data for each predetermined time in the unit of the heat source equipment,
The controller applies a first mathematical programming method to the characteristic coefficient data and the first demand heat data, and derives a solution that minimizes a predetermined objective function in the first mathematical programming method, Demand heat amount second data calculation means for calculating demand heat amount second data for each predetermined time of the heat source equipment enabling the optimum operation of the heat source device;
A second mathematical programming method is applied to the characteristic coefficient data, the first demand heat quantity data, and the second demand heat quantity data calculated by the second demand heat quantity data calculation means, and a predetermined number in the second mathematical programming method is determined. By deriving a solution that minimizes the objective function, the optimal number of operating heat source devices per predetermined time and the optimal amount of heat supplied per predetermined time of the heat source devices in accordance with the second heat demand data are calculated. Operating condition calculation means;
An operation plan determination system, comprising: an operation condition output unit that outputs the number of operating units of the heat source devices per predetermined time calculated by the operating condition calculation unit and the amount of heat supplied per predetermined time of the heat source devices.   The controller, heat source equipment operating means for operating the heat source equipment based on the number of operating units of the heat source equipment calculated per predetermined time and the amount of heat supplied per predetermined time of the heat source equipment calculated by the operating condition calculating means, and the demand 2. An operation plan determination system according to claim 1, further comprising: a heat storage tank operating means that operates the heat storage tank while adjusting the amount of heat supplied for each predetermined time of cold or warm heat supplied from the heat storage tank based on the second heat amount data. .   The controller receives the weather data on the operation plan decision date and the heat demand condition data of the heat source facility on the operation plan decision date, and the controller stores the first heat demand data from the past to the present. Operating plan determination date of the heat source facility based on the first data storage means, the weather data and the heat demand condition data on the operation plan determination date, and the demand heat quantity first data stored by the first data storage means Demand heat quantity prediction data generation means for generating demand heat quantity prediction data in which the demand heat quantity for each predetermined time is predicted, and in the demand heat quantity second data calculation means, the characteristic coefficient data and the demand heat quantity prediction data include Applying the first mathematical programming and deriving a solution that minimizes a predetermined objective function in the first mathematical programming , Operation plan determination system according to claim 1 or claim 2 for calculating a demand amount of heat the second data for each predetermined time of the heat source equipment to enable optimal operation of the heat source device.   The operation plan determination system according to any one of claims 1 to 3, wherein in the operation plan determination system, the predetermined time can be set in a range of 5 minutes to 120 minutes. The objective function in the first mathematical programming is
{(Load on heat source equipment at a certain time (t) ÷ Characteristic coefficient of heat source equipment) × Energy intensity unit}
The characteristic coefficient of the heat source equipment is
(Heat source device output ÷ heat source device input)
The constraint on the objective function is
(1) Load on heat source equipment at a certain time (t) = heat demand of heat source equipment at a certain time (t) + heat storage amount of the heat storage tank at a certain time (t) −heat radiation amount of the heat storage tank at a certain time (t) However, at least one of the heat storage amount of the heat storage tank and the heat dissipation amount of the heat storage tank is 0.
(2) 0 ≦ heat storage amount of heat storage tank at a certain time (t) ≦ maximum heat storage amount per unit time (3) 0 ≦ heat dissipation amount of the heat storage tank at a certain time (t) ≦ maximum heat dissipation amount per unit time (4) 0 The operation plan determination system according to claim 1, wherein ≦ Σ heat storage amount ≦ maximum capacity of the heat storage tank. The objective function in the second mathematical programming is
{(Σ heat source device output ÷ heat source device characteristic coefficient) × energy intensity unit}
The characteristic coefficient of the heat source equipment is
6. The operation plan determination system according to claim 1, wherein the operation plan determination system is calculated by (output of heat source device / input of heat source device). The operation plan determination system according to claim 5 or 6, wherein the energy intensity is one of the heat source equipment operation cost, primary energy conversion amount, supply heat amount, and CO ₂ emission amount.   The operation plan determination according to any one of claims 5 to 7, wherein the characteristic coefficient of the heat source device is obtained based on one of a product specification of the heat source device and a past operation result of the heat source device. system.

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