JP2005287252A - Method, device, and program for preparing optimum procurement plan for system operator - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To determine the economically optimum amount of procurement even when a procurement cost provided by a concave function is included, and an operation pattern regarding start stop for a generator is restricted. <P>SOLUTION: The procurement amount is determined so that the procurement cost may become minimum by sequentially performing a liner approximating process (S704) which approximates the procurement cost to the simply increasing concave function by a linear function based on procurement source data and demand data stored in a memory means at the preset and prescribed time or each prescribed cycle (YES for S703) when the specified relative trade of the procurement cost provided by a function including the simply increasing concave function exists, and a procurement amount calculating process (S705) which calculates the procurement amount from the respective procurement sources by using a Lagrange's relaxation method based on the procurement cost of the obtained linear function. The procurement amount is checked if the obtained procurement amount satisfies an operation restriction of a transmission line or not, and a procurement amount calculation process (S706) for each area is performed when the operation restriction is not observed. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  In the present invention, when a system operator procures electric power from a plurality of suppliers with different properties and supplies it to a customer's load, the procurement amount from each supplier is determined to be economically optimal. The present invention relates to a method and apparatus for creating an optimum procurement plan.

  With the recent liberalization of the electric power market, the grid operator has become a supplier of electric power, such as generators owned by the grid operator itself, relative transactions with power generators, and markets where electric power is traded. In many cases, power is procured from a plurality of suppliers having different properties. In order to determine the amount of procurement from multiple suppliers to be economically optimal, it is essential to accurately calculate the procurement costs required to procure power from each supplier. In this case, the nature of the procurement method and procurement cost for procuring electric power vary depending on the supplier. This will be described below.

  First, when the generator owned by the grid operator itself is the procurement source, since the power procurement method is power generation, the power procurement cost is the power generation cost such as fuel costs, and the convex function with a monotonously increasing power output Given in. Further, when the procurement source is a relative transaction or a market, the power procurement method is purchase, and therefore the power procurement cost is the power purchase cost.

  Here, the power purchase cost in the spot market in which power is sold to an unspecified power retailer at a unit price determined in the market is given by a linear function using a unit price common to the market. On the other hand, the power purchase cost in a relative transaction is given by an individual function according to the contents of each relative contract, and may be given by a monotonically increasing convex function, but a monotonically increasing concave function. Or may be given as a plurality of functions including both convex and concave functions.

  Thus, the amount of procurement from a plurality of suppliers with different procurement costs, that is, generators owned by the grid operator itself, relative transactions with the power generation companies, markets, etc., is economically optimal. In this way, the objective function is the total procurement cost corresponding to the procurement amount from each supplier. Moreover, the constraint conditions of this optimization problem include supply-demand balance constraints that match the total procurement amount with the demand amount, maximum / minimum constraints on each procurement amount, and operation pattern constraints related to generator start / stop.

  In order to solve such an optimization problem, for example, it is conceivable to apply a method for solving a generator start / stop planning problem with the objective function of minimizing the power generation cost (for example, see Non-Patent Document 1). This solution approximates the cost to be minimized with a convex function such as a quadratic function, and applies the Lagrangian relaxation method. As long as the cost is given by the convex function, the operation pattern restrictions related to the start and stop of the generator are considered. The optimum power generation output can be calculated.

  However, the optimization problem as described above, that is, to determine the amount of procurement from the generator owned by the grid operator, the relative transaction with the power generation company, the market, etc., to be economically optimal. Regarding the optimization problem, as mentioned above, the procurement cost of the relative transaction may be given as a concave function. In this case, even if the same solution is used, it is not possible to obtain a procurement amount that minimizes the procurement cost. Can not.

  Further, when the procurement amount is economically determined by online control on the day of operation, if the cost to be minimized is given by a piecewise linear and monotonically increasing concave function, it is disclosed in Patent Document 1 Different economic load allocation methods can be applied. However, the proposal of Patent Document 1 is aimed at instantaneous cost minimization at a certain time, and is not suitable when there is an operation pattern restriction related to starting and stopping of the generator.

JP 2003-199251 A IEEJ Power and Energy Sector Power System Technical Committee New Power System Planning Method Research Special Committee, “New Power System Planning Method”, IEEJ Technical Report No. 647, August 8, 1997, p. 45

  As mentioned above, the procurement cost given by the concave function when the power is procured from a plurality of suppliers with different properties such as generators owned by the grid operator, relative transactions with the power generation company, market, etc. In addition, when there is an operation pattern restriction related to the start / stop of the generator, the conventional method cannot obtain an economically optimal procurement amount.

  Furthermore, in the optimal procurement plan creation method of the grid operator, it is necessary to consider the handling in the case of including not only the thermal power generator but also the hydroelectric (pumped water) generator as the own generator owned by the grid operator. It is also necessary to consider operational restrictions on power transmission lines and tidal currents through interconnection lines.

  The present invention has been proposed in order to solve the above-described problems of the prior art, and its purpose is to provide a concave function when a system operator procures power from a plurality of suppliers with different properties. In addition to the operation pattern constraints, the hydropower generator handling, transmission line operation constraints, It is an object of the present invention to provide an optimum procurement plan creation method and apparatus capable of determining an economically optimum procurement amount in consideration of various conditions such as a power flow through a connection line.

  In order to achieve the above object, the present invention approximates a procurement cost given by a concave function that is monotonically increasing with respect to the procurement amount to a monotonically increasing convex function and approximates the procurement cost to the procurement amount. By checking the operation restrictions of the transmission line and adjusting the demand data based on the planned power flow of the interconnection line, the operation pattern restriction related to the start / stop of the generator, the handling of the hydroelectric generator, the operation restriction of the transmission line, the interconnection line The procurement amount that minimizes the total procurement cost can be calculated while taking into account the current and other factors.

In the present invention, important terms are defined as follows.
“System operator” is a term that refers to an operator that operates an electric power system and supplies and sells power to a customer's load. It is a broad concept that includes not only business operators that do not themselves generate power.

“Procurement cost” is a term that means a cost required to procure electric power from a supplier.
“Relative transaction” is a term that means a relative transaction between a grid operator and another business that supplies and sells power to the grid operator.
“Market” is a term that means a place for power trading, but is not limited to what is commonly called a market, such as a spot market that sells power to unspecified power retailers at a publicly disclosed unit price, It is a broad concept that includes all transactions where procurement costs are given by a linear function with a common unit price, such as a regular backup contract.

  The invention of claim 1 uses a computer to determine the amount of procurement from one or a plurality of suppliers so as to minimize the procurement cost for a given customer load. In the optimal procurement plan creation method, the supplier is selected from the group including the thermal power generator owned by the grid operator itself, the hydroelectric power generator owned by the grid operator itself, the relative transaction with the power generator, and the market. In the case of the selected supplier, a linear approximation step, a procurement amount calculation step, an operation constraint check step, and an area-specific calculation step are included.

  Here, the linear approximation step is based on the supplier data related to the procurement cost of the supplier, and when there is a specific supplier whose procurement cost is given by a function including a concave function with a monotonically increasing value, the monotonically increasing concave function is obtained. On the other hand, the procurement cost is approximated by a linear function. The procurement amount calculation step uses the procurement cost of the linear function obtained by approximation for a specific supplier based on the supplier data and the demand data related to the customer's load, and other suppliers Is a step of calculating the procurement amount from each supplier so that the total procurement cost from one or a plurality of suppliers is minimized by using the procurement cost given by a function corresponding to each supplier.

  On the other hand, the operation constraint check step is a step of checking whether or not the procurement amount calculated for the transmission line satisfies the operation constraint when the transmission line connecting the plurality of target areas has an operation constraint. The area-specific calculation step is a step of recalculating the procurement amount for each target area when the calculated procurement amount does not satisfy the operational constraints. In addition, the procurement amount calculation step is based on demand data and the interconnected power flow plan value when there is an interconnected power flow plan value given in advance from the interconnecting destination connected via the interconnected line. A step of calculating an effective demand value used for calculating the quantity.

  The invention of claim 9 grasps the invention of claim 1 from the viewpoint of the apparatus, and uses a computer to increase the amount of procurement from one or a plurality of suppliers to a given consumer load. On the other hand, in the system operator's optimal procurement plan creation device that determines the procurement cost to be minimized, the procurement source is a thermal power generator owned by the system operator itself, a hydroelectric power generator owned by the system operator itself, In the case of a supplier selected from a group including a relative transaction with a power generation company and a market, linear approximation means having each function corresponding to each step in the invention of claim 1, procurement amount calculation means, It is characterized by having operation constraint checking means.

  The invention of claim 10 grasps the inventions of claim 1 and claim 9 from the viewpoint of a computer program, and the amount of procurement from one or a plurality of suppliers is given in advance using a computer. In a program for creating an optimal procurement plan for a grid operator that determines the procurement cost to be minimal with respect to the customer's load, the procurement source is the thermal power generator owned by the grid operator itself, the grid operator's own A linear approximation function corresponding to each step in the invention of claim 1 and a procurement amount calculation when the procurement source is selected from a group including a hydropower generator, a relative transaction with a power generation company, and a market. It is characterized by having a computer realize a function and an operation constraint check function.

  According to the invention as described above, when the procurement cost is given by a monotonically increasing concave function with respect to the procurement amount, the procurement cost given by the monotonically increasing concave function is approximated by a linear function and is monotonically increasing. Since it can be a convex function, the procurement amount that minimizes the total procurement cost is calculated by applying the existing method such as the Lagrangian relaxation method and taking into account the operation pattern restrictions related to the start / stop of the generator. can do.

  In addition, if the supplier includes a hydroelectric generator owned by the grid operator itself, the procurement amount that minimizes the total procurement cost, taking into account the operation pattern restrictions related to the start and stop of the hydroelectric generator. Can be calculated. In addition, by checking the operational constraints on the transmission line against the procurement amount and calculating the effective demand value based on the planned power flow of the interconnection line, while considering the operational constraints of the transmission line and the flow through the interconnection line, The procurement amount that minimizes the total procurement cost can be calculated.

  Therefore, even if there is a procurement cost given by the concave function and there is an operation pattern constraint related to the start and stop of the generator, in addition to the operation pattern constraint, the handling of the hydroelectric generator, the transmission line Considering various conditions such as operational constraints and tidal currents through interconnection lines, the optimal procurement amount can be determined.

  The invention of claim 2 is characterized in that, in the system operator's optimum procurement plan creation method of claim 1, the procurement amount calculating step includes the step of determining the procurement amount from the supplier as follows. . That is, in this step, when the procurement amount from each supplier is calculated, if the procurement cost from the supplier is given by a linear function or a linear function obtained by approximation, When the incremental unit price (λ) and the first order coefficient (a) are the same, the total load of the customer given in advance and the total amount of procurement from one or more suppliers are the same. Determine the amount of procurement from the supplier.

  According to the present invention, when the procurement cost is given by a concave function that is monotonically increasing with respect to the procurement amount, the procurement cost is approximated by a linear function, and in the calculation process, according to the value of the incremental unit price. Since the amount of procurement from the supplier can be easily obtained, the vibration of the start / stop state of the generator when updating the Lagrangian constant in the Lagrangian relaxation method is reduced, and as a result, the number of convergence is reduced and the calculation time is reduced. Can be shortened.

  The invention of claim 3 is characterized in that, in the optimum procurement plan creation method of the system operator of claim 1 or claim 2, the procurement amount calculation step includes a step of repeating sequential calculation until the procurement cost is not reduced. Yes.

  According to this invention, when the procurement cost is given by a concave function that is monotonically increasing with respect to the procurement amount, the procurement cost is approximated by a linear function, and the procurement amount is calculated by the Lagrange relaxation method. By repeating the calculation until the procurement cost does not decrease with respect to the current procurement amount, the procurement cost can be minimized more strictly.

  According to a fourth aspect of the present invention, in the optimum procurement plan creation method of the grid operator according to any one of the first to third aspects, when the procurement amount calculating step does not need to consider operation pattern constraints, The method includes the step of calculating the procurement amount so that the total procurement cost is minimized. Here, “when there is no need to consider the operation pattern constraint” is a case where one or a plurality of suppliers includes generators owned by the grid operator, and the generators are all included in the procurement period. This is either the case where the same state regarding start and stop is maintained in the time zone, and the case where one or a plurality of suppliers does not include the generator owned by the grid operator itself.

  According to the present invention, when it is not necessary to consider the operation pattern restrictions related to the start and stop of the generator, depending on the operation pattern of the generator owned by the grid operator itself and the presence or absence of the owned generator, economic load distribution is performed. Since only the calculation can minimize the procurement cost, the calculation time can be shortened.

  According to a fifth aspect of the present invention, in the optimum procurement plan creation method for the grid operator according to any one of the first to fourth aspects, the procurement amount calculating step is performed in advance within a procurement period in one or a plurality of suppliers. When there is a supplier who needs to procure a predetermined procurement amount, the procurement amount is calculated from the supplier so that the procurement amount more than a predetermined amount is obtained and the total procurement cost is minimized. Including a step.

  According to this invention, when there is a restriction on the amount of procurement from the supplier, such as when it is necessary to purchase a predetermined amount of electricity with respect to the amount of electricity purchased from the relative transaction, the procurement amount restriction is considered. The optimal procurement amount can be determined above.

  According to a sixth aspect of the present invention, in the optimum procurement plan creation method for the grid operator according to any one of the first to fifth aspects, the procurement amount calculation step applies a load to the procurement amount from one or a plurality of suppliers. In the case where it is necessary to provide an output adjustment margin for tracking, the method includes a step of securing the output adjustment margin and calculating the procurement amount so that the total procurement cost is minimized.

  According to the present invention, when there is an output adjustment capacity constraint for load following, such as an error in demand prediction or a sudden fluctuation in demand, an optimum procurement amount that secures an output adjustment capacity is determined. be able to.

  The invention according to claim 7 is the optimum procurement plan creation method for the grid operator according to any one of claims 1 to 6, wherein the procurement amount calculating step is an adjustable load in a given consumer load. And a step of calculating a procurement amount so that the total procurement cost after the load adjustment is minimized.

  According to the invention as described above, when the load adjustment of the consumer is possible, the optimum procurement amount can be determined in consideration of the penalty cost due to the load adjustment.

  According to an eighth aspect of the present invention, in the optimum procurement plan creation method for the grid operator according to any one of the first to seventh aspects, the procurement amount calculating step includes a power sale determining step. Here, in the power sale determination step, when one or a plurality of suppliers includes a market and the procurement amount from the market becomes negative (minus), it is determined to sell power to the market. It is a step.

  According to the invention as described above, when the procurement amount from the market becomes negative, by selling only the amount of the procurement amount obtained in the market, the procurement amount of electricity is not excessive and is procured. It is possible to determine an optimum procurement amount that minimizes the cost.

  According to the present invention, the procurement cost given by a monotonically increasing concave function with respect to the procurement amount is approximated by a linear function to be a monotonically increasing convex function, and the operation constraint of the transmission line against the procurement amount is checked, By adjusting demand data based on the planned power flow from the interconnected line, it is possible to take into account operational pattern restrictions related to generator start / stop, handling of hydroelectric generators, operational restrictions on transmission lines, tidal currents through the interconnected lines, etc. However, the procurement amount that minimizes the total procurement cost can be calculated.

  Therefore, when the system operator procures electric power from a plurality of suppliers with different properties, it includes the procurement cost given by the concave function, and there are operating pattern restrictions related to generator start / stop. However, in addition to the operational pattern constraints, considering the conditions such as the handling of hydroelectric generators, operational constraints on power transmission lines, tidal currents through interconnection lines, etc. It is possible to provide an optimum procurement plan creation method and apparatus that can be determined.

  Hereinafter, an embodiment of an optimum procurement plan creation apparatus to which the present invention is applied will be specifically described with reference to the drawings.

[1. Basic embodiment]
[1-1. Basic configuration]
FIG. 1 is a conceptual diagram showing the procurement and supply of power by the grid operator targeted by the optimum procurement plan creation apparatus of the present embodiment. The optimum procurement plan creation apparatus of this embodiment is adapted to the power generator that the grid operator owns (thermal power / hydropower ( Pumping) generators), relative transactions with power generation companies, spot markets, etc., to obtain a combination of procurement quantities that minimize procurement costs.

  In this case, for each supplier, how much power should be purchased at each time zone from relative transactions and the spot market, and how much power should be purchased at each time zone for the own generator owned by the grid operator itself. Is to be output. At that time, in the own generator, the optimum procurement amount is determined in consideration of the start and stop of each time zone.

  In addition, when preparing the optimal procurement plan, if the grid flow plan value from the power retailer, the market, other grid operators, etc. is given in advance, the grid flow plan for each time zone It is necessary to subtract the value from the demand in each time zone in advance. In FIG. 1, the flow of the procurement amount is indicated by a solid line arrow, and the flow of the interconnected power flow plan value is indicated by a broken line arrow. As shown in FIG. 1, in the relationship with the grid operator, the spot market is not only a power supply source but also a connection destination connected via a connection line.

  FIG. 2 is a block diagram showing the optimum procurement plan creation apparatus according to this embodiment. The optimum procurement plan creation apparatus 1 communicates with the demand prediction system 3 through the transmission line 2. Here, the demand prediction system 3 is a system that predicts the total load of a customer for each time period for one or a plurality of consumers given in advance, and the demand data predicted by the demand prediction system 3 21 is transmitted to the optimum procurement plan creation device 1 through the transmission line 2.

  The optimum procurement plan creation device 1 inputs the required information by the information transmission device 4 that receives the demand data 21 transmitted from the demand prediction system 3, and displays the processing progress and processing results to the operator. A man-machine interface device (MMI) 5 is provided.

  The optimum procurement plan creation device 1 is composed of an optimum procurement plan creation unit 10, own generator data storage means 11, relative transaction data storage means 12, spot market data storage means 13, power retailer data storage means 14, and other systems. It is composed of operator data storage means 15, demand data storage means 16, output data storage means 17, transmission line operation constraint check means 18, demand data correction means 19, and the like. Below, each part of this optimal procurement plan preparation apparatus 1 is demonstrated.

  The own generator data storage means 11, the relative transaction data storage means 12, and the spot market data storage means 13 are means for storing supplier data relating to the procurement costs of each supplier. The spot market data storage means 13, the power retailer data storage means 14, and the other grid operator data storage means 15 are means for storing connection destination data relating to connection destinations connected via connection lines. It is. The demand data storage means 16 is means for storing the demand data 21 received from the demand prediction system 3.

  Among them, the self-generator data storage means 11 includes fuel cost characteristics, start-up cost characteristics, maximum output, minimum output, and operation pattern (minimum) of the self-generator owned by the grid operator (thermal power / hydropower (pumped water) generator). Operation time, minimum stop time, start / stop pattern) and other necessary data are saved. The relative transaction data storage unit 12 stores power transaction price characteristics, maximum purchase amount, minimum purchase amount, and other necessary data by relative transaction. Furthermore, the spot market data storage means 13 stores the expected price characteristics, the maximum purchase amount, the minimum purchase amount, and other necessary data according to the spot market.

  On the other hand, the electric power retailer data storage means 14 stores an interconnected power flow plan value by the electric power retailer connected via the interconnecting line and other necessary data. Further, the other grid operator data storage means 15 is a means for storing interconnected line power flow plan values and other necessary data by other grid operators connected via the interconnected lines.

  The optimum procurement plan creation unit 10 is a main part of the optimum procurement plan creation apparatus 1, and each supplier stored in the own generator data storage unit 11, the relative transaction data storage unit 12, and the spot market data storage unit 13. The procurement amount is determined so as to minimize the procurement cost based on the procurement source data relating to the procurement cost and the demand data 21 stored in the demand data storage means 16. The optimum procurement plan creation unit 10 includes linear approximation means 101 and procurement amount calculation means 102.

  The linear approximation means 101 is based on the data regarding the procurement cost of the relative transaction stored in the relative transaction data storage means 12, and when there is a specific relative transaction in which the procurement cost is given by a function including a concave function whose monotonously increases, This is a means of approximating the procurement cost with a linear function for a monotonically increasing concave function.

  The procurement amount calculation means 102 is obtained by approximation by the linear approximation means 101 with data relating to the procurement cost of each supplier stored in the own generator data storage means 11, the relative transaction data storage means 12, and the spot market data storage means 13. This is means for calculating the procurement amount from each supplier based on the procurement cost of the linear function obtained and the demand data 21 stored in the demand data storage means 16.

  In this case, the procurement amount calculation unit 102 uses the procurement cost of the linear function obtained by approximation by the linear approximation unit 101 for a specific relative transaction given as a function including a concave function whose procurement cost is monotonously increased. For other suppliers, the procurement cost given by the function corresponding to each supplier is used based on the data relating to the procurement cost of each supplier stored in each storage means 11-13.

  On the other hand, the output data storage means 17 is means for storing the output result data 22 of the optimum procurement plan creation unit 10, and the transmission line operation constraint check means 18 is that the output result data 22 of the optimum procurement plan creation unit 10 is the transmission line. This is a means for checking whether or not the operation restrictions are satisfied. The demand data correcting means 19 is means for correcting the demand data 21 based on the output result data 22 stored in the output data storage means 17.

  FIG. 3 is a block diagram showing an example of a computer system for realizing the optimum procurement plan creation apparatus 1 shown in FIG. In this computer system, reference numeral 301 denotes a computer including a CPU 302, a main memory 303, a memory 304, and the like, and the computer 301 is shown in FIG. 2 by a processing program recorded on the main memory 303 of the computer 301. It is made to operate as a suitable optimum procurement plan creation device 1. That is, according to the processing program, the CPU 302 and the main memory 303 are operated as the optimum procurement plan creation unit 10, the transmission line operation constraint check unit 18, and the demand data correction unit 19, and the memory 304 is operated as the storage units 11 to 17. .

  Further, the computer 301 is connected with a recording medium writing device 306 for recording a program in the recording medium 305 by a cable 307 such as a general-purpose SICI, and the processing program recorded in the main memory 303 is recorded in the recording medium writing device. The information can be arbitrarily recorded on the recording medium 305 by 306. Thus, the same processing program can be executed by another computer using the recording medium 305 or another recording medium written from the recording medium 305.

[1-2. Optimization problem]
In the optimum procurement plan creation apparatus 1 as described above, the objective function of the optimization problem solved by the optimum procurement plan creation unit 10 is the amount of procurement from each supplier as shown in the equation (1) in FIG. Total procurement cost according to

  In addition, as shown in FIG. 5, the constraint conditions for the objective function of this optimization problem are the supply and demand balance constraint that matches the total procurement amount with the demand amount, the maximum and minimum constraints for each procurement amount, and the start / stop of the generator Operating pattern restrictions, fuel consumption restrictions on thermal power generation, water consumption restrictions on hydroelectric (pumped) power generation, etc.

In the optimization problem expressed as described above, P ⁱ _g (t), P ⁱⁱ _gg (t), P ^j _b (t), and P _m (t) are procurement amounts to be determined. Of the data used to determine the procurement amount, D (t) is the demand data 21 received from the demand prediction system 3 via the information transmission device 4 and the interconnection current of each interconnection destination. It is the effective demand value calculated based on the plan value. The other data is data obtained from the procurement source data related to the procurement cost of each procurement source and the interconnection destination data related to each interconnection destination stored in each storage unit 11 to 15.

  That is, fuel cost characteristics, start-up cost characteristics, maximum / minimum output, operation pattern (minimum operation time, minimum stop time, start-stop pattern) of self-generator (thermal power) i, and use of self-generator (hydropower) ii Water volume characteristics, maximum / minimum output are stored in own generator data recording means 11, transaction price characteristics of relative transaction j, and maximum / minimum purchase amount are calculated in relative transaction data recording means 12, market expected price characteristics, maximum / minimum. The purchase amount and the interconnected power flow plan value are stored in the market data recording means 13, respectively. In addition, the planned power line connection value of the power retailer is stored in the power retailer data recording means 14, and the planned power line connection value of the other grid operators is stored in the other grid operator data recording means 15. Each is stored.

  The effective demand value D (t) is predicted by the demand prediction system 3 and is sent from the demand data sent through the information transmission device 4 as shown in the equation (9) in FIG. It is calculated by subtracting the interconnected power flow plan value planned in advance by the system operator or the like.

[1-3. Overall behavior]
FIG. 7 is a flowchart showing an outline of the operation in the optimum procurement plan creation apparatus 1 of the present embodiment having the above-described configuration.

  As shown in FIG. 7, every time the demand data 21 transmitted from the demand prediction system 3 is received by the information transmission apparatus 4 (YES in S701), the demand data storage unit 16 stores the received demand data 21. (S702). Further, the optimum procurement plan creation unit 10 is based on the data stored in the storage units 11 to 16 at a predetermined time or a predetermined cycle (YES in S703) set in advance to determine an optimal procurement amount. Then, the linear approximation processing (S704) by the linear approximation means 101 and the procurement amount calculation processing (S705) by the procurement amount calculation means 102 are sequentially performed to determine the procurement amount so that the procurement cost is minimized. Note that the processing content by the optimum procurement plan creation unit 10 is appropriately displayed to the operator by the MMI 5 during the processing.

  The transmission line operation constraint check means 18 checks whether or not the transmission line operation constraint is satisfied with respect to the output result data 22 from the optimum procurement plan creation unit 10 as a transmission line operation constraint check process. When it is a constraint violation, the procurement amount calculation unit 102 of the optimum procurement plan creation unit 10 performs the operation constraint violation notification 23 to perform the procurement amount calculation process for each area (S706).

  Then, when the optimum procurement amount from each supplier is determined by the optimum procurement plan creation unit 10, the result is displayed to the operator by the MMI 5, and also as output result data 22 by the output data storage means 17. Saved (S707). In addition, when the amount of procurement is determined by the optimum procurement plan creation unit 10 so that the total procurement cost after the load adjustment of the customer is minimized, the demand data needs to be corrected (YES in S708). The output data storage means 17 passes the output result data 22 to the demand data correction means 19, and the demand data correction means 19 reads the demand data from the demand data storage means 16, makes necessary corrections, and stores the demand data again. The data is stored in the means 16 (S709).

[1-4. Linear approximation process]
FIG. 8 is a flowchart showing an example of a subroutine of the linear approximation process (S704) by the linear approximation means 101 of the optimum procurement plan creation unit 10 among the operations shown in FIG.

  As shown in FIG. 8, in the linear approximation process, the linear approximation means 101 is a function including a concave function whose procurement cost is monotonically increased based on data on the procurement cost of the relative transaction stored in the relative transaction data storage unit 12. It is determined whether there is a given relative transaction (S801). If there is no relative transaction given by a function including a monotonically increasing concave function (NO in S801), the linear approximation process is terminated and the process proceeds to a procurement amount calculation process (S705) shown in FIG. If there is a relative transaction given by a function including a monotonically increasing concave function (YES in S801), it is further determined whether or not all procurement costs of the relative transaction are given by a monotonically increasing concave function ( S802).

  When all the procurement costs for the relative transaction are given by a monotonically increasing concave function (YES in S802), the procurement costs for the relative transaction are all approximated by a linear function (S803). Further, when the procurement costs of the relative transaction are not all given by a monotonically increasing concave function, that is, when they are given by a monotonically increasing convex function and a monotonically increasing concave function (NO in S802), the monotonically increasing The procurement cost is approximated by a linear function only for the concave function (S804). Then, after approximating the procurement cost, the linear approximation process is terminated and the process proceeds to the procurement amount calculation process (S705) shown in FIG.

  FIG. 9 is an explanatory diagram showing a specific method for approximating a procurement cost given by a monotonically increasing concave function to a linear function. As shown in FIG. 9, when the procurement cost of a specific relative transaction is given by a monotonically increasing concave function (for example, an upward convex quadratic function), the procurement cost at the minimum purchase amount in the relative transaction By linearly approximating two points of (Xmin, Ymin) and procurement cost (Xmax, Ymax) at the maximum purchase amount, the procurement cost can be approximated by a linear function. Note that 901 in FIG. 9 is a continuous and monotonically increasing concave function before approximation, and 902 is a linear function after approximation.

  FIG. 9 shows the case where the procurement cost is given by a continuous and monotonically increasing concave function. However, the case where the procurement cost is given by a piecewise linear and monotonically increasing concave function is similarly reduced to the minimum / Procurement cost can be approximated by a linear function by linearly approximating two points of procurement cost at the maximum purchase amount.

  Since all procurement costs are expressed as a monotonically increasing convex function by the linear approximation process as described above, the subsequent procurement amount calculation process can be implemented by applying existing methods such as the Lagrangian relaxation method. The procurement quantity that minimizes the cost can be determined.

[1-5. Procurement amount calculation process]
FIG. 10 is a flowchart illustrating an example of a subroutine of the procurement amount calculation process (S705) by the procurement amount calculation unit 102 of the optimum procurement plan creation unit 10. The procurement amount calculation process shown in FIG. 10 shows an example when the Lagrangian relaxation method is applied as an existing method.

  As shown in FIG. 10, in the procurement amount calculation process, the procurement amount calculation means 102 first determines whether or not a grid flow plan value is given by the market, a power retailer, another system operator, or the like. (S1001) If there is a predetermined interconnected ship tidal current plan value (YES in S1001), the effective demand value is calculated based on the demand data and the interconnected tidal current plan value as shown in FIG. Calculate (S1002).

  The procurement amount calculation unit 102 also sets a Lagrange constant and initial values of each procurement amount (S1003). Next, using a dynamic planning (DP) method, a procurement state (start-stop state) that minimizes the procurement cost is obtained for each supplier (S1004). In this case, the own generator also considers operation pattern constraints such as minimum operation time, minimum stop time, and start / stop pattern. Next, the procurement amount in the procurement state that minimizes the procurement cost is obtained for each supplier (S1005). In this case, the maximum / minimum (maximum / minimum purchase amount) constraints for each supplier are considered.

  With respect to the procurement amount obtained for each supplier, the supply-demand balance constraint is checked (S1006). If the constraint is satisfied (YES in S1006), the procurement amount calculation process is terminated and shown in FIG. Proceed to the power transmission line operation constraint check process (S706). If the supply-demand balance constraint is not satisfied (NO in S1006), the Lagrange constant is updated in accordance with each constraint (S1007), and the process returns to S1004.

[1-6. Transmission line operation constraint check processing]
FIG. 11 is a flowchart showing an example of a subroutine of the transmission line operation constraint check process (S706) by the transmission line operation constraint check unit 18 and the procurement amount calculation unit 102 of the optimum procurement plan creation unit 10.

  As shown in FIG. 11, in the power transmission line operation constraint check process, the power transmission line operation constraint check means 18 among the power transmission lines connecting the plurality of target areas, the power transmission line that should be considered for operation constraints (YES in S1101). Is identified as a check target (S1102), and for each of the identified transmission lines, a check is made as to whether the procurement amount in the output result data 22 from the optimum procurement plan creation unit 10 satisfies the operational constraints of the transmission line. This is performed (S1103).

  If the output result data 22 satisfies the transmission line operation constraint (YES in S1104), or if the transmission line operation constraint does not need to be considered (S1101 NO), the transmission line operation is performed as it is. The constraint check process is terminated, and the process proceeds to the result output / save process (S707) shown in FIG. On the other hand, when the output result data 22 violates the transmission line operation constraint (NO in S1104), the transmission line operation constraint check unit 18 includes the procurement amount calculation unit 102 of the optimum procurement plan creation unit 10. By performing the operation constraint violation notification 23, the procurement amount calculation processing for each target area is performed (S1105).

  Here, as shown in FIG. 12, a case where a 10 MW operation constraint violation occurs from the area A to the area B in the time zone t1 will be described as an example. First, in the first procurement amount calculation process (S705 in FIG. 7), after satisfying the constraints of equations (2) to (8) in FIG. 5, equation (1) in FIG. 4 is used as the objective function. Minimizing. Therefore, the supply-demand balance constraint in equation (2) is equivalent to satisfying equation (10) in FIG.

  In this case, in the example of FIG. 12, since a 10 MW operation constraint violation has occurred on the power transmission line between the two areas, the Σ demand in each area is obtained using equations (11) and (12) in FIG. Thus, the procurement amount calculation process for each area is performed. However, there is no change in Σ demand in the area during the time when no constraint violation has occurred. At that time, in the objective function of the equation (1) in FIG. 4, the in-house generator, the relative transaction, and the market are formulated by dividing into the corresponding areas, and accordingly, the equation (2) to FIG. The constraint equation of equation (8) will also change.

[1-7. Basic effects]
As described above, according to the present embodiment, when the procurement cost is given by a concave function that is monotonically increasing with respect to the procurement amount, the procurement cost given by the monotonically increasing concave function is approximated by a linear function. Procurement that minimizes the total procurement cost by applying existing methods such as the Lagrangian relaxation method and taking into account operating pattern constraints related to generator start-up and shutdown because it can be a monotonically increasing convex function The amount can be calculated.

  In addition, if the supplier includes a hydroelectric generator owned by the grid operator itself, the procurement amount that minimizes the total procurement cost, taking into account the operation pattern restrictions related to the start and stop of the hydroelectric generator. Can be calculated. In addition, by checking the operational constraints on the transmission line against the procurement amount and calculating the effective demand value based on the planned power flow of the interconnection line, while considering the operational constraints of the transmission line and the flow through the interconnection line, The procurement amount that minimizes the total procurement cost can be calculated.

  Therefore, even if there is a procurement cost given by the concave function and there is an operation pattern constraint related to the start and stop of the generator, in addition to the operation pattern constraint, the handling of the hydroelectric generator, the transmission line Considering various conditions such as operational constraints and tidal currents through interconnection lines, the optimal procurement amount can be determined.

  FIG. 14 is a time chart showing an example of the procurement amount from each procurement source obtained by the optimum procurement plan creation apparatus 1 of the present embodiment. In the case of the example shown in FIG. 14, the own generator has an operation pattern restriction such as a minimum operation time, a minimum stop time, and a start / stop pattern, that is, a time restriction, so that the procurement cost is minimized. In order to obtain the procurement amount, the Lagrangian relaxation method will be adopted. On the other hand, there are no time restrictions such as operation pattern restrictions in the relative transaction and spot market, so the lambda iteration method or the incremental method is adopted to obtain the procurement amount that minimizes the procurement cost. be able to. In this embodiment, by adopting linear approximation and the Lagrangian relaxation method for a plurality of suppliers with different temporal constraints, the optimal amount of procurement considering different constraints for each supplier. Is something that can be determined.

[2. Modification of procurement amount calculation process]
[2-1. Procurement amount calculation process according to incremental unit price]
As described above, when the procurement amount calculation process is performed by the optimum procurement plan creation unit 10 of the present embodiment, as shown in FIG. 10, the calculation is repeated until the constraints are satisfied while the Lagrange constant is updated. Become. In this case, if the procurement cost approximated by a linear function or the procurement cost given by the unit price (primary function) of wholesale purchased power is applied as it is, the self-generated power is generated when the convergence calculation is repeated. The machine start / stop state may vibrate.

  In order to suppress such vibration in the start / stop state, in the calculation process for calculating the procurement amount, the procurement amount is obtained by the value of the incremental unit price as follows. That is, the procurement unit incremental unit price (λ) in which the procurement cost is given by a linear function as shown in equation (13) in FIG. 15 is a constant (primary coefficient) as shown in equation (14) in FIG. The relationship between the procurement amount and the incremental unit price is as shown in FIG.

  From FIG. 16, when λ> a, the procurement amount is the maximum purchase amount (Pmax), and when λ <a, the procurement amount is the minimum purchase amount (Pmin). In addition, when λ = a, the incremental unit price (λ) is constant no matter how much the procurement amount is, so the value obtained by subtracting other procurement amounts from the demand data to balance the supply and demand Set to procurement amount.

  According to this procurement amount calculation process, when the procurement cost is given by a concave function that is monotonically increasing with respect to the procurement amount, the procurement cost is approximated by a linear function, and the unit price is incremented during the calculation process. Accordingly, the procurement amount from the supplier can be easily obtained. Therefore, the vibration in the start / stop state of the generator when the Lagrangian constant is updated in the Lagrangian relaxation method can be reduced. As a result, the number of convergence can be reduced and the calculation time can be shortened.

[2-2. Procurement amount calculation process by repeated calculation using incremental unit price]
As described above, when the procurement amount calculation process is performed by the optimum procurement plan creation unit 10 of the present embodiment, if the procurement cost is given by a concave function that is monotonically increasing with respect to the procurement amount, the procurement cost is set to 1. A Lagrangian relaxation method can be applied by approximating a quadratic function. However, when a procurement cost approximated to a linear function is simply used, an error occurs from the actual procurement cost (original function before approximation), and strict cost minimization cannot be performed.

  Therefore, in order to perform more rigorous cost minimization, when determining the procurement amount from each supplier in S1005 (FIG. 10) in the procurement amount calculation process, the current procurement amount (the procurement amount during the calculation process) is determined. On the other hand, using the incremental unit price in the direction of increasing the procurement amount (upward increment unit price) or the incremental unit price in the direction of decreasing the procurement amount (decrease incremental unit price), the calculation is repeated until the procurement cost does not decrease.

  When the procurement amount from each supplier is determined in the procurement amount calculation process (S1005 in FIG. 10), it is possible to minimize the instantaneous procurement cost at a certain time by repeatedly performing such incremental unit price. By repeating the determination of the status of each supplier, the determination of the procurement amount, and the balance between supply and demand while updating the Lagrange constant (S1004 to S1007 in FIG. 10), the entire procurement time period can be obtained. Procurement costs can be minimized.

  According to this procurement amount calculation process, when the procurement cost is given by a concave function that increases monotonously with respect to the procurement amount, when the procurement amount is approximated by a linear function and the procurement amount is calculated by the Lagrange relaxation method, By repeatedly calculating until the procurement cost does not decrease with respect to the current procurement amount during the calculation process, the procurement cost can be minimized more strictly.

[2-3. Procurement amount calculation when there is no need to consider operation pattern restrictions]
As described above, when performing the procurement amount calculation process by the optimum procurement plan creation unit 10 of the present embodiment, the operation pattern of the own generator can be considered by applying the Lagrange relaxation method. There may be cases where it is not necessary to consider generator operating pattern constraints.

  That is, according to the optimum procurement plan creation apparatus 1 of the present embodiment, the optimum procurement plan can be obtained when there are three types of suppliers, that is, a self-generator, a relative transaction, and a spot market. When there is any one or two types of suppliers, for example, even when the system operator does not own one of the own generators, the optimum procurement plan can be obtained in the same manner.

  In this way, when the system operator does not own any own generator, it is not necessary to consider the operation pattern restrictions of the own generator. In addition, even if the grid operator owns its own generator, if the own generator is activated or stopped in all time zones within the procurement period, the same applies. Since it is not necessary to consider the operation pattern restrictions, the procurement cost may be minimized at each procurement time. In such a case, the procurement cost can be minimized and the calculation time can be shortened by adapting the existing economic load distribution calculation such as the lambda iteration method and the incremental method instead of the optimization by the Lagrangian relaxation method.

  FIG. 17 is a flowchart illustrating an example of a procurement amount calculation process in the case where it is not necessary to consider the operation pattern restriction of the own generator. As shown in FIG. 17, when the self-generator maintains the same state in all time zones within the procurement period, or when there is no self-generator (YES in S1701), economic load distribution is performed. (S1702), if not (NO in S1701), the optimal procurement amount is calculated by the Lagrange relaxation method (S1703). In this case, the “optimum procurement amount calculation process” of S1703 corresponds to the processes of S1003 to S1007 shown in FIG.

  According to this procurement amount calculation process, when it is not necessary to consider the operation pattern restrictions related to the start and stop of the generator depending on the operation pattern of the generator owned by the grid operator and the presence or absence of the owned generator Since the procurement cost can be minimized by performing only the economic load distribution calculation, the calculation time can be shortened.

  In the following description, the term “procurement amount calculation process” will be used to indicate the overall process for calculating the procurement amount from each supplier, and the term “optimum procurement amount calculation process” It is used to indicate a basic calculation process included in the “procurement amount calculation process”, that is, a basic calculation process by the Lagrange relaxation method as shown in S1003 to S1007 of FIG.

[2-4. Procurement volume calculation process considering procurement volume constraints]
In the case of a relative transaction, the content of the contract may include the procurement (purchase) of a predetermined amount of power with respect to the amount of power to be purchased. FIG. 18 is a flowchart illustrating an example of a procurement amount calculation process in consideration of such a procurement amount constraint. As shown in FIG. 18, first, after calculating the optimum procurement amount without setting the procurement amount constraint (S1801), the procurement amount (purchase amount) from the obtained relative transaction and the actual purchase amount are obtained. The amount of power (constraint amount) that must be compared is compared (S1802).

  In this case, if the obtained procurement amount is larger (YES in S1802), the procurement amount calculation process is terminated because the procurement amount constraint is satisfied. In addition, when the constraint amount is larger than the procurement amount (NO in S1802), the amount of power that must actually be purchased is set as the constraint amount (S1803), and the optimum procurement amount calculation process is performed again. It performs (S1804). In this case, equations (15) and (16) in FIG. 19 are added to the constraint conditions (FIG. 5) for the objective function of the optimization problem described above.

  According to this procurement amount calculation process, when there is a restriction on the procurement amount from the supplier, the optimum procurement amount can be determined in consideration of the restriction on the procurement amount.

[2-5. Procurement amount calculation process considering output adjustment capacity constraints]
As described above, the optimum procurement plan creation unit 10 of the present embodiment determines the amount of procurement from each supplier based on the predicted demand data. Therefore, it is necessary to secure reserve capacity because sudden fluctuations in demand may occur. For example, a large reserve capacity is provided for a time zone in which the demand fluctuation changes greatly (morning load rise). On the contrary, in the time zone (midnight zone) where the load fluctuation is relatively small, a supplier with a small reserve capacity is secured to secure a supplier whose output can be adjusted.

  Specifically, when performing the procurement amount calculation process by the optimum procurement plan creation unit 10, the equations (17) and (18) in FIG. 20 are added to the constraint conditions for the objective function of the optimization problem described above.

  According to this procurement amount calculation process, the optimal procurement amount with sufficient output adjustment capacity when there is an output adjustment capacity limitation for load following, such as a demand forecast error or a sudden fluctuation in demand. Can be determined.

[2-6. Procurement volume calculation process considering customer load adjustment]
As described above, in the optimum procurement plan creation unit 10 of the present embodiment, the demand data 21 predicted by the demand prediction system 3, that is, the total load of one or a plurality of consumers given in advance is used as the demand data. The procurement amount from each supplier is determined so as to satisfy the supply-demand balance constraint. In this case, if each customer has a contract that can adjust the load (it is possible to cut some of the load against the contract power and remove it from the procurement target), adjust the load adjustment. It is possible to perform procurement amount calculation processing in consideration.

  When the system operator sets the load to be removed from the procurement target by some means, the system operator pays a penalty to the customer of the target load. Since the penalty in this case can be converted into a unit cost [yen / kW], for example, with respect to the load to be removed from the procurement target, the procurement amount can be calculated using the converted cost as the load adjustment cost.

  FIG. 21 is a flowchart illustrating an example of a procurement amount calculation process in consideration of such load adjustment costs. As shown in FIG. 21, first, after performing the optimum procurement amount calculation process without adjusting the load (S2101), the load of demand data is adjusted for the load adjustable consumer (S2102). . In this case, the cost conversion for the load to be cut may be a unit cost whose price varies depending on the load to be cut as shown in FIG. Next, the optimum procurement amount calculation process is performed using the demand data adjusted in this way, and the value obtained by adding the load adjustment cost to the procurement cost is set as the procurement cost after the load adjustment (S2103).

  Subsequently, the procurement cost after the current load adjustment is compared with the previous procurement cost before the load adjustment (S2104). If the previous procurement cost is lower (YES in S2104), the procurement amount obtained in the previous optimum procurement amount calculation process is determined (S2105), and the procurement amount calculation process is terminated. If the adjustment cost after the current load adjustment is lower than the previous one (NO in S2104), the process returns to S2102 and the processes of S2102 to S2105 are repeated as long as the adjustment cost is reduced. Note that the end determination by the adjustment cost comparison in S2104 can also be determined by a human system, and the process can be ended even when the end determination is not satisfied.

  According to this procurement amount calculation process, when the load adjustment of the consumer is possible, the optimum procurement amount can be determined in consideration of the penalty cost due to the load adjustment.

[2-7. Procurement amount calculation process considering power sales to the market]
As described above, the optimum procurement plan creation unit 10 of the present embodiment calculates the amount of procurement from each supplier based on the predicted demand data, but the maximum / minimum constraints (( In equation (6), if the maximum and minimum constraints are set to minus, the obtained procurement amount may be minus. The fact that the amount of procurement from the market is negative indicates that it is possible to minimize costs by selling power to the market rather than from the market.

  Specifically, when determining the procurement amount from the market in S1005 of FIG. 10, if the procurement amount calculated for the market is negative, the amount of the negative procurement amount is sold to the market. Decide to power.

  According to this procurement amount calculation process, when the procurement amount from the market becomes negative, the electricity is sold by the amount of the procurement amount obtained in the market, and the procurement amount of electricity is not excessive. It is possible to determine an optimum procurement amount that minimizes the cost.

[3. Other Embodiments]
It should be noted that the present invention is not limited to the above-described embodiments, and various other variations can be implemented within the scope of the present invention. For example, the above-described modified examples can be appropriately combined.

  Moreover, in the said embodiment, although the case where a supplier is a self-generator, a relative transaction, and a spot market was demonstrated, the supplier of this invention is not limited to this. For example, if the spot market is not established and there is a regular backup contract by an electric power company, the expected price characteristic of the spot market in the objective function shown in equation (1) of FIG. Can be formulated in the same way.

  Furthermore, the configuration and processing procedure of the optimum procurement plan creation apparatus shown in the above embodiment are merely examples, and the procurement cost given by a concave function that is monotonically increasing with respect to the procurement amount is approximated by a linear function, As long as the amount of procurement from each supplier is calculated so that the total procurement cost is calculated by checking the operation restrictions of the wires and adjusting the demand data based on the planned power flow of the interconnection, the specific equipment configuration and processing procedure Can be changed freely.

The conceptual diagram which shows the procurement and supply of the electric power by the system operator which the optimal procurement plan creation apparatus of embodiment to which this invention is applied makes object. The block block diagram which shows the optimal procurement plan creation apparatus of embodiment to which this invention is applied. The block diagram which shows an example of the computer system for implement | achieving the optimal procurement plan preparation apparatus shown in FIG. The figure which shows an example of the objective function of the optimization problem solved by the optimal procurement plan preparation part shown in FIG. The figure which shows an example of the constraint condition with respect to the objective function of the optimization problem shown in FIG. The figure which shows an example of the calculation formula and calculation result which calculate the demand value shown in FIG. 5 based on the demand data predicted by the demand prediction system shown in FIG. 2 and the interconnection line power flow plan value given beforehand. The flowchart which shows the outline of operation | movement in the optimal procurement plan preparation apparatus shown in FIG. 8 is a flowchart illustrating an example of a subroutine for linear approximation processing illustrated in FIG. 7. FIG. 9 is an explanatory diagram showing a specific method for approximating a procurement cost given by a monotonically increasing concave function to a linear function in the linear approximation processing shown in FIG. 8. The flowchart which shows an example of the subroutine of the procurement amount calculation process shown in FIG. The flowchart which shows an example of the subroutine of the power transmission line operation restrictions check process shown in FIG. The figure which shows an example of the concrete operation | movement constraint violation detected by the power transmission line operation | movement constraint check process shown in FIG. The figure which shows the calculation formula for demonstrating the detail of the power transmission line operation | movement constraint check process shown in FIG. The time chart which shows an example of the procurement amount from each supplier obtained by the optimal procurement plan creation apparatus shown in FIG. The figure which shows each definition formula of a procurement cost and an incremental unit price about the procurement destination where a procurement cost is given by a linear function. The graph which shows the relationship between the increment unit price of the supplier in which procurement cost is given with a linear function, and the amount of procurement. The flowchart which shows an example when it is not necessary to consider the operation pattern restrictions of a self-generator as a modification of the procurement amount calculation process shown in FIG. The flowchart which shows an example at the time of considering procurement amount restrictions as a modification of the procurement amount calculation process shown in FIG. The figure which shows the constraint conditions added to the constraint conditions shown in FIG. 5 in the procurement amount calculation process shown in FIG. FIG. 11 is a diagram illustrating a constraint condition that is added to the constraint condition illustrated in FIG. 5 in a case where an output adjustment margin constraint is considered as a variation of the procurement amount calculation process illustrated in FIG. The flowchart which shows an example at the time of considering load adjustment cost as a modification of the procurement amount calculation process shown in FIG. The graph which shows the relationship between the load amount to cut and load adjustment cost in the case of considering load adjustment of a consumer.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Optimal procurement plan preparation apparatus 2 ... Transmission line 3 ... Demand prediction system 4 ... Information transmission apparatus 5 ... Man-machine interface apparatus (MMI)
DESCRIPTION OF SYMBOLS 10 ... Optimal procurement plan preparation part 11 ... Own generator data storage means 12 ... Relative transaction data storage means 13 ... Spot market data storage means 14 ... Electric power retailer data storage means 15 ... Other system operator data storage means 16 ... Demand data storage means 17 ... output data storage means 18 ... transmission line operation constraint check means 19 ... demand data correction means 21 ... demand data 22 ... output result data 23 ... output result data 101 ... linear approximation means 102 ... procurement amount calculation means

Claims (10)

In the optimal procurement plan creation method of the grid operator that determines the procurement amount from one or more suppliers using a computer so that the procurement cost is minimized with respect to the load of the customer given in advance,
The supplier is a supplier selected from a group including a thermal power generator owned by the grid operator, a hydroelectric generator owned by the grid operator, a relative transaction with the power generator, and a market. If
Based on the supplier data relating to the procurement cost of the supplier, when there is a specific supplier whose procurement cost is given as a function including a monotonically increasing concave function, the procurement cost is firstly determined for the monotonically increasing concave function. A linear approximation step to approximate with a function;
Based on the supplier data and demand data related to the load of the customer, the procurement cost of the linear function obtained by the approximation is used for the specific supplier, and each supplier is provided for other suppliers. A procurement amount calculation step of calculating a procurement amount from each of the suppliers so that a total procurement cost from the one or more suppliers is minimized using a procurement cost given by a function according to the destination;
When there is an operation constraint on a transmission line connecting a plurality of target areas, an operation constraint check step for checking whether or not the calculated procurement amount for the transmission line satisfies the operation constraint;
When the calculated procurement amount does not satisfy the operational constraints, the calculation step for each area recalculates the procurement amount for each target area,
The procurement amount calculating step is based on the demand data and the interconnected power flow plan value when there is an interconnected power flow plan value given in advance from the interconnecting destination connected via the interconnected line. Including a step of calculating an effective demand value used for calculating the quantity,
An optimal procurement plan creation method for grid operators characterized by The procurement amount calculating step includes:
When the procurement amount from each supplier is calculated, when the procurement cost from the supplier is given by a linear function or a linear function obtained by the approximation, the incremental unit price (λ) of the procurement cost And the first-order coefficient (a) become the same so that the total load of the given customer is the same as the total amount of procurement from the one or more suppliers Including determining the amount of procurement from the destination,
The optimal procurement plan creation method for the grid operator according to claim 1. The procurement amount calculating step includes:
Including the step of repeating sequential calculation until the procurement cost does not decrease,
The method for creating an optimum procurement plan for a system operator according to claim 1 or claim 2, wherein: The procurement amount calculating step includes:
The one or more suppliers include a generator owned by the grid operator itself, and the generator maintains the same state with respect to startup and shutdown in all time zones within the procurement period; and
When the one or more suppliers do not include the generator owned by the grid operator itself,
Calculating the procurement amount so that the total procurement cost at each procurement time is minimized,
The method for creating an optimum procurement plan for a system operator according to any one of claims 1 to 3. The procurement amount calculating step includes:
When there is a supplier that must procure a predetermined procurement amount within the procurement period among the one or more suppliers, procure a procurement amount that is greater than a predetermined amount from the supplier, And calculating a procurement amount so that the total procurement cost is minimized.
The method for creating an optimum procurement plan for a system operator according to any one of claims 1 to 4, wherein The procurement amount calculating step includes:
When it is necessary to provide an output adjustment margin for load tracking with respect to the procurement amount from the one or a plurality of suppliers, the output adjustment margin is ensured and the total procurement cost is minimized. Including the step of calculating the procurement amount,
The method for creating an optimum procurement plan for a grid operator according to any one of claims 1 to 5. The procurement amount calculating step includes:
Including a step of calculating a procurement amount so that the total procurement cost after the load adjustment is minimized when there is an adjustable load in the load of the customer given in advance.
The method for creating an optimum procurement plan for a system operator according to any one of claims 1 to 6. The procurement amount calculating step includes:
When the one or more suppliers include the market, and when the procurement amount from the market becomes negative (minus), including a power sale determination step of determining to sell power to the market;
The method for creating an optimum procurement plan for a system operator according to any one of claims 1 to 7. In the optimal procurement plan creation device of the grid operator that determines the procurement amount from one or more suppliers using a computer so that the procurement cost is minimized with respect to the load of a given customer in advance,
The supplier is a supplier selected from a group including a thermal power generator owned by the grid operator, a hydroelectric generator owned by the grid operator, a relative transaction with the power generator, and a market. If
Based on the supplier data relating to the procurement cost of the supplier, when there is a specific supplier whose procurement cost is given as a function including a monotonically increasing concave function, the procurement cost is firstly determined for the monotonically increasing concave function. Linear approximation means to approximate with a function;
Based on the supplier data and demand data related to the load of the customer, the procurement cost of the linear function obtained by the approximation is used for the specific supplier, and each supplier is provided for other suppliers. A procurement amount calculation means for calculating a procurement amount from each supplier so that a total procurement cost from the one or more suppliers is minimized by using a procurement cost given by a function according to the destination,
When there is an operation constraint on a transmission line connecting a plurality of target areas, the operation constraint check means for checking whether or not the calculated procurement amount for the transmission line satisfies the operation constraint,
The procurement amount calculation means is configured to recalculate the procurement amount for each target area when the calculated procurement amount does not satisfy the operation constraint, and via a connection line When there is an interconnected power flow plan value given in advance from the connected interconnecting destination, an effective demand value used to calculate a procurement amount is calculated based on the demand data and the interconnected power flow plan value Configured
An optimal procurement plan creation device for grid operators. In a system operator's optimal procurement plan creation program that uses a computer to determine the amount of procurement from one or more suppliers to minimize procurement costs for a given customer load. ,
The supplier is a supplier selected from a group including a thermal power generator owned by the grid operator, a hydroelectric generator owned by the grid operator, a relative transaction with the power generator, and a market. If
Based on the supplier data relating to the procurement cost of the supplier, when there is a specific supplier whose procurement cost is given as a function including a monotonically increasing concave function, the procurement cost is firstly determined for the monotonically increasing concave function. A linear approximation function that approximates with a function;
Based on the supplier data and demand data related to the load of the customer, the procurement cost of the linear function obtained by the approximation is used for the specific supplier, and each supplier is provided for other suppliers. A procurement amount calculation function for calculating a procurement amount from each supplier so that a total procurement cost from the one or a plurality of suppliers is minimized by using a procurement cost given by a function according to the destination;
When there is an operation constraint on a transmission line connecting multiple target areas, the computer implements an operation constraint check function that checks whether the calculated procurement amount for the transmission line satisfies the operation constraint. Configured to let
The procurement amount calculation function includes a function for recalculating the procurement amount for each target area when the calculated procurement amount does not satisfy the operation restrictions, and a connection connected via a connection line. Including a function of calculating an effective demand value to be used for calculating a procurement amount based on the demand data and the interconnected current flow plan value when there is an interconnected power flow plan value given in advance from the system;
A program for creating an optimal procurement plan for grid operators.