DE112019007194T5 - OPERATIONAL PLANNING INSTITUTION, OPERATIONAL PLANNING PROCEDURE AND OPERATIONAL PLANNING PROGRAM - Google Patents

Abstract

A power generator group determination unit (122) divides a plurality of power generators into a plurality of power generator groups. A partial problem solution acquiring unit (123) generates a partial problem in units of power generation groups based on a reference problem that is an optimization problem for setting an operation plan for the plurality of power generations, and solves the partial problem in units of power generation groups, thereby obtaining a partial problem solution. A final solution acquiring unit (124) extracts some partial problem solutions from a collection of partial problem solutions for each power producer group, generates a final solution setting problem, which is an optimization problem for a case where each power producer works according to the some partial problem solutions, and solves it Final solution determination problem, whereby a final solution is obtained.

Description

field of technology

The present invention relates to a technique for obtaining operation schedules from a plurality of power producers.

General state of the art

When it comes to energy supply, it is necessary to draw up corresponding operating plans for a large number of energy producers in order to achieve stability and economy. In particular, operation plans need to be prepared so that power demand and power generation amount are matched, physical constraint conditions of each power generator are satisfied, and a power generator with good power generation efficiency is operated appropriately.

A problem for setting operational schedules for a variety of power generators is referred to as an "operational planning problem".

The operational planning problem is also known as the unit commitment problem (power plant utilization optimization) and has been widely studied. It is known that the operational planning problem is formulated as a mixed 01 integer programming problem in which a 01 decision variable and a continuous decision variable coexist.

In many studies in which the operation planning problem is formulated as a mixed 01-integer programming problem, a power generator operation status and a power generator suspension status are formulated by a 01 decision variable, and a power generator output value is expressed by a continuous decision variable. Then, a decision variable is added according to the types of constraint conditions to be considered and the way of describing the constraint conditions to be considered. The goal is to minimize the total energy production costs, which are composed of fuel costs and energy generator operating costs.

The most important constraint conditions are a demand-supply-demand-balance constraint, a reserve power constraint, a power generation constraint, a fuel constraint, and so on. The demand-satisfaction-demand-equilibrium constraint is a constraint that the energy demand and the amount of energy production must match. The reserve energy constraint is a restriction that a certain amount of reserve energy and a certain amount of adjustment energy must be secured. The power generator operation constraint is a constraint that the power generator must meet operating conditions inherent in it, such as a minimum continuous operating time, a minimum continuous down time, a posted upper limit, a posted lower limit, and a posted slew rate. The fuel constraint is a constraint that the fuel consumption amount must not exceed a remaining fuel amount.

The mixed-01 integer programming problem is a combinatorial optimization problem, and accordingly it takes time to solve the mixed-01 integer programming problem. In particular, as the scale of the mixed-01 integer programming problem increases, a solution time tends to increase sharply.

A scope of the operational planning problem is defined by a number of energy producers, a length of a planned runtime, and a time increment.

It is expected that the number of power generators as a target of operational planning will increase in the future due to the large-scale cooperation accompanying the liberalization of the power market. In addition, the time step size is expected to be fine-tuned to formulate a more detailed operational plan.

It is therefore to be expected that the scope of the operational planning problem will increase in the future. For this reason, a means for solving the operational planning problem at high speed is required.

Patent Literature 1 discloses a method of formulating operation plans for a plurality of power generators.

In this method, a plurality of power generators are divided into a plurality of power generator groups, an operation plan is formulated for each power generator group by regarding power generators belonging to a single power generator group as a virtual power generator, and an operation plan is formulated for each power generator in units of power generator groups. In this way, a high-speed solution can be achieved.

List of citations

patent literature

Patent Literature 1: JP 2018-106431 A

Summary of the Invention

Technical problem

In the method of Patent Literature 1, when the power generation group is to be regarded as a virtual power producer, only limited information such as power generation efficiency is used.

Meanwhile, various restrictions are imposed on a power generator, such as a minimum continuous operation time, an output upper limit, an output lower limit, and an output slew rate. Therefore, the feasibility can only be guaranteed if a virtual power generator is created considering the various constraints.

Therefore, the application cases of the method disclosed in Patent Literature 1 are limited to a relatively simple example.

An object of the present invention is to enable an operation planning problem to be solved with high speed and accuracy while considering various constraint conditions imposed on the respective power generators.

solution of the task

• eine Energieerzeugergruppe-Festlegungseinheit, um eine Vielzahl von Energieerzeugern in eine Vielzahl von Energieerzeugergruppen zu unterteilen;
• eine Teilproblemlösung-Erwerbungseinheit, um ein Teilproblem, das ein Optimierungsproblem ist zum Festlegen eines Betriebsplans für einen oder mehrere Energieerzeuger, gehörend zu jeder Energieerzeugergruppe, in Einheiten von Energieerzeugergruppen zu generieren auf Grundlage eines Referenzproblems, das ein Optimierungsproblem ist zum Festlegen eines Betriebsplans für die Vielzahl von Energieerzeugern, und um das Teilproblem in Einheiten von Energieerzeugergruppen zu lösen, wodurch eine Teilproblemlösung, angebend einen Betriebsplan jedes Energieerzeugers, erhalten wird; und
• eine Finale-Lösung-Erwerbungseinheit, um einige Teilproblemlösungen aus einer Sammlung von Teilproblemlösungen für jede Energieerzeugergruppe zu extrahieren, um ein Finale-Lösung-Festlegungsproblem, das ein Optimierungsproblem ist für einen Fall, in dem jeder Energieerzeuger gemäß den einigen Teilproblemlösungen arbeitet, zu generieren auf Grundlage des Referenzproblems, und das Finale-Lösung-Festlegungsproblem zu lösen, wodurch eine finale Lösung, angebend den Betriebsplan jedes Energieerzeugers, erhalten wird.

An operational planning device according to the present invention has:

• a power generator group determination unit for dividing a plurality of power generators into a plurality of power generator groups;
• a partial problem solution acquisition unit for generating a partial problem, which is an optimization problem for setting an operation plan for one or more power producers belonging to each power generation group, in units of power generation groups, based on a reference problem, which is an optimization problem for setting an operation plan for the plurality of power generators, and to solve the partial problem in units of power generator groups, thereby obtaining a partial problem solution indicating an operation plan of each power generator; and
• a final solution acquiring unit to extract some partial problem solutions from a collection of partial problem solutions for each power producer group to generate a final solution fixing problem which is an optimization problem for a case where each power producer operates according to the some partial problem solutions basis of the reference problem, and to solve the final solution determination problem, thereby obtaining a final solution indicating the operation plan of each power producer.

Advantageous Effects of the Invention

According to the present invention, a final solution determination problem is generated using some partial problem solutions, and the final solution determination problem is solved to obtain a final solution of the operational planning. Since a sub-problem is generated in units of power generation groups, the sub-problem can be solved faster than a reference problem. Since the some partial problem solutions are used by the final solution fixing problem, the final solution fixing problem can be solved faster than the reference problem. In addition, a final solution can be obtained considering various constraint conditions corresponding to the remaining partial problem solutions. Therefore, it is possible to solve the operation planning problem at high speed and with high accuracy.

character list

• 1 1 is a configuration diagram of an operation planning system 200 in Embodiment 1.
• 2 10 is a configuration diagram of an operation scheduler 100 in Embodiment 1.
• 3 12 is a diagram showing a configuration of an operation planning unit 120 and a configuration of an optimization problem unit 140 in Embodiment 1. FIG.
• 4 Fig. 12 is a flowchart of an operation planning method in Embodiment 1.
• 5 12 is a flowchart of an acceptance process (S110) in Embodiment 1.
• 6 12 is a flowchart of an operation planning process (S120) in Embodiment 1.
• 7 12 is a hardware configuration diagram of the operation scheduler 100 in an embodiment.

Description of Embodiments

In one embodiment and the drawings, the same or equivalent element is denoted by the same reference number. A description of an element denoted by the same reference numeral as that of an explained element may be omitted or simplified as appropriate. Arrows in the drawings mainly represent data flows or process flows.

Embodiment 1.

An operational planning system 200 is described with reference to FIG 1 until 6 described.

The operation planning system 200 is a system for setting operation plans for a plurality of power producers.

*** Description of configurations ***

A configuration of an operational planning system 200 is described with reference to FIG 1 described.

The operation planning system 200 is equipped with a user terminal 210 and an operation planning device 100 .

The user terminal 210 is a computer that the user operates.

A concrete user is an operational personnel person of a power producer.

A specific example of a user terminal 210 is a personal computer, a tablet computer, or a smartphone.

The user terminal 210 communicates with the operation scheduler 100 via a network.

Specifically, the user terminal 210 transmits input data 211 to the operation planning device 100.

The input data 211 includes energy requirement data 212, energy generator configuration data 213 and energy generator characteristic data 214.

It should be noted that the power demand data 212, the power generator configuration data 213 and the power generator characteristic data 214 may be transmitted separately.

Contents of the power demand data 212, the power generator configuration data 213, and the power generator characteristic data 214 will be described later.

The operation planning device 100 functions as an operation planning server.

The operation planning device 100 generates operation plan data 201 based on the input data 211.

The operation plan data 201 is data indicating the operation plans of the plurality of power generators.

A configuration of the operation scheduler 100 is described with reference to FIG 2 described.

The operation planning device 100 is a computer equipped with hardware devices such as a processor 101 , a working memory 102 , an auxiliary storage device 103 , a communication device 104 and an input/output interface 105 . These hardware devices are connected to one another via a signal line.

The processor 101 is an IC to perform arithmetic processing and controls the other hardware devices. For example, the processor 101 is a CPU, a DSP, or a GPU.

• IC für Integrierte Schaltung steht;
• CPU für zentrale Verarbeitungseinheit steht;
• DSP für Digitaler Signalprozessor steht; und
• GPU für Grafikverarbeitungseinheit steht.

It should be noted that:

• IC stands for Integrated Circuit;
• CPU stands for central processing unit;
• DSP stands for Digital Signal Processor; and
• GPU stands for graphics processing unit.

Working memory 102 is a volatile storage device. The working memory 102 is also referred to as a main storage device or main memory. For example, memory 102 is RAM. Data stored in the work memory 102 is backed up in the auxiliary storage device 103 as needed.

Note that RAM stands for Random Access Memory.

The auxiliary storage device 103 is a non-volatile storage device. For example, the auxiliary storage device 103 is a ROM, an HDD, or a flash memory. The data stored in the auxiliary storage device 103 is loaded into the work memory 102 as needed.

It should be noted that ROM stands for Read-Only-Memory.

It should be noted that HDD stands for Hard Disk Drive.

More specifically, the communication device 104 is a receiver/transmitter. For example, the communication device 104 is a communication chip or NIC.

It should be noted that NIC stands for Network Interface Card.

The input/output interface 105 is a port to which an input device and an output device are connected. For example, the input/output interface 105 is a USB port, the input device is a keyboard/mouse, and the output device is a display.

It should be noted that USB stands for Universal Serial Bus.

The operation planning device 100 is equipped with elements such as an acceptance unit 110 , an operation planning unit 120 , an output unit 130 and the optimization problem unit 140 . These elements are implemented by software.

An operation planning program that causes the computer to function as the accepting unit 110, the operation planning unit 120, the output unit 130, and the optimization problem unit 140 is stored in the auxiliary storage device 103. FIG. The operational planning program is loaded into the main memory 102 and executed by the processor 101 .

Furthermore, an OS is stored in the auxiliary storage device 103 . At least a portion of the OS is loaded into memory 102 and executed by processor 101 .

The processor 101 executes the operation planning program while executing the OS.

It should be noted that OS stands for Operating System.

Input/output data of the operation planning program is stored in a storage unit 190 .

The working memory 102 functions as the storage unit 190. Note that a storage device such as the auxiliary storage device 103, a register in the processor 101, and a cache memory in the processor 101, instead of the working memory 102 or together with the working memory 102 as the Storage unit 190 can function.

The operational planning device 100 can be equipped with a plurality of processors that replace the processor 101 . The plurality of processors share a task of processor 101.

The operation planning program may be computer-readably recorded (stored) in a non-volatile recording medium such as an optical disk and a flash memory.

A configuration of the operation planning unit 120 and a configuration of the optimization problem unit 140 are described with reference to FIG 3 described.

The operation planning unit 120 is equipped with elements such as a preliminary solution acquisition unit 121 , a power generation group determination unit 122 , a partial problem solution acquisition unit 123 , and a final solution acquisition unit 124 . Functions of the elements equipped in the operation planning unit 120 will be described later.

The optimization problem unit 140 is equipped with elements such as a reference problem generation unit 141 and an optimization problem calculation unit 142 . Functions of the elements equipped in the optimization problem unit 140 will be described later.

*** Description of functional processes ***

A flow of operations of the operation planning device 100 corresponds to an operation planning method. Also, the flow of operations of the operation planner 100 corresponds to a flow of processing executed by the operation planning program.

The operation planning procedure is described with reference to 4 described.

In step S110, the acceptance unit 110 accepts the input data 211.

An acceptance process (S110) is described with reference to FIG 5 explained.

In step S111, the accepting unit 110 receives the input data 211 transmitted from the user terminal 210.

In step S112, the accepting unit 110 stores the received input data 211 in the storage unit 190.

Referring again to 4 the description proceeds from step S120.

In step S120, the operation planning unit 120 generates the operation plan data 201 based on the input data 211.

Details of an operation planning process (S120) will be described later.

The output unit 130 outputs the operation plan data 201 in step S130.

For example, the output unit 130 transmits the operation plan data 201 to the user terminal 210.

The operation planning process (S120) is described with reference to FIG 6 described.

In step S121, the operational planning unit 141 generates a reference problem based on the input data 211.

The reference problem is an optimization problem for deciding the operation schedule of the plurality of power producers, and includes a decision variable indicating whether or not each power producer is operating at each time point.

The input data 211 includes the energy requirement data 212, the energy generator configuration data 213 and energy generator characteristic data 214.

The energy demand data 212 is data indicating the energy demand.

Specifically, the energy demand data 212 indicates a predicted energy demand value for a scheduled runtime. The planned run time is a run time that is a target of the operation plan. The predicted power demand value expresses an amount of power to be generated by the plurality of power generators and is given per unit time.

If the operation schedules for a week from April 1 to April 7 are to be set hourly, the energy demand data 212 gives predicted energy demand values for 24 points in time (12:00 a.m., 1:00 a.m., ..., 11:00 p.m.) of each day from April 1 to April 7. April on.

The power generator configuration data 213 is data indicating configurations of the plurality of power generators.

Specifically, the power generator configuration data 213 indicates information such as the number of power generators and a relationship between the power generators. The relationship between the power generators is information that, for example, a fuel tank is shared, a reservoir of a pump storage hydro power generator is shared, and two or more power generators constitute a combined cycle power generator. The relationship between the energy producers is a basis for constraint conditions relating to two or more energy producers.

The power generator characteristic data 214 is data indicating a characteristic of each power generator.

Specifically, the power generator characteristic data 214 indicates information such as a type of power generator, a power generation efficiency, a minimum continuous operation time, the minimum continuous suspension time, an output upper limit value, an output lower limit value, and an output slew rate. The power generation efficiency is expressed by a function of a power generation amount and a fuel consumption amount.

The reference problem can be generated using an existing technique for generating an optimization problem. A process of generating the reference problem is not described.

In step S122, the tentative-solution acquiring unit 121 generates a tentative-solution setting problem based on the reference problem.

The tentative-solution setting problem is an optimization problem for a case where all of the plurality of power generators are working.

The tentative-solution acquiring unit 121 generates the tentative-solution setting problem as follows.

First, the preliminary solution acquiring unit 121 divides a plurality of decision variables included in the reference problem into a first decision variable group and a second decision variable group. A decision variable is a variable to be determined in operational planning is. A decision variable group consists of one or more decision variables.

The first set of decision variables indicates whether or not each individual power producer is operating at each point in time. The second decision variable group consists of all decision variables not included in the first decision variable group and indicates, for example, an output value (power generation amount) of each power generator at each time point.

Then, the tentative solution acquiring unit 121 assigns an operational status value to each decision variable included in the first decision variable group. The operation status value is a value indicating that the power generator is working.

In the tentative solution setting problem, a value of the first decision variable group is determined as a constraint condition. That is, the tentative solution setting problem is an optimization problem for setting a value of the second decision variable group.

Determining the value of the first set of decision variables reduces the number of decision variables to solve. Thus, the tentative solution determination problem can be solved relatively easily.

In step S123, the tentative-solution acquiring unit 121 solves the tentative-solution setting problem, thereby obtaining a tentative solution.

A preliminary solution gives an energy value for each energy generator.

Specifically, the tentative-solution acquiring unit 121 passes the tentative-solution setting problem to the optimization problem computing unit 142 and receives the tentative solution from the optimization problem computing unit 142. The optimization problem computing unit 142 receives the tentative-solution setting problem from the tentative- Solution acquisition unit 121 solves the preliminary solution determination problem and passes the preliminary solution to the preliminary solution acquisition unit 121 .

As a method for solving an optimization problem such as a tentative solution setting problem, any existing technique can be used.

For example, there is a method in which software, a so-called mathematical planning solver, is used. Many software titles are known as paid math planning solvers or free math planning solvers. An example of the paid mathematical planning solver is the Gurobi optimizer. Each mathematical programming solver is dedicated to a class optimization problem that it can solve. If the optimization problem calculation unit 142 uses an existing mathematical planning solver, the reference problem generation unit 141 generates an optimization problem (reference problem) of a class that the mathematical planning solver to be used can solve.

In step S124, the power generation group setting unit 122 divides the plurality of power generation groups into a plurality of power generation groups.

An overview of the grouping is described.

The power generator group setting unit 122 makes two or more power generators that cooperate with each other belong to the same power generator group based on the power generator configuration data 213.

The power generator group determination unit 122 divides the plurality of power generators into a plurality of power generator groups based on the power generator characteristic data 214 so that a characteristic of a power generator belonging to each power generator group does not vary between the power generator groups.

For example, the power generator group setting unit 122 divides the plurality of power generators into a plurality of power generator groups so that a power generation efficiency of a power generator belonging to each power generator group does not vary between the power generator groups.

The power generator characteristic data 214 indicates, for example, an output range of each power generator as a characteristic of that power generator. The output range is identified by an output lower limit and an output upper limit. Then, the power generator characteristic data 214 divides the plurality of power generators into a plurality of power generator groups based on an output value of each power generator indicated by the provisional solution obtained in step S123 and based on of the output range of each power generator indicated by the power generator characteristic data 214 . Specifically, the power generator group setting unit 122 divides the plurality of power generators into a plurality of power generator groups so that power generators each having an output value equal to an output lower limit value are distributed. The power producer group setting unit 122 also divides the plurality of power producers into a plurality of producer groups so that power producers each having an output value larger than an output lower limit value and smaller than an output upper limit value are divided.

The power generator characteristic data 214 indicates, for example, whether or not each power generator is suspended in the scheduled running time as a characteristic of each power generator. Then, the power producer group setting unit 122 divides the plurality of power producers into a plurality of power producer groups so that power producers suspended during the scheduled run time are distributed.

Details of the grouping are described.

The power generation group setting unit 122 performs grouping so that a first condition and a second condition are satisfied. Alternatively, grouping can also be performed in such a way that only the first condition is met.

According to the first condition, two or more energy producers that are to work in the network must belong to the same group. By satisfying the first condition, when the optimization problem is decomposed into units of power generation groups, the optimization problem becomes independent of the power generation groups. That is, the restriction condition does not relate to the plurality of power generation groups.

According to the second condition, the characteristics of the power generators belonging to each power generator group must be the same among the power generator groups. By satisfying the second condition, the accuracy of the operation plan is not degraded even if the optimization problem is decomposed into units of power generation groups.

Regarding the first condition, a concrete example of two or more power producers belonging to the same power producer group is given. In the concrete example of the first condition, the two or more power producers belonging to the same power producer group are referred to as a plurality of power producers.

A plurality of thermal energy generators share a fuel tank.

A large number of pumped storage hydroelectric generators share a reservoir.

A multiplicity of energy generators form a combined circuit energy generator.

A variety of energy producers form a must-run group. In the must-run group, a predetermined number of power generators or more must work constantly.

A large number of energy producers form a group whose upper limit value for the total output has been determined.

A large number of energy producers form a group whose upper limit value for total output has been determined.

A plurality of power generators form a group in which it is forbidden for two or more power generators to operate within a certain time interval.

A plurality of power generators form a group in which two or more power generators are forbidden to be exposed within a range of a certain time interval.

With regard to the second condition, a concrete example of the grouping is given.

The power generator group determination unit 122 distributes the power generators whose generation efficiencies are close to each other so that power generators whose generation efficiencies are close to each other are not concentrated in the same group. Concretely, it is defined that the smaller the first-order coefficient of a relational expression representing a relationship between a power generation amount and fuel cost of a power generator, the higher the power generation efficiency of a power generator. The energy producers are then assigned to the energy producer groups according to the round-robin scheme in ascending order of the coefficient values.

Regarding a power generator whose output value, which is a preliminary solution, is equal to the output lower limit value, if such a power generator is suspended and another power generator is working, it is likely clear that the efficiency improves. The power generator group determination unit 122 distributes power generators of such a type as not to be concentrated in the same group.

Regarding a power generator whose output value, which is a preliminary solution, is smaller than the output upper limit value and not equal to the output lower limit value, it is possible to transfer a load of a power generation amount from another power generator to such a power generator. That is, the power generation amount of such a power generator leaves much room for adjustment. The power generator group determination unit 122 distributes such power generators so that they are not concentrated in the same group.

Regarding a power generator known in advance to be suspended for a certain reason such as regular inspection during the scheduled run time, the power generator determination unit 122 distributes such power generators so that they are not concentrated in the same group .

By prioritizing the plurality of concrete examples mentioned above and combining the plurality of prioritized concrete examples, the characteristics of the power generators belonging to each power generator group can be made uniform among the power generator groups.

In step S125, the sub-problem acquiring unit 123 generates a sub-problem in sub-units of the power generation groups based on the reference problem.

The sub-problem is an optimization problem for setting an operation plan for one or more power producers belonging to each power producer group.

An outline of a sub-problem generation method will be explained.

The partial problem solution acquiring unit 123 sets a constraint condition for the partial problem in units of power generator groups based on the output value of each power generator indicated by the preliminary solution obtained in step S123.

For example, the partial problem solution acquisition unit 123 calculates a sum of output values of power generators belonging to each power generator group based on the output value of each power generator indicated by the preliminary solution in units of power generator groups. The sum to be calculated is referred to as a group requirement amount. Then, the sub-problem solution acquisition unit 123 adds the group demand amount to the constraint condition of the sub-problem in units of power generation groups.

For example, the partial problem solution acquisition unit 123 calculates the excess generated power of each power generator based on the output value of each power generator indicated by the provisional solution obtained in step S123. The excess generated energy is calculated by subtracting the output value (tentative solution) from the output upper limit value. Then, the partial problem solution acquisition unit 123 calculates a sum of surplus generated power of the power generators belonging to each power generator group. A calculated sum is called the excess group energy. Then, the partial problem solution acquisition unit 123 sets lower limit reserve power for each power generation group based on a ratio of group excess power between the power generation groups. The lower limit reserve power is a lower limit for the excess generated power. Then, the sub-problem solution acquisition unit 123 adds the lower limit reserve power to the constraint condition of the sub-problem in units of power generation groups.

A method of generating the sub-problem will be described in detail.

A sub-problem is generated in units of energy producer groups. By the determination regarding the plurality of power generator groups in step S124, some restriction conditions among restriction conditions related to the plurality of power generator groups are restricted to each power generator group. Some constraint conditions mean constraint conditions except for: a constraint condition given in the form of a required amount that should satisfy a sum of the output values of the plurality of power generators; and a constraint condition given in the form of a required amount that should satisfy a sum of calculation values such as reserve energies that can be calculated from each output value, respectively. Concretely, the constraint conditions to be excluded from some constraint conditions are a demand-satisfaction-balance constraint and a reserve power constraint. Therefore, each of the demand-demand-satisfaction-balance-in restriction and the reserve energy restriction can be broken down into units of energy production groups.

In order to decompose the demand-satisfaction-balance constraint into units of power generator groups, the partial problem solution acquisition unit 123 uses the output value of each power generator included in the preliminary solution obtained in step S123. Specifically, the partial problem solution acquisition unit 123 calculates a power generation amount to be generated by the power generation group by adding the output values of the power generators belonging to the power generation group in units of power generation groups. Then the amount of power generation to be generated by all power generation groups corresponds to the original power demand. This satisfies the demand-demand-satisfaction-equilibrium constraint. In addition, each power generation group can be assigned a power generation amount quota according to the capacity of each power generation group.

In order to decompose the reserve power constraint into units of power generator groups, the partial problem solution acquisition unit 123 uses the output value of each power generator included in the preliminary solution obtained in step S123. Concretely, the partial problem solution acquisition unit 123 calculates excess generated power in units of power generator groups by subtracting the output value of each power generator from the output upper limit value of each power generator. In addition, the partial problem solution acquisition unit 123 calculates group excess energy in units of power generation groups by adding the excess generated power of the power generators belonging to each individual power generation group. Then, the partial problem solution acquisition unit 123 sets the lower limit reserve power of each power generation group according to the group excess power ratio between the power generation groups. Thus, the reserve energy secured by all power generation groups (surplus generated energy) exceeds the original reserve energy. In addition, each power generation group can be assigned a reserve power quota according to the capacity of each power generation group.

In step S126, the partial problem solution acquisition unit 123 solves the partial problem in units of power generation groups, thereby obtaining a partial problem solution.

The partial problem solution specifies an operation plan for each energy producer.

Specifically, the partial problem solution acquisition unit 123 passes the partial problem to the optimization problem calculation unit 142 and receives the partial problem solution from the optimization problem calculation unit 142. The optimization problem calculation unit 142 receives the partial problem from the partial problem solution acquisition unit 123, solves the partial problem, and provides the partial problem solution the partial problem solution acquisition unit 123 continues.

In step S127, the final solution acquiring unit 124 extracts some partial problem solutions from a collection of partial problem solutions for each power generation group.

Specifically, the final solution acquiring unit 124 extracts a partial problem solution indicating whether or not each power producer is working at each time point from the collection of the partial problem solutions for each power producer group.

In step S128, the final solution acquisition unit 124 generates a final solution determination problem based on the reference problem and some partial problem solutions.

The final solution determination problem is an optimization problem for a case where each power producer works according to some partial problem solutions.

Specifically, the final solution setting problem is an optimization problem for the case where each power generator operates or is exposed according to the partial problem solution extracted in step S127.

A method of generating the final solution problem will now be described in detail.

The final solution acquisition unit 124 substitutes only one value of the first decision variable group out of all the sub-problem solutions for the reference problem. Thus, the final solution fixing problem can be obtained. That is, in the final solution determination problem, the value of the first decision variable group is determined as the constraint condition. Thus, the final solution setting problem is an optimization problem for setting a value of the second decision variable group. By fixing the value of the first decision variable group, a number of decision variables to solve is reduced. Therefore, the final solution determination problem can be solved relatively easily, as can the preliminary solution problem.

Note that the final solution acquisition unit 124 can use accumulation of all sub-problem solutions as the final solution. In this case a final solution fixing problem is not necessary.

In step S129, the final solution acquiring unit 124 solves the final solution setting problem, thereby obtaining a final solution.

The final solution gives the operation plan for each power generator.

Specifically, the final solution acquisition unit 124 outputs the final solution determination problem to the optimization problem calculation unit 142 and receives the final solution from the optimization problem calculation unit 142. The optimization problem calculation unit 142 receives the final solution problem from the from the final solution acquisition unit 124, solves the final solution problem and passes the final solution to the final solution acquisition unit 124.

*** Description of examples ***

The operation planning system 200 can be equipped with a variety of user terminals 210 .

The operation scheduler 100 can also serve as the user terminal 210 .

The input data 211 can be automatically entered into the operational planning device 100 from another system.

*** Effect of embodiment 1 ***

In Embodiment 1, the power generator groups can be set so that both requirements are satisfied, that is, all the different constraint conditions imposed on the individual power generators should be satisfied and a decrease in the approximation accuracy should be prevented. Then, the sub-problem is calculated in units of power generation groups, so that the operation plan can be obtained with high speed and high accuracy.

Embodiment 2.

A method of generating a preliminary solution setting problem and a method of setting a power generator group will be described mainly in terms of differences from Embodiment 1.

*** Description of configurations ***

A configuration of an operation planning system 200 is the same as the configuration in Embodiment 1 (see 1 until 3 ).

*** Description of functional processes ***

A process of an operation planning method is the same as the process in Embodiment 1 (see 4 until 6 ).

It should be noted that in step S122, a method of generating a preliminary solution determination problem differs from the method in Embodiment 1. Also, a new method of setting a power generation group is added to the method in Embodiment 1 in step S124.

An outline of the method of generating the tentative solution decision problem is explained.

First, a tentative solution acquisition unit 121 classifies the power generators into either operational power generators or suspension power generators. An operational power generator is a power generator that is operating at any point in time during a scheduled runtime. An intermittent energy producer is an energy producer that is suspended at any time during the scheduled runtime.

Specifically, the preliminary solution acquiring unit 121 selects one or more operational power generators from a plurality of power generators in descending order of power generation efficiency based on the power generator characteristic data 214 so that a total sum of output upper limit values of the one or more operational power generators is equal equal to or greater than the energy demand.

Then, the tentative-solution acquiring unit 121 generates a tentative-solution determination problem based on a reference problem.

The tentative solution determination problem is an optimization problem for a case where all of one or more working energy generators are working and all of one or more suspension energy generators are suspended.

Details of the method of generating the tentative solution determination problem will be explained.

First, the preliminary solution acquiring unit 121 divides a plurality of decision variables included in the reference problem into a first decision variable group and a second decision variable group.

Then, the tentative-solution acquiring unit 121 assigns an operation status value to a decision variable corresponding to one of the one or more operation power generators of the first decision variable group. The tentative-solution acquiring unit 121 assigns a decision variable an exposure status corresponding to each one of the one or more exposure energy generators of the first decision variable group. The suspension status value is a value that means that the power generator is suspended.

When setting a value of each decision variable included in the first decision variable group, the tentative solution acquiring unit 121 classifies a plurality of thermal energy producers between thermal energy producers that will be in the operating status at all times (operating energy producers) and thermal energy producers that are will be in the suspension status at all times (suspension energy generator). At this time, the preliminary solution acquiring unit 121 sets a classification so that a total sum of the outputted upper limit values of the thermal power generators that will be in the operating status at all times satisfies the maximum power demand in the scheduled runtime. The preliminary solution acquiring unit 121 also classifies one or more thermal power generators, in the descending order of power generation efficiency, as thermal power generators that will operate at all times. That is, thermal power generators classified as thermal power generators that will be in the suspension status at all times are those that have low power generation efficiency. In this way, the preliminary solution acquiring unit 121 sets a value of each decision variable included in the first decision variable group. Then, the preliminary solution acquiring unit 121 assigns the value of each decision variable included in the first decision variable groups to an optimization problem for setting an operation plan (reference problem). The post-substitution optimization problem is the preliminary solution fixing problem. In the tentative solution setting problem, the value of the first decision variable group is determined as the constraint condition. That is, the tentative solution setting problem is an optimization problem for setting a value of the second decision variable group.

The tentative solution determination problem generated in this way is not always executable. This is because there is a case where each thermal power generator that will be in the operating status at all times cannot reach an output value corresponding to an output upper limit value due to restriction of an output change speed or the like.

In view of this, when the temporary solution setting problem is not executable, the temporary solution acquiring unit 121 reclassifies a thermal energy generator having the highest energy generation efficiency among the one or more thermal energy generators classified as thermal energy generators located at all times in will be in the suspension status than heat energy generators, which will be in the operational status at all times. With this, the preliminary solution determination problem is updated. The tentative-solution acquiring unit 121 repeats updating of the tentative-solution setting problem until an executable tentative-solution setting problem is obtained.

The procedure of setting a power generation group will now be described.

The power generator group setting unit 122 divides the plurality of power generators into a plurality of power generator groups such that a number of suspension power generators belonging to each power generator group does not vary between the power generator groups.

That is, if there are a plurality of thermal power generators that will be in the suspension status at all times, the power generator group determination unit 122 distributes the thermal power generators that will be in the suspension status at all times so that the thermal power generators that are will be in suspension status at all times are not concentrated in the same group.

*** Effect of embodiment 2 ***

With embodiment 2, the same effect as with embodiment 1 can be obtained.

*** Supplement to the embodiments ***

A hardware configuration of the operation scheduler 100 is described with reference to FIG 7 described.

The operation scheduler 100 is equipped with a processing circuit 109 .

The processing circuit 109 is hardware that implements the acceptance unit 110, the operation planning unit 120, the output unit 130, and the optimization problem unit 140. FIG.

The processing circuitry 109 may be dedicated hardware or the processor 101 executing the program stored in the working memory 102 .

If the processing circuitry 109 is dedicated hardware, the processing circuitry 109 is, for example, a single circuit, a composite circuit, a programmed processor, a parallel-programmed processor, an ASIC, or an FPGA, or a combination of the enumerated elements.

It should be noted that ASIC stands for Application Specific Integrated Circuit.

Note that FPGA stands for Field Programmable Gate Array.

The operation scheduler 100 may be equipped with a variety of processing circuits replacing the processing circuit 109 . The plurality of processing circuits share a task of the processing circuit 109.

In the operational scheduler 100, some of the functions may be implemented by dedicated hardware and the remaining functions may be implemented by software or firmware.

In this manner, processing circuitry 109 may be implemented by hardware, software, or firmware; or implemented by a combination of hardware, software, and firmware.

The embodiments are examples of a preferred embodiment, and the technical scope of the present invention should not be limited thereby. Each embodiment can also be implemented only partially, or can be implemented in combination with another embodiment. A process described using a flowchart or the like may be changed as necessary.

The operation scheduler 100 can be implemented by a variety of devices.

A "unit" that is an element of the operation scheduler 100 can be read as "process" or "stage".

Reference List

100

operations planning facility;

101

Processor;

102

Random access memory;

103

auxiliary storage device;

104

communication facility;

105

input/output interface;

109

processing circuit;

110

acceptance unit;

120

operational planning unit;

121

temporary solution acquisition unit;

122

power generation group determination unit;

123

partial problem solving acquisition unit;

124

final solution acquisition unit;

130

output unit;

140

optimization problem unit;

141

reference problem generation unit;

142

optimization problem calculation unit;

190

storage unit;

200

operational planning system;

210

user terminal;

211

input data;

212

energy demand data;

213

energy producer configuration data;

214

power generator characteristic data.

QUOTES INCLUDED IN DESCRIPTION

This list of documents cited by the applicant was generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Patent Literature Cited

• JP 2018106431A [0013]

Claims (17)

Operational planning facility, comprising: a power generator group determination unit for dividing a plurality of power generators into a plurality of power generator groups; a partial problem solution acquisition unit for generating a partial problem, which is an optimization problem for setting an operation plan for one or more power producers belonging to each power generation group, in units of power generation groups, based on a reference problem, which is an optimization problem for setting an operation plan for the plurality of power generators, and to solve the partial problem in units of power generator groups, thereby obtaining a partial problem solution indicating an operation plan of each power generator; and a final solution acquiring unit to extract some partial problem solutions from a collection of partial problem solutions for each power producer group to generate a final solution fixing problem which is an optimization problem for a case where each power producer operates according to the some partial problem solutions basis of the reference problem, and to solve the final solution determination problem, thereby obtaining a final solution indicating the operation plan of each power producer. operational planning facility claim 1 wherein the power generator group setting unit causes two or more power generators that cooperate with each other to belong to the same power generator group based on power generator configuration data indicating configurations of the plurality of power generators. operational planning facility claim 1 or 2 , wherein the power generator group determination unit divides the plurality of power generators into the plurality of power generator groups based on the power generator characteristic data indicating a characteristic of each power generator such that a characteristic of a power generator belonging to each power generator group does not vary between the power generator groups. operational planning facility claim 3 , wherein the power generator group setting unit divides the plurality of power generators into the plurality of power generator groups such that a power generation efficiency of a power generator belonging to each power generator group does not vary between the power generator groups. operational planning facility claim 3 or 4 , wherein the power generator characteristic data indicates an output range of each power generator as a characteristic of that power generator, wherein the operation planning means includes a tentative solution acquiring unit for determining a tentative solution setting problem, which is an optimization problem for a case where all of the plurality of Power generators operate to generate based on the reference problem and to solve the temporary solution setting problem, thereby obtaining a temporary solution indicative of an output value of each power generator, and wherein the power generator group setting unit divides the plurality of power generators into the plurality of power generator groups based on the output value of each power generator indicated by the provisional solution and based on the output range of each power generator indicated by the power generator characteristic data. operational planning facility claim 5 wherein the power generator characteristic data indicates an output range of each power generator as a characteristic of that power generator, wherein the operational planning means comprises a preliminary solution acquisition unit for classifying the plurality of power generators between one or more operational power generators and one or more suspension power generators, to generate a preliminary solution setting problem based on a reference problem, the preliminary solution setting problem being an optimization problem for a case where all of the one or more operational energy generators are working and all of the one or more exposure energy generator(s), and solving the preliminary solution setting problem, thereby obtaining a preliminary solution indicative of an output value of each power generator, and wherein the power generator group setting unit selects the plurality of power generators ern divided into the plurality of power generator groups based on the output value of each power generator indicated by the preliminary solution and based on the output range of each power generator indicated by the power generator characteristic data. operational planning facility claim 6 , wherein the power generator characteristic data is a Specify power generation efficiency of each power generator as a characteristic of each power generator, and wherein the tentative solution acquiring unit selects the one or more operation power generators from the plurality of power generators in a descending order of power generation efficiency such that a total sum of output upper limit values of the one or more Operating energy generator / generators is equal to or greater than the energy requirement. operational planning facility claim 6 or 7 , wherein the power generator group setting unit divides the plurality of power generators into the plurality of power generator groups such that a number of suspension power generators belonging to each power generator group does not vary between the power generator groups. Operational planning device according to one of Claims 5 until 8th , wherein the power generator group setting unit divides the plurality of power generators into the plurality of power generator groups so that power generators each having an output value equal to an output lower limit value are distributed. Operational planning device according to one of Claims 5 until 9 wherein the power generator group setting unit divides the plurality of power generators into the plurality of generator groups so that power generators each having an output value greater than an output lower limit value and smaller than an output upper limit value are distributed. Operational planning device according to one of Claims 5 until 10 , wherein the power generator characteristic data indicates whether or not each power generator is suspended in a scheduled running time as a characteristic of each power generator, and the power generator group setting unit divides the plurality of power generators into the plurality of power generator groups so that power generators operating during the scheduled term are suspended. operational planning facility claim 1 1 . comprising a tentative-solution acquiring unit for generating a tentative-solution setting problem, which is an optimization problem for a case where all of the plurality of power generators work, based on the reference problem, and solving the tentative-solution setting problem , whereby a provisional solution indicating an output value of each energy producer is obtained, wherein the partial problem solution acquiring unit sets a constraint condition for the partial problem in units of energy producer groups based on the output value of each energy producer indicated by the provisional solution. operational planning facility claim 12 , wherein the partial problem solution acquisition unit calculates a sum of output values of power generators belonging to each power generator group based on the output value of each power generator indicated by the preliminary solution as a group demand quantity in units of power generator groups and the group demand quantity to the constraint condition of the sub-problem in Added units of energy producer groups. operational planning facility claim 12 or 13 , wherein the partial problem solution acquisition unit calculates excess generated power of each power generator, based on the output value of each power generator indicated by the provisional solution, a sum of the excess generated power of the power generators belonging to each power generator group, as group surplus power, lower limit reserve power, the is a lower limit of the group excess power, sets for each power generation group based on a ratio of the group excess power among the power generation groups, and adds the lower limit reserve power to the constraint condition of the sub-problem in units of power generation groups. Operational planning device according to one of Claims 1 until 14 , wherein the final solution acquiring unit extracts a partial problem solution indicating whether or not each power producer works at each time point from a collection of partial problem solutions for each power producer group, and generates an optimization problem for a case where each power producer works or is suspended according to the extracted partial problem solution, as the final solution fixing problem. An operation planning method comprising: by a power generation group determination unit, dividing a plurality of power generation groups into a plurality of power generation groups; by a partial problem solution acquiring unit, generating a partial problem which is an optimization problem for setting an operation plan for one or more power producers belonging to each power producer group in units of power producer groups based on a Refe renzproblems, which is an optimization problem for setting an operation plan for the plurality of power generators, and solving the partial problem in units of power generator groups, thereby obtaining a partial problem solution indicating an operation plan of each power generator; and by a final solution acquiring unit, extracting some partial problem solutions from a collection of partial problem solutions for each power producer group, generating a final solution fixing problem, which is an optimization problem for a case where each power producer operates according to the some partial problem solutions, based on the reference problem, and solving the final solution determination problem, thereby obtaining a final solution indicating the operation plan of each power producer. Operational scheduling program that causes a computer to run: a power generation group setting process of dividing a plurality of power generation groups into a plurality of power generation groups; a partial problem solving acquisition process of generating a partial problem that is an optimization problem for setting an operation plan for one or more power producers belonging to each power producer group in units of power producer groups based on a reference problem that is an optimization problem for setting an operation plan for the plurality of power producers , and solving the partial problem in units of power generator groups, thereby obtaining a partial problem solution indicating an operation plan of each power generator; and a final solution acquisition process of extracting some partial problem solutions from a collection of partial problem solutions for each power producer group, generating a final solution fixing problem, which is an optimization problem for a case where each power producer operates according to the some partial problem solutions, based on the reference problem , and solving the final solution setting problem, thereby obtaining a final solution indicative of the operation plan of each power producer.

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