JP2006325336A - Controller for dispersed energy system, method, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a controller for a dispersed energy system in which an optimum operation plan can be prepared, even when the characteristic change of a device due to air temperature, water temperature or the degradation of the device or the like exists. <P>SOLUTION: A modeling operation plan preparing section 21 prepares an operation plan, based on the modeling operation plan of an energy generating device and an energy storing device which are set in advance. A measurement information storing section 23 internally stores the measured results of the output characteristics of the device which is operated, based on the modeling operation plan. A device characteristic modeling section 24 models the device characteristics, based on the stored output characteristics and stores them in a device characteristic storing section 25. An optimum operation plan preparing section 27 prepares the optimum operation plan, based on the modeled device characteristics and a demand amount which is estimated by a demand amount estimating section 26. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention includes one or more energy generating devices, one or more energy storage devices, one or more energy loads, and each customer's energy generating device and energy connected to a power system. The present invention relates to a distributed energy system control device that creates an operation plan for a storage device.

  As a method for effectively using the energy of the distributed energy system and performing low-cost operation control, there is a “distributed energy system and its control method” described in Patent Document 1.

This is because the control center receives data on the power generation amount of the fuel cell, the energy storage amount of the storage battery, and the power consumption amount of the load from the control device via the communication line, and the generated power value and the received / transmitted power are transmitted to each energy generating device. This is a system for commanding a value and complementarily controlling power supply and demand via a power line between a plurality of distributed energy systems having different daily load characteristics of power demand.
JP 2002-44870 A

  In the conventional distributed energy system described above, when creating an operation plan for each energy generating device, changes in device characteristics due to the effects of seasonal temperature and water temperature, or deterioration of the device over time, etc. are taken into account. Therefore, there was a problem that the created operation plan was not optimized. In addition, when calculating the amount of exhaust heat, the conventional method of calculating the amount of heat from the product of the circulating flow rate of the water circulating through the fuel cell and hot water tank and the temperature is measured with a highly accurate flow meter when the flow rate decreases. Otherwise, an accurate flow rate could not be measured, and there was a problem that the cost would increase if a high-precision flow meter was attached. Further, the fuel flow rate and the amount of exhaust heat are difficult to reach a constant value, and it is necessary to measure or calculate the fuel flow rate and the amount of exhaust heat of the same output for a long time.

  An object of the present invention is to provide a distributed energy system control apparatus and method capable of creating an optimal operation plan even if there is a change in apparatus characteristics due to temperature, water temperature, apparatus deterioration, or the like.

  Another object of the present invention is to provide a distributed energy system control apparatus and method that do not require a high-precision flow meter.

  Still another object of the present invention is to provide a distributed energy system control apparatus and method capable of obtaining a stable fuel flow rate and exhaust heat characteristics.

The distributed energy system controller of the present invention is
A modeling operation plan creation means for creating a modeling operation plan for the energy generation device and the energy storage device set in advance as a modeling operation plan creation target among the energy generation device and the energy storage device,
Output characteristic collecting means for collecting output characteristics of the apparatus operated based on the modeling operation plan;
Output characteristic storage means for storing the output characteristic;
Device characteristic modeling means for modeling a device characteristic based on the stored output characteristic;
Demand amount predicting means for predicting the demand amount of the energy load;
At least one of the energy generation device and the energy storage device in all time zones using a method for solving a combination optimization problem from the modeled device characteristics and the predicted demand amount While the amount of energy supplied from the power system satisfies the energy demand of the energy load, the fuel cost, which is the cost required for the energy generating device to generate energy, and the power out of the generated energy And an optimum operation plan creating means for creating an optimum operation plan so as to minimize the running cost which is the sum of the grid power cost which is the integrated value of the amount bought and sold at the electricity price.

  The distributed energy system control device periodically performs an operation for modeling each device, takes in the latest information on the device characteristics, and creates an operation plan based on the information.

  Moreover, when calculating | requiring the amount of exhaust heat, the amount of heat in a hot water tank is calculated | required from the position and temperature of the temperature sensor with which the hot water tank was equipped. Furthermore, the operation characteristics of the same output for a long time are acquired by creating an operation plan for modeling.

  According to the present invention, the distributed energy control device periodically performs an operation for modeling each device, and operates based on the latest information on the device characteristics that change from time to time due to temperature, water temperature, or device deterioration. By creating a plan, it is possible to optimize the operation plan. Also, when calculating the amount of exhaust heat, instead of obtaining the amount of heat from the product of the circulating flow rate and temperature of the water circulating through the fuel cell and the hot water tank, the heat amount is obtained from the position and temperature of the temperature sensor provided in the hot water tank, There is no need to attach a high-accuracy flow meter to the exhaust pipe, and costs can be reduced. Furthermore, it is possible to acquire stable fuel flow rate and exhaust heat quantity characteristics by acquiring operation characteristics with the same output for a long time by the operation plan for modeling. Can be realized.

  Next, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 shows a configuration of a distributed energy system according to an embodiment of the present invention.

As shown in the figure, this distributed energy system includes a plurality of consumers 1 ₁ , 1 ₂ ,..., 1 _n connected to an electric power system 3, a distributed energy system control device 2, and electric power / gas. It consists of price DB4.

Each consumer 1 ₁ to 1 _n is provided with a fuel cell system 13, a storage battery system 12, and a hot water tank 15 as energy generators, and an electric power load 11 and a heat load 14 as energy loads. The fuel cell system 13 and the storage battery system 12 each include peripheral devices such as auxiliary machines. The fuel cell system 13, the storage battery system 12, and the power load 11 of each consumer 1 ₁ to 1 _n are connected to the power system 3 by a power line 5 indicated by a thin line in the figure, and the fuel cell system 13, the thermal load 14, and the hot water storage. The tanks 15 are connected to each other by a heat pipe 6 indicated by a thick line in the drawing. Here, the number and types of energy generation devices and energy storage devices installed in the consumers 1 ₁ to 1 _n and the modes of accommodation are various. For example, there are consumers who have a plurality of kitchens with energy generators and energy storage devices, and the surplus power can be accommodated, and there are customers who have only a power load or only a heat load.

The distributed energy system control device 2 includes a modeling operation plan creation unit 21, an information collection unit 22, a measurement information storage unit 23, a device characteristic modeling unit 24, a device characteristic storage unit 25, a demand amount prediction unit 26, and an optimum operation plan. A creation unit 27 is provided, which is connected from the information collection unit 22 to each device of each of the consumers 1 ₁ to 1 _n through a communication line 7 indicated by a dotted line in the drawing. The modeling operation plan creation unit 21 creates a modeling operation plan for the energy generator and the energy storage device set in advance as the modeling operation plan creation target. The measurement information storage unit 23 stores therein the measurement results of the output characteristics of the device operated based on the modeling operation plan collected by the information collection unit 22. The device characteristic modeling unit 24 models a device characteristic based on the stored output characteristic and stores it in the device characteristic storage unit 25. The optimum operation plan creation unit 27 uses at least one of the energy generation device and the energy storage device in all time zones by using a method for solving the combined optimization problem from the modeled device characteristics and the predicted demand. On the other hand, the energy supply amount from the power system 3 satisfies the energy demand of the energy load, and the fuel cost, which is a cost required for the energy generating device to generate energy, and the power out of the generated energy The optimum operation plan is created so as to minimize the running cost which is the sum of the grid power cost which is the integrated value of the amount bought and sold at the power price.

  FIG. 2 is a flowchart for explaining the overall operation of the distributed energy system control device 2 shown in FIG. As shown in the figure, each price is first input to the distributed energy system controller 2 from the electric power and gas price DB 4 of the external electric power company and the gas company (step 101). Next, each device characteristic is modeled. The distributed energy system control device 2 first creates a modeling operation plan for the device to be modeled at the modeling operation plan creation unit 21 periodically, and issues an operation command to the modeled device. Perform (step 102). The periodic modeling operation is performed, for example, every season or every month. In addition, this modeling operation plan is suitable for device characteristics such as, for example, accumulating a stable fuel flow rate with the same output for a long time in consideration of the fuel flow rate that fluctuates greatly in a short time even if the output is the same. It is assumed that an operation plan that can be acquired is prepared in advance. The commanded modeling target device operates according to the command, and the measured operation data is received by the information collecting unit 22 of the distributed energy system control device 2 via the communication line 7 and is stored in the measurement information storage unit 23 in the device model. Is stored as operation data for conversion. As a storage method, for example, as shown in the table of FIG. 3, operation data measured for each input item is written in units of one minute. A summary of these input items is shown in FIG. As input items, input power of auxiliary equipment required when the device is started up, output power output from the device, hot water tank temperature measured at every height in the hot water tank and measurement position indicating the measurement point, customer Hot water flow rate to supply hot water, water temperature of tap water, fuel gas flow rate of fuel cell, gas flow rate to supply hot water to consumers, fuel cell start time, output time, stop time, power generation output fluctuation time indicating output fluctuation time, There are storage battery discharge power and charge power. Further, the measured operation data is graphed in the measurement information storage unit 23 like the fuel gas flow rate characteristic of FIG. 5 and the output power characteristic of FIG. 6, and the administrator of the distributed energy system control device 2 can easily make the characteristic. Can grasp. Next, the apparatus characteristic modeling unit 24 models the apparatus characteristic from the measured operation data (step 104). For example, as shown in FIG. 7, the device characteristic modeling unit 24 obtains the power transmission end efficiency ηe from the fuel integrated value Gin and the power integrated value Pout in the time zone output by the fuel cell system 13 using the equation (1). However, in order to match the units when obtaining the efficiency, the calculation is performed after all are converted to the amount of heat (for example, [MJ]).

ηe = Pout / Gin (1)
Similarly, the device characteristics other than the power transmission efficiency are modeled, and the device characteristics of the fuel cell system 13 are stored in the device characteristic storage unit 25. In addition, the modeling method of the hot water storage tank 15 and the storage battery system 12 will be described later. FIG. 8 shows a summary of the device characteristic items modeled in this way. The device characteristic items include the start time required for the energy generator to start up, the amount of start fuel required for start-up, the amount of start-up power required for start-up (including auxiliary power), and the power transmission efficiency, which is the power efficiency of the device Exhaust heat recovery efficiency that is thermal efficiency, power generation fluctuation speed indicating the fluctuation speed of output, hot water supply efficiency of hot water heater, heat dissipation loss of hot water tank, equipment stop time, stop power amount, charge / discharge efficiency of storage battery, storage battery capacity, etc. There is. This device characteristic item is updated whenever a modeling operation is performed periodically (step 105), and when the optimum operation plan of the distributed energy system described later is created, the updated latest information is updated. It is assumed that an optimum operation plan is created based on the device characteristics. When device characteristic information such as factory test data at the time of manufacture is already present at the time of device introduction, a series of procedures for modeling the device characteristics is omitted, and the factory test data is directly stored in the device characteristic storage unit 25. You may enter. Then, predicted in demand prediction unit 26 customer ₁ 1 to 1 _n of the power, the heat load demand (step 106). These are determined by predicted values of demand for power and heat using multiple regression analysis and energy demand prediction methods using neural networks. Based on the predicted electric power and thermal load demand, the optimum operation plan creation unit 27 creates an appropriate initial operation plan (step 107), and performs optimization problems such as genetic algorithms and tabu search from the initial operation plan. Using the solving method, an optimum operation plan of the energy generator is created so that the running cost is minimized in a short time (steps 107 and 108). However, the device selected as the device to be modeled previously is excluded from the creation of the optimum operation plan, and the device to be modeled is operated based on the operation plan for modeling. Create Here, after repeating the prescribed number of calculations, a convergence determination is performed (step 109). If the minimum running cost is not updated for a certain period of time or more, an optimal operation plan is determined as having converged (step 110). ). If the operation plan is determined, the distributed energy system control device 2 issues an output command to each device based on the operation plan (step 111). Here, if it is a periodic device information update cycle such as season or one month (step 112), the modeling operation is performed again for modeling. If it is not the update cycle, the customer's power and thermal load demand are measured (step 113), and the difference between the predicted power and thermal load demand and the predicted demand made earlier is large. (Steps 114 and 115), and an initial operation plan is created again based on the prediction correction information and the apparatus characteristic information.

  Next, a method for modeling the hot water tank 15 will be described. FIG. 9 is a flowchart for obtaining the exhaust heat recovery efficiency from the amount of heat accumulated in the hot water tank 15 and the amount of heat. For example, the hot water storage tank 15 is provided with a plurality of temperature sensors 16 in the hot water storage tank 15 as shown in FIG. 10 or a temperature sensor 17 capable of freely moving in the hot water storage tank 15 as shown in FIG. The temperature sensors 16 and 17 in FIGS. 10 and 11 are configured to transmit the position and temperature information measured in the hot water tank 15 to the distributed energy system control device 2. Here, the temperature and position information before the amount of heat is accumulated in the hot water storage tank 15 are acquired in advance (steps 201 and 202). The amount of heat H in the hot water tank 15 is calculated using equation (2) (step 203). However, the height from the bottom of the hot water tank 15 is p, the temperature difference between the temperature before the heat is accumulated and tap water is f (p), the coefficient for converting the temperature into the heat is α, the bottom of the hot water tank 15 Let the area be A.

H = α × A × ∫f (p) dp (2)
After that, when the fuel cell system 13 is operated and the amount of heat is accumulated in the hot water storage tank 15 (step 204), the internal temperature of the hot water storage tank 15 is determined in the same manner as the method using the equation (2) from the measured position and temperature information again. The amount of heat H ′ is calculated (steps 205 to 207). Here, the heat quantity Hch stored in the hot water tank 15 is calculated from the difference between the heat quantity H before the heat quantity accumulation and the heat quantity H ′ after the heat quantity accumulation using the equation (3) (step 208).

Hch = H−H ′ (3)
Further, the exhaust heat recovery efficiency ηh is calculated using the equation (4) from the heat amount Hch and the accumulated fuel integrated value Gin (step 209).

ηh = Hch / Gin (4)
Here, normally, the exhaust heat recovery efficiency uses equation (5) instead of equation (4). However, Hfl is the circulation flow rate of water circulating in the fuel cell and hot water tank 15, and Tfl is the temperature of the circulation flow rate.

ηh ′ = Hfl × Tfl / Gin (5)
However, when using a method for obtaining the exhaust heat recovery efficiency from the circulation flow rate as in equation (5), the efficiency may not be calculated correctly. For example, when the output of the fuel cell in FIG. 12 is reduced such as 40%, the circulating flow rate Hfl is also reduced. Therefore, accurate measurement is impossible unless the flow meter is highly accurate. Becomes 0. Therefore, if the equation (4) is used instead of the equation (5), the amount of heat is accumulated in the hot water tank 15 even if the circulating flow rate Hfl is lowered, so that the exhaust heat recovery efficiency is obtained without using a highly accurate flow meter. It becomes possible.

  Next, a method for modeling the storage battery system 12 will be described. FIG. 13 shows the storage state of the storage battery. In order to obtain the storage battery capacity, the normal state as in (1) is changed to the complete discharge state as in (2) by periodic modeling operation. Further, after the fully charged state as shown in (3) is completed, the battery is completely discharged again as shown in (4). At this time, the charging / discharging efficiency ηbatt is obtained from the charging power amount Wch charged from (2) to (3) and the discharging power amount Wdis discharged from (3) to (4) using the equation (6). Moreover, let discharge electric energy Wdis discharged from (3) to (4) be storage battery capacity.

ηbatt = Wdis / Wch (6)
As mentioned above, although the example of the apparatus and the example of a method corresponding to this were enumerated and explained about an embodiment of the present invention, the present invention is not necessarily limited only to the above-mentioned method, and has the above-mentioned effect. Changes can be made as appropriate within the range.

  The above-described function of the distributed energy control apparatus 2 is executed by recording a program for realizing the function on a computer-readable recording medium and causing the computer to read the program recorded on the recording medium. You may do. The computer-readable recording medium refers to a recording medium such as a flexible disk, a magneto-optical disk, and a CD-ROM, and a storage device such as a hard disk device built in a computer system. Furthermore, the computer-readable recording medium is a medium that dynamically holds the program for a short time (transmission medium or transmission wave) as in the case of transmitting the program via the Internet, and the computer serving as the server in that case Such as a volatile memory that holds a program for a certain period of time.

1 is a configuration diagram of a distributed energy community system according to an embodiment of the present invention. FIG. It is a flowchart which shows the whole operation | movement of the distributed energy system control apparatus of FIG. It is a figure which shows the example of driving | operation data for modeling an apparatus stored in the measurement information storage part of a distributed energy system control apparatus. It is a figure which shows the input item of FIG. It is a figure which shows the example by which the measured fuel gas flow volume characteristic of the fuel cell was graphed in the measurement information storage part. It is a figure which shows the example by which the measured output power characteristic of the fuel cell was graphed in the measurement information storage part. It is a figure which shows the example which calculates power transmission end efficiency (eta) e in an apparatus characteristic modeling part. It is a figure which shows what put together the apparatus characteristic item modeled in the apparatus characteristic modeling part. It is a flowchart for calculating | requiring exhaust heat recovery efficiency from the calorie | heat amount accumulate | stored in the hot water storage tank, and its calorie | heat amount. It is a figure which shows the structure of the hot water tank which provided the some temperature sensor in the hot water tank. It is a figure which shows the structure of the hot water tank provided with the temperature sensor which can move the inside of a hot water tank freely. It is a figure which shows the waste heat recovery efficiency calculated | required from the hot water storage tank and the circulation flow rate, respectively. It is a figure which shows the electrical storage state of the storage battery for demonstrating modeling of a storage battery system.

Explanation of symbols

1 ₁ to 1 _n Consumer 2 Distributed energy control device 3 Electric power system 4 Electricity and gas price DB
DESCRIPTION OF SYMBOLS 5 Power line 6 Thermal piping 7 Communication line 11 Electric power load 12 Storage battery system 13 Fuel cell system 14 Thermal load 15 Hot water storage tank 16, 17 Temperature sensor 21 Modeling operation plan preparation part 22 Information collection part 23 Measurement information storage part 24 Apparatus characteristic modeling Unit 25 Device characteristic storage unit 26 Demand amount prediction unit 27 Optimal operation plan creation unit 101-115, 201-209 Step

Claims (9)

One or a plurality of energy generation devices, one or a plurality of energy storage devices, one or a plurality of energy loads, and the energy generation device and the energy storage device of each consumer connected to a power system In a distributed energy system controller that creates an operation plan for
A modeling operation plan creation means for creating a modeling operation plan for the energy generation device and the energy storage device set in advance as a modeling operation plan creation target among the energy generation device and the energy storage device;
Output characteristic collecting means for collecting output characteristics of the apparatus operated based on the modeling operation plan;
Output characteristic storage means for storing the output characteristic;
Device characteristic modeling means for modeling a device characteristic based on the stored output characteristic;
Demand amount predicting means for predicting the demand amount of the energy load;
At least one of the energy generation device and the energy storage device in all time zones using a method for solving a combination optimization problem from the modeled device characteristics and the predicted demand amount While the amount of energy supplied from the power system satisfies the energy demand of the energy load, the fuel cost, which is the cost required for the energy generating device to generate energy, and the power out of the generated energy And an optimum operation plan creation means for creating an optimum operation plan so as to minimize a running cost that is the sum of the grid power cost that is an integrated value of the amount bought and sold at a power price of System controller.   The device characteristic modeling means uses the output characteristic data collected by the output characteristic collecting means to start the energy required for starting the energy generating device, the amount of starting fuel required for starting, and Starting power amount that is necessary power amount, power transmission end efficiency that is power efficiency of the energy generator, exhaust heat recovery efficiency, power generation fluctuation speed that is fluctuation speed of output power, hot water supply efficiency, the energy storage device is a hot water storage tank Heat dissipation loss of the hot water storage tank in some cases, stop time required for the energy generator to stop, stop power amount that is the amount of power required to stop, charge / discharge efficiency when the energy storage device is a storage battery, At least one device characteristic of the capacity of the storage battery is modeled based on a preset input formula, and the optimum operation plan creating means is modeled before Used while updating the information of the device characteristics at any time, distributed energy system control device according to claim 1.   The optimum operation plan creation means is the energy generation device for which the modeling operation plan has already been created by the modeling operation plan creation means, and the optimum operation plan creation by the optimum operation plan creation means for the energy storage device 2. The distributed energy system control device according to claim 1, wherein the device is operated as a non-target device based on the modeling operation plan, and the optimum operation plan of the remaining energy generation device and the energy storage device is created.   When the energy storage device is a hot water storage tank, the hot water storage tank is provided with a temperature sensor, and the device characteristic modeling means calculates the amount of heat of the hot water storage tank from the temperature of the temperature sensor and position information in the hot water storage tank. The distributed energy system control device according to claim 1.   The distributed energy system control device according to claim 4, wherein a plurality of the temperature sensors are installed in the hot water storage tank.   The distributed energy system control device according to claim 4, wherein the temperature sensor is movable and can move in the hot water storage tank.   The distributed energy system control device according to claim 4, wherein in the hot water storage tank, exhaust heat recovery efficiency is calculated from a difference heat quantity before and after the heat quantity accumulation. One or a plurality of energy generation devices, one or a plurality of energy storage devices, one or a plurality of energy loads, and the energy generation device and the energy storage device of each consumer connected to a power system In a distributed energy system control method for creating an operation plan for
A modeling operation plan creation step of creating an operation plan for modeling the energy generation device and the energy storage device set in advance as a modeling operation plan creation target among the energy generation device and the energy storage device;
An output characteristic collecting step for collecting output characteristics of a device operated based on the modeling operation plan;
An output characteristic storage step of storing the output characteristic in a storage device;
A device characteristic modeling step for modeling a device characteristic based on the stored output characteristic;
A demand amount prediction step for predicting a demand amount of the energy load;
At least one of the energy generation device and the energy storage device in all time zones using a method for solving a combinational optimization problem from the modeled device characteristics and the predicted demand. And the amount of energy supplied from the power system satisfies the energy demand of the energy load, and the fuel cost, which is the cost required for the energy generating device to generate energy, and the electric power out of the generated energy An optimal operation plan creation step for creating an optimal operation plan so as to minimize a running cost that is the sum of the grid power cost, which is an integrated value of the amount bought and sold at the power price of the power system. Type energy system control method.   A program for causing a computer to operate as the distributed energy system control device according to any one of claims 1 to 4 and 7.

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