JP2009240080A - Device and method for preparing operation plan of energy system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To prepare an optimal operation plan of an energy system in which energy is supplied to a load by being equipped with an energy generation device and an energy accumulation device without falling into a local solution. <P>SOLUTION: A device 10 for preparing the operation plan includes: a data accumulation section 17 that accumulates past data measured in the energy system; a prediction calculation section 12 that calculates prediction values of the amount of generated energy and the amount of the load based on information given from the outside and past measurement data; an evaluation function calculation section 13 that calculates an evaluation value of the operation plan by using the model via an evaluation function after modeling the energy generation device and the energy accumulation device; an optimal operation plan searching section 14 that searches the operation plan such that the evaluation value becomes optimal; and a model parameter adjustment section 15 that adjusts a parameter in the model of the evaluation function calculation section 13 according to the researched result in the optimal operation plan searching section 14. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an apparatus and method for creating an operation plan of an energy system for supplying energy.

  Provide one or a plurality of energy generators such as solar cells and fuel cells and one or a plurality of energy storage devices such as a storage battery and a heat storage device to provide energy to one or a plurality of energy loads in the form of electric power or heat. There is an energy system as a system that can be supplied. Such an energy system is called a microgrid and is attracting attention as a means of realizing a distributed energy source, and it uses electric power from a power system (commercial power supply) and various types of thermal energy generated in the energy system. By supplying energy to the load in combination, high energy efficiency is achieved, and energy is supplied to each load at low cost and stably. The energy system stably supplies energy such as electric power and heat to the load while using natural energy with large fluctuations without suppressing fluctuations in the electric power supplied from the electric power system and affecting the grid. Such an energy system also has an advantage that energy can be supplied to the load even when the system power supply is lost (at the time of power failure).

  When operating an energy system equipped with multiple energy generators and multiple energy storage devices, predict fluctuations in the load due to weather, time of day, etc. and fluctuations in the amount of energy generated in each energy generator in advance. It is desirable to establish an operation plan. Patent Document 1 (Japanese Patent Application Laid-Open No. 2005-130550: Distributed Energy System Operation Plan Creation Device and Creation Method) discloses energy storage as a method for creating operation plans for a plurality of energy generation devices and a plurality of energy storage devices. And a method of determining an operation plan so as to minimize the running cost in consideration of the balance of discharge and the like.

Metaheuristic methods such as tabu search and genetic algorithms are effective methods for determining a plan for realizing such minimization, that is, for solving an optimization problem. The meta-heuristic method can be used for power generation planning and so on because it can obtain a high-precision approximate solution of the global optimal solution at a relatively high speed without depending on the function form of the optimization target ( (Refer nonpatent literature 1).
JP 2005-130550 A Akira Takeuchi, Mitsuru Kudo, Akira Nakazawa, Hisahi Endo, “Optimum Control Technology for Energy Network”, NTT Technical Journal, Vol. 18, No. 1, pp. 29-32, January 2006

  However, when creating an operation plan of an energy system by the above-described conventional method, for example, the power supply amount (amount of power purchased) from the power system is desired to be constant or desired according to the time zone in order to minimize the influence on the system. For energy generators that are concerned about the effects of fluctuations in output, such as fuel cells, on the life of the battery, make the amount of energy generated as smooth as possible, or charge a storage device that is one of the energy storage devices. If you try to create an operation plan under various complicated constraints such as considering discharge amount constraints and charge / discharge balance, the evaluation function and constraints used to solve the optimization problem will not be smooth. , Easy to fall into a local solution. That is, in the conventional method, there is a problem that the operation plan created under complicated constraints is not likely to be optimal globally.

  An object of the present invention is to apply an evaluation function creation method and an optimal search method that can smooth an evaluation function and a search space, even when considering various constraints as described above. It is to provide an operation plan creation device that realizes a realistic search and creates an operation plan of an energy system.

  Another object of the present invention is to propose an evaluation function creation method and an optimal search method that can smooth an evaluation function and a search space, even when considering the above various constraints. Another object of the present invention is to provide an operation plan creation method capable of creating an operation plan of an energy system by realizing a global search.

  An energy system operation plan creation device of the present invention is an operation plan creation device that creates an operation plan of an energy system that supplies energy, and is provided from the outside with a data accumulation unit that accumulates past measurement data in the energy system. Based on the measured information and past measurement data, a prediction calculation unit that calculates predicted values of energy generation amount and load amount, and modeling of energy generation and energy storage in the energy system, and using the model by an evaluation function The function in the model is adjusted according to the search results in the evaluation function calculation unit that calculates the evaluation value, the optimum operation plan search unit that searches for the operation plan that optimizes the evaluation value, and the optimum operation plan search unit A model parameter adjustment unit.

  In the above-described apparatus, the optimum operation plan search unit creates an operation plan as an initial operation plan, and in order to search for the optimum operation plan, the created operation plan is repeatedly corrected, and the model parameter adjustment unit The optimal operation plan search unit may search for an operation plan that optimizes the evaluation value by the optimal operation plan search unit correcting the operation plan while changing the parameters.

  In the apparatus of the present invention, the model parameter adjustment unit relates to an item for which an upper limit value and / or a lower limit value is specified in the model, and the value of the item is determined from the upper limit value and / or the lower limit value specified for the item. In the case of deviating, the adjustment coefficient to be multiplied by the item or its upper limit value and / or lower limit value may be adjusted. In this case, the evaluation function calculation unit multiplies the adjustment rate corresponding to the upper limit value of the output change rate by the change rate of the energy generation amount required for the energy generation device in the energy system. In a time period larger than the change rate, the evaluation value may be calculated on the assumption that the output change rate is a constraint condition or that the energy generation efficiency is reduced according to the excess amount of the change rate. . Furthermore, the evaluation function calculation unit is an amount that exceeds the upper limit value or falls below the lower limit value in the time zone in which the energy storage speed in the energy storage device in the energy system exceeds the upper limit value or lower than the lower limit value. Assuming that the accumulation rate is lower than the actual model or the release rate is larger than the actual model using the adjustment factor according to the time, the energy release rate in the energy storage device exceeds the upper limit value of the release rate or falls below the lower limit value. The amount of energy stored in the energy storage device is assumed to be higher than the actual model by using an adjustment factor according to the amount exceeding the upper limit value or below the lower limit value. Assuming that the accumulation rate is limited in the time period exceeding, the amount of time the accumulated amount falls below the lower limit of the accumulated amount Assuming the release rate is greater than the actual model in, may calculate the evaluation value.

  The energy system operation plan creation method of the present invention is an operation plan creation method for creating an operation plan of an energy system that supplies energy, based on information given from the outside and past measurement data in the energy system, A predicted value calculating step for calculating a predicted value of energy generation amount and load amount; an evaluation value calculating step for modeling energy generation and energy storage in an energy system and calculating an evaluation value of an operation plan using the model by an evaluation function; And a search step for searching for an operation plan in which the evaluation value is optimal, and an adjustment step for adjusting a parameter in the model according to a search result in the optimal operation plan search unit.

  In the above-described method, the search step is constituted by the initial operation plan creation step for creating the operation plan to be the initial operation plan and the correction step for repeatedly correcting the created operation plan, and the correction step is performed while changing the adjustment coefficient. By repeating the above, an operation plan that optimizes the evaluation value may be searched.

  In the method of the present invention, in the adjustment step, regarding an item for which an upper limit value and / or a lower limit value are defined in the model, the value of the item deviates from the upper limit value and / or the lower limit value defined for the item. In this case, an adjustment coefficient to be multiplied by the item or its upper limit value and / or lower limit value may be adjusted. In that case, in the evaluation value calculation step, the change rate of the energy generation amount required for the energy generator in the energy system is multiplied by the adjustment coefficient corresponding to the upper limit value of the output change rate in the energy generator. In a time period larger than the change rate, the evaluation value may be calculated on the assumption that the output change rate is a constraint condition or that the energy generation efficiency is lowered according to the excess amount of the change rate. Further, in the step of calculating the evaluation value, the energy storage speed in the energy storage device in the energy system exceeds the upper limit value or falls below the lower limit value in a time zone in which the energy storage speed exceeds the upper limit value or falls below the lower limit value. Assuming that the accumulation rate is lower than the actual model or the release rate is higher than the actual model using an adjustment factor according to the amount of energy, the time when the energy release rate in the energy storage device exceeds the upper limit value or falls below the lower limit value In the band, it is assumed that the release rate is higher than the actual model by using an adjustment factor according to the amount exceeding the upper limit value or below the lower limit value, and the energy storage amount in the energy storage device is Assuming that the accumulation speed is limited in the time zone exceeding the upper limit, the accumulated amount is below the accumulated amount. Assuming the release rate is greater than the actual model in the time period below a value, it may be calculated evaluation value.

  The present invention, for example, can be applied globally without falling into a local solution under the condition that the time variation of the output amount of the power generation device, which is an energy generating device, is suppressed as much as possible, and in consideration of various constraint conditions of the power storage device. There is an effect that an optimal operation plan can be created.

  Next, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a diagram illustrating a configuration of an operation plan creation device according to an embodiment of the present invention. An example of a configuration of an energy system in which an operation plan is created by the operation plan creation device 10 together with the operation plan creation device 10. Is shown.

  First, the basic configuration of the operation plan creation device 10 will be described. The operation plan creation device 10 creates an operation plan for an energy system. The operation plan creation device 10 has an input unit 11 for inputting information related to weather forecasts or the like by means of communication or the like, and an energy generation device based on the information input to the input unit 11. A prediction calculation unit 12 for calculating a predicted value of energy generation amount and energy demand at energy load, a prediction value supplied from the prediction calculation unit 12, and modeling the energy generation device and the energy storage device. The evaluation function calculation unit 13 that calculates the evaluation value of the degree of achievement of the control objective using the optimal operation plan search unit 14 that searches for an operation plan that optimizes the evaluation value calculated by the evaluation function calculation unit 13 And a model for adjusting the parameters of the model used in the evaluation function calculation unit 13 based on the signal from the optimum operation plan search unit 14. It includes a le parameter adjuster 15. The prediction calculation unit 12 may calculate a prediction value based on past prediction data in addition to the information input to the input unit 11. For this purpose, the operation plan creation apparatus 10 stores data that accumulates past prediction data. A storage unit 16 is provided.

  In the model used in the evaluation function calculation unit 13, for example, the upper limit value of the energy output amount in the energy generation device, the upper limit value of the change rate of the energy output amount, the energy accumulation rate, the release rate, and the upper limit of the accumulation amount in the energy storage device The value and the lower limit value, the storage rate or the release rate required for the energy storage device when the energy storage device deviates from the range of the upper limit value and the lower limit value, and the like are defined. The accumulation rate and the release rate in the energy storage device respectively indicate how much energy is stored in the energy storage device or released from the energy storage device per unit time. If the energy storage device is a storage battery, the storage speed corresponds to the charging power (or charging current under the condition that the charging voltage is constant), and the discharging speed is the condition that the discharging power (or discharge voltage is constant). Discharge current). The accumulated amount indicates the amount of energy that is actually accumulated in the energy storage device, and corresponds to a value obtained by integrating the accumulation rate and the discharge rate. Corresponds to the quantity.

  The model parameter adjustment unit 15 adjusts, for example, an adjustment coefficient for the upper limit value of the change rate of the energy output amount, and an adjustment coefficient for the accumulation speed and the release speed obtained by the energy storage device when the energy output amount deviates from the upper and lower limits. These adjustment factors are multiplied by corresponding amounts or upper and lower limits in the model.

  The optimum operation plan search unit 14 repeats an initial operation plan creation step for creating an initial operation plan using past operation plan data and an initial operation plan when searching for an operation plan with an optimum evaluation value. An operation plan correcting step for correcting and searching for an optimal operation plan is executed. In the operation plan correction step, the evaluation function calculation unit 13 repeatedly calculates the evaluation value while changing the adjustment coefficient by the model parameter adjustment unit 15, and the optimal operation plan is searched by this repetition. It is preferable to use tabu search for searching for the optimum operation plan. When using tabu search, add a term formulated so that the evaluation value becomes worse when the adjustment factor is exceeded, or add it to the function for neighborhood evaluation of tabu search, or Accordingly, when the evaluation value becomes worse than a predetermined value, it is stored in the tabu list and the movement is prohibited for a certain period, so that the operation plan correction step is repeated while selecting the variable to be corrected to determine the operation plan.

  In such an operation plan creation device 10, the change in energy output amount after the amount of fluctuation in the energy amount required for the energy output device for energy storage in the load or energy storage device is multiplied by the adjustment factor. For time periods that exceed the upper limit value of the speed, the evaluation function calculation unit 13 assumes the output change speed as a constraint condition, or the energy generation efficiency decreases according to the excess of the output change speed from the upper limit value. Assuming that, the evaluation value may be calculated. In addition, when the energy accumulation rate in the energy storage device deviates from the range of the upper limit value and the lower limit value, the evaluation function calculation unit 13 adjusts according to the amount exceeding the upper limit value or the amount falling below the lower limit value. Assuming that the accumulation rate is smaller than the actual model or the release rate is larger than the actual model using a coefficient, and if the release rate deviates from the upper and lower limit range, similarly, use the adjustment coefficient according to the deviation amount from the actual model. Assuming that the release rate increases, the accumulation rate is assumed to be limited in the time zone when the accumulation amount exceeds the upper limit value, and the release rate becomes larger than the actual model in the time zone when the accumulation amount falls below the lower limit value. Assuming that the evaluation value may be calculated.

  Since the predicted value calculated by the prediction calculation unit 12 may be different from the actual value thereafter, the operation plan creation device 10 is provided with a predetermined reserve so that energy can be supplied even when such an error occurs. Create an operation plan to ensure the power. However, since it is possible that a predetermined reserve capacity cannot be secured depending on the time zone, for such a time zone, the evaluation function calculator 13 stores the energy storage device according to the insufficient reserve capacity. The evaluation value may be calculated by adjusting the upper limit value and the lower limit value of the speed and the release speed.

  Next, the operation plan creation apparatus 10 of the present embodiment will be described in more detail by taking as an example the case of creating an operation plan for the energy system shown in FIG.

  First, the configuration of the exemplified energy system will be described. The energy system is supplied with power from the power system 20 via the power line 21 and includes a plurality of energy generation devices and a plurality of energy storage devices, and supplies energy to the energy load. In this example, a solar cell 31 and fuel cells 32 and 33 are provided as energy generation devices, a storage battery 34 and a heat storage device 35 are provided as energy storage devices, and a power load 36 and a heat load 37 are provided as energy loads. Yes. The solar cell 31, the fuel cells 32 and 33, the storage battery 34, and the power load 36 are connected to the power line 31. For the power load 36, the power purchased from the power system 20 and the solar cell 31 and the fuel cells 32 and 33 are used. The generated electric power is supplied directly or once after being stored in the storage battery 34 according to the operation plan. In addition, a heat pipe 38 is provided to collect the exhaust heat from the fuel cell 32 and supply it to the heat load 37, and the heat pipe 38 temporarily stores the collected heat in the heat pipe 38. Is also connected.

  Between such an energy system and the operation plan creation device 10, an energy control device 25 is provided. The energy control device 25 controls means for controlling the fuel cells 32 and 33 and the storage battery 34, and means for collecting measurement data relating to past power load / heat load and input / output during operation of the fuel cell or storage battery as required. It has. In order to control the fuel cells 32, 33 and the storage battery 34 and acquire measurement data from each energy generation device, each energy storage device and each energy load, the energy control device 25 is connected to the mode battery 31, The fuel cells 32 and 33, the storage battery 34, the heat storage device 35, the power load 36 and the heat load 37 are connected.

  Here, with respect to the solar cell 31, the operation plan is applied only to the fuel cells 32 and 33 as to accept the change in the power generation amount according to the weather and the time zone without controlling the power generation amount. Shall be created. In preparing the operation plan, not only the power load 36 but also the heat load 37 is considered.

Therefore, assuming the energy system shown in FIG. 1, in the operation plan creation device 10, the prediction calculation unit 12 generates the power generation amount of the solar cell 31 based on information such as weather information input via the input unit 11. Prediction is performed, and demand prediction for the power load 36 and the heat load 37 is performed. For this prediction, past measurement data stored in the data storage unit 16 may be used. Measurement data in the energy system is input to the data storage unit 16 via the energy control device 25. The prediction result in the prediction calculation unit 12 is sent to the evaluation function calculation unit 13. The evaluation function calculation unit 13 calculates an evaluation value based on the models of the fuel cells 32 and 33 and the storage battery 34 based on the prediction result in the prediction calculation unit 12. In these models, the input / output function of the actual model may be updated as necessary using past input / output data of the fuel cell or storage battery (stored in the data storage unit 16). As an example of the evaluation function, the energy cost of the entire system in a predetermined period such as one day or one week, the carbon dioxide (CO ₂ ) emission amount emitted from the entire system, etc. can be considered. The operation plan that minimizes the volume is the optimal operation plan. Energy basic unit information is also given to the input unit 11 for calculating energy costs and the like.

  The optimum operation plan search unit 14 causes the evaluation function calculation unit 13 to repeatedly execute this evaluation function calculation, and finds an operation plan having the optimum evaluation value. At that time, the search is performed while changing various adjustment coefficients of the fuel cell and the storage battery model via the model parameter adjustment unit 15. As an adjustment factor, the upper limit value of the output fluctuation of the fuel cell is assumed to be slower than the actual model, when the charge / discharge power of the storage battery and the accumulated value, which is the accumulated value, exceed the upper limit value or below the lower limit value. In such a case, there is a case for assuming a change in the amount of stored electricity.

  FIG. 2 is a flowchart showing an outline of the operation plan creation processing in the optimum operation plan creation device 10.

  First, in step 41, information such as weather forecast is received by the input unit 11, and in step 42, the prediction calculation unit 12 receives the received information such as weather forecast and past measurement data stored in the data storage unit 16. Is used to calculate the demand for power load and heat load and the predicted value of solar cell power generation. Next, in step 43, the optimum operation plan search unit 14 creates an initial operation plan to be evaluated first, and in step 44, the model parameter adjustment unit 15 performs initial setting of various adjustment coefficients.

  Thereafter, in step 45, the evaluation function calculation unit 13 performs an optimum evaluation of the entire system in a predetermined period. At that time, past measurement data stored in the data storage unit 16 may be used as necessary. In step 46, it is determined whether or not the evaluation value satisfies the end condition. If the end condition is not satisfied, the optimized operation search unit 14 adjusts / changes the operation plan by the optimization method in step 48. In step 49, the model parameter adjusting unit 15 changes various adjustment coefficients as necessary, and these processes are repeated until the end condition is satisfied in step 46. In step 48, when the tabu search is used as the optimization method, the operation plan is changed and adjusted using the neighborhood evaluation / taboo list. If the end condition is satisfied in step 46, in step 47, the optimum operation plan search unit 14 selects an operation plan having the best evaluation value in the evaluation function calculation unit 13 from the operation plans evaluated so far. To do.

  For the search of the operation plan and the setting of the termination condition, methods based on various optimization methods can be used in addition to a metaheuristic method represented by tabu search and a genetic algorithm. Tabu search uses a memory to avoid returning to an already evaluated solution for a predetermined number of iterations and stores it in a memory called a tabu list so that it does not go around the same operation plan and It aims at the direction with the best evaluation value by evaluation. The genetic algorithm calculates fitness based on an evaluation function for multiple operation plans, and then performs operations called genetic operators consisting of selection, crossover, and mutation to create a probabilistic operation plan probabilistically. This is a priority.

  A method of using the evaluation function modified by the adjustment coefficient other than the evaluation function calculation unit 13 when the tabu search is applied to the search by the optimum operation plan search unit 14 will be described.

  One example is to add a term formulated so that the evaluation value becomes worse when the adjustment factor is exceeded, to a function for neighborhood evaluation of tabu search. When the neighborhood evaluation is evaluated with a function equal to the decrease value of the evaluation value in the evaluation function calculation unit 13, the result is the same as when the adjustment coefficient is added to the evaluation function, but the calculation amount of the evaluation function is large and approximate. In the case where the neighborhood is evaluated by a function, the present invention can be executed efficiently.

  Another example of use in tabu search is a method of storing an evaluation value in a tabu list when an evaluation value becomes worse than a predetermined value in response to an excess regarding an adjustment coefficient. The normal taboo list prohibits the transition to an operation plan similar to that evaluated in the near past, but in this example, the operation plan is a feature that you want to avoid as much as possible, such as an increase in the output of the fuel cell. By prohibiting the movement for a certain period of time, it is possible to preferentially search for an operation plan that does not increase the characteristics desired to be avoided. Setting to the tabu list can be performed at a predetermined timing at the start of the search, at the time of erasing the tabu list frequently used in the tabu search, or at other times during the search.

  Next, an effect of adjusting various adjustment coefficients in the present embodiment and an example of setting the adjustment coefficient will be described.

  FIG. 3 shows an example in which the optimum operation plan is improved by the adjustment coefficient for the upper limit value of the output change rate of the fuel cell. In general, there are many power generation operation plans in which the value of the evaluation function is almost the same if the correction by the adjustment factor is not taken into account, and considering that the evaluation function value includes an error, the evaluation is equivalent to these operation plans. Will do. The operation plans shown in (a) and (b) of FIG. 3 are evaluations that are equal as evaluation function values for the purpose of minimizing carbon dioxide emissions and the like, and are solutions for optimization problems that do not consider corrections by adjustment factors. There is no superiority or inferiority. However, by using the adjustment coefficient shown in the present embodiment, as shown in (b), it is possible to create an optimum operation plan that takes into account the constraint that the change in the output of the fuel cell is to be suppressed as much as possible.

  FIG. 4 shows an example of a calculated value of the power generation efficiency corresponding to the output change rate of the fuel cell model as the power generation device. As shown in the figure, smoothly in the range between the upper limit value of the output change rate in the actual model of the fuel cell shown on the horizontal axis and the upper limit value obtained by multiplying the adjustment coefficient in the model used in the evaluation function calculation unit 13. It is effective to change the power generation efficiency. Along with this adjustment coefficient, the slope of the power generation efficiency change may be used as the adjustment coefficient. Even in the actual model, even if the efficiency characteristic does not change much, the output fluctuation of the fuel cell may affect the life of the fuel cell. However, since it is difficult to quantify the influence on the lifetime and accurately reflect it in the evaluation function, virtual modeling of the decrease in efficiency is an effective method for creating the optimum operation plan.

  Next, the effect obtained by searching the optimum operation plan search unit 14 while changing the adjustment coefficient of the output change rate upper limit value of the fuel cell from the initial stage to the final stage of the search will be described.

  When there is an optimal solution with an operation pattern that is significantly different from the initial solution, the variation of the fuel cell was ultimately suppressed while searching for various patterns by allowing the variation of the fuel cell in the initial optimal search. An operation plan can be created. That is, not only a local search but also a global optimum operation plan can be searched and created.

  On the other hand, for example, when there is an operation pattern in which the evaluation value of the entire system improves by making a large output change only at a specific time when the predicted power changes suddenly, the search is performed so as to allow fuel cell fluctuations at the end of the search. By doing so, it is possible to create a better optimum operation plan while suppressing the burden on the output fluctuation of the fuel cell.

  In general, the upper limit value must always be observed for the energy storage rate and discharge rate of the storage battery, that is, the charge / discharge power. However, deviation from the lower limit value is allowed, but if the lower limit value is exceeded, the charge / discharge efficiency May decrease. Such charge / discharge efficiency characteristics are difficult to formulate, and are complicated, and thus impose a burden on optimization calculations. FIG. 5 shows an example in which the optimum operation plan is improved by the adjustment coefficient related to the lower limit value of the charge / discharge power of the storage battery. As shown in FIG. 5 (a), when an optimum operation plan is created without providing a restriction on the lower limit value of the charge / discharge power, the operation plan includes a period for performing a small amount of charge / discharge and repeats charge / discharge. On the other hand, by setting an adjustment coefficient relating to the lower limit value of charging / discharging, they can be avoided as shown in FIG.

  On the other hand, if an optimal operation plan is created with a constraint on the lower limit value of charge / discharge power, the search space becomes unsmooth because the switch from the charge state to the discharge state passes through the infeasible solution, and Escape becomes difficult. Therefore, there is a need for an evaluation function that allows deviations from charging and discharging power restrictions, or a search method that adjusts temporary allowance.

  In FIG. 6, an example of the calculated value of the storage amount increment corresponding to the charge / discharge power of the storage battery model in the evaluation function calculation unit 13 is shown. As in the example shown in the figure, when the charge / discharge power falls below the lower limit, it is assumed that it is less than the increase in the storage amount in the actual model or more than the decrease in the storage amount. Formulate so that the difference between the model and the evaluation function model is large. Even when the upper limit value of the charge / discharge power is exceeded, the formulation is similarly formulated so that the increment of the charged amount decreases according to the excess amount and the decrease of the charged amount increases. By formulating in this way, the optimum operation plan search unit 14 can easily escape even when the operation plan being searched enters the restricted region. The above adjustment coefficient, that is, the slope in FIG. 6, needs to be adjusted so that the operation plan selected as optimal does not include the restricted region, and is the optimum operation as with the output change rate adjustment coefficient in the power generation apparatus. By changing during the plan search, it can be adjusted so as not to fall into a local solution.

  When an operation plan is created, reserve power may be taken into consideration in order to supply energy even when an error occurs in demand prediction or power generation prediction. In this case, in a time zone in which reserve capacity cannot be secured, an operation plan can be created based on the present embodiment by adjusting the upper and lower limit values of charge / discharge power in the storage battery according to the insufficient reserve capacity. it can.

  The storage battery also has a constraint on the upper and lower limits of the amount of electricity stored. For example, it is assumed that the amount of stored electricity does not accumulate any more during the time period that exceeds the upper limit value, and that the accumulated amount is released more than the actual model during the time period when the accumulated amount is less than the lower limit value. By adding the model, it is possible to handle the storage battery constraints uniformly.

  In this way, by uniformly reflecting the constraints on storage battery and reserve capacity in the virtual increase / decrease in storage battery storage capacity, if the storage battery storage capacity is treated in a dimensionless manner as a percentage of its maximum rating, the capacity of the energy system Regardless of the control purpose such as scale, environment, economy, etc., the adjustment amount and method of various adjustment coefficients can be applied for general purposes.

  In the embodiment described above, the procedure for creating the optimum operation plan based on the present invention, the method for applying to the optimum search algorithm, and the modeling of the fuel cell and the storage battery are shown, but the present invention is not limited to these. Instead, various adjustment factors can be selected and the adjustment methods in the optimum algorithm can be combined.

It is a block diagram which shows the structure of the operation plan creation apparatus of one Embodiment of this invention. It is a flowchart which shows the process which produces an operation plan preparation. It is a figure explaining that an optimal driving | operation plan is improved with the adjustment coefficient of the output change speed upper limit of a fuel cell model. It is a graph which shows an example of the calculated value of the power generation efficiency corresponding to the output change speed of the fuel cell model in an evaluation function calculating part. It is a figure explaining that an optimal driving | operation plan is improved with the adjustment coefficient of the charging / discharging electric power lower limit of a storage battery model. It is a graph which shows an example of the calculation value of the storage amount increment corresponding to the charging / discharging electric power of the storage battery model in an evaluation function calculating part.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 Operation plan preparation apparatus 11 Input part 12 Prediction calculation part 13 Evaluation function calculation part 14 Optimal operation plan search part 15 Model parameter adjustment part 16 Data storage part 20 Power system 21 Power line 25 Energy control apparatus 26 Communication line 31 Solar cell 32, 33 Fuel cell 34 Storage battery 35 Heat storage device 36 Electric power load 37 Thermal load 38 Thermal piping 41-49 steps

Claims (10)

An operation plan creation device for creating an operation plan of an energy system for supplying energy,
A data storage unit for storing past measurement data in the energy system;
Based on information given from the outside and the past measurement data, a prediction calculation unit that calculates predicted values of energy generation amount and load amount,
Modeling energy generation and energy storage in the energy system, and using an evaluation function to calculate an evaluation value of an operation plan using the model,
An optimal operation plan search unit that searches for an operation plan that optimizes the evaluation value;
According to the search result in the optimum operation plan search unit, a model parameter adjustment unit that adjusts parameters in the model,
An energy system operation plan creation device comprising: The optimal operation plan search unit creates an operation plan to be an initial operation plan, and repeatedly corrects the operation plan to search for an optimal operation plan,
The optimum operation plan search unit searches for an operation plan that optimizes the evaluation value by the optimum operation plan search unit correcting the operation plan while the model parameter adjustment unit changes the parameter. The energy system operation plan creation device according to claim 1.   The model parameter adjustment unit relates to an item for which an upper limit value and / or a lower limit value is defined in the model, and the value of the item deviates from the upper limit value and / or the lower limit value defined for the item The energy system operation plan creation apparatus according to claim 1 or 2, wherein an adjustment coefficient to be multiplied by the item or the upper limit value and / or the lower limit value is adjusted.   The evaluation function calculation unit is obtained by multiplying the change rate of the energy generation amount required for the energy generation device in the energy system by an adjustment coefficient corresponding to the upper limit value of the output change rate in the energy generation device. 4. The evaluation value is calculated by assuming that the output change rate is a constraint condition in a time zone larger than the change rate, or assuming that the energy generation efficiency is lowered according to an excess amount of the change rate. The energy system operation plan creation device described in 1.   The evaluation function calculation unit is an amount that exceeds the upper limit value or falls below the lower limit value in a time zone in which the energy storage speed in the energy storage device in the energy system exceeds the upper limit value or lower than the lower limit value of the storage speed. Assuming that the accumulation rate is smaller or larger than the actual model using an adjustment coefficient according to the time, the energy release rate in the energy storage device exceeds the upper limit value of the release rate or falls below the lower limit value. Then, it is assumed that the release rate is larger than the actual model by using an adjustment coefficient according to the amount exceeding the upper limit value or less than the lower limit value, and the amount of energy stored in the energy storage device is the amount stored. Assuming that the accumulation speed is limited in a time zone exceeding the upper limit value of Assuming the release rate is greater than the actual model in the time period is below the lower limit value, calculates the evaluation value, the energy system operation plan creation device according to claim 3 or 4. An operation plan creation method for creating an operation plan of an energy system for supplying energy,
Calculating predicted values of energy generation amount and load amount based on information given from outside and past measurement data in the energy system;
Modeling energy generation and energy storage in the energy system, and calculating an evaluation value of an operation plan using the model by an evaluation function;
Searching for an operation plan that optimizes the evaluation value;
Adjusting the parameters in the model according to the search result in the optimum operation plan search unit;
A method for creating an energy system operation plan.   The step of searching includes a step of creating an operation plan to be an initial operation plan, and a step of repeatedly correcting the operation plan, and the evaluation value is obtained by repeating the step of correcting while changing the parameter. The method for creating an energy system operation plan according to claim 6, wherein an operation plan that optimizes the energy system is searched.   The step of adjusting the parameter is related to an item for which an upper limit value and / or a lower limit value is specified in the model, and the value of the item deviates from the upper limit value and / or the lower limit value specified for the item. The energy system operation plan creation method according to claim 6 or 7, wherein an adjustment coefficient to be multiplied by the item or the upper limit value and / or the lower limit value is adjusted.   In the calculating step, the change rate of the energy generation amount required for the energy generating device in the energy system is a change obtained by multiplying the upper limit value of the output change rate in the energy generating device by a corresponding adjustment coefficient. 9. The evaluation value is calculated by assuming that the output change speed is a constraint condition in a time zone larger than the speed, or assuming that the energy generation efficiency decreases according to an excess amount of the change speed. The energy system operation plan creation method described.   In the calculating step, the amount of energy stored in the energy storage device in the energy system exceeds the upper limit value or falls below the lower limit value in a time zone in which the energy storage speed exceeds the upper limit value of the storage system or falls below the lower limit value. Assuming that the accumulation rate is smaller or larger than the actual model using the corresponding adjustment factor, the energy release rate in the energy storage device exceeds the upper limit value of the release rate or falls below the lower limit value. Assuming that the release rate is larger than the actual model using an adjustment coefficient according to the amount exceeding the upper limit value or falling below the lower limit value, the amount of energy stored in the energy storage device is Assuming that the accumulation rate is limited during the time period exceeding the upper limit, the accumulation amount is In a time zone is below the lower limit value of the accumulated amount on the assumption that the release rate is greater than the actual model, calculates the evaluation value, the energy system operation plan creating method according to claim 8 or 9.

Images