JP2014192904A - Power system management device and method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To try stabilized operation of a system by calculating an optimum state quantity of a power system, depending on the configuration or the state of a power system, which varies by region, and the need of an operator.SOLUTION: A power system management device for managing the system state in a power system comprises: a partial system setting unit for classifying into more than one partial system based on the system information acquired from a power system, an objective function setting unit for setting one or more than one objective function in a partial system set in the partial system setting unit; a partial system calculation unit for determining the system state of the partial system; and a priority setting unit for setting the weighting on the basis of the priority of each partial system. The power system management device determines the system state of the power system on the basis of the system state of more than one partial system determined in the partial system calculation unit, and the weighting set in the priority setting unit.

Description

  The present invention relates to a power system management apparatus and method for managing a system state in order to support operation of a power system.

  When a large amount of natural energy that causes steep power fluctuations due to changes in the climate or the environment is introduced into the power system, it becomes difficult to stably control the system. In addition, when a large number of devices that control the fluctuation are introduced into the power system, the control configuration becomes complicated, and it becomes difficult to control in accordance with the characteristics of the plurality of control devices. Furthermore, due to changes in the business system such as the liberalization of electric power and the separation of dispatched power, a plurality of business operators manage and operate the power system, making collective management and control of the power system even more difficult.

  In view of this, an optimization control technique has been devised for a business operator who operates the power system as described above to stabilize the system. For example, in Patent Document 1, although a plurality of power systems are related to each other in operation, control is performed so as to satisfy each control target independently, and an objective function for system operation is improved. Therefore, the purpose is to comprehensively handle and optimize a plurality of power system control operations. For this reason, the state of the power system is evaluated based on the system state quantity, the objective function is changed, the state change is dealt with, the target function value is displayed together with the weight value of each operation task, and human It can be corrected based on the judgment. In addition, multi-objective optimization has a partial order relationship, and is intended to optimize a single objective function (integrated objective function) obtained by applying a weight to the multi-objective function.

JP-A-7-250431

  However, in the technique described in Patent Document 1, the objective function is not set for each individual power system, and power system control considering power system characteristics for each region, in particular, the amount of introduction for each region. In power system control that takes into account variations in different natural energies and distributed power sources, control that reflects the operator's intention is difficult.

  An object of the present invention is to calculate the optimum amount of state of the power system according to the configuration and state of the power system that varies from region to region and the needs of the operator, and to stabilize the operation of the system.

  In order to solve the above-described problems, the present invention provides a partial system setting unit that classifies two or more partial systems based on system information acquired from the power system in a power system management apparatus that manages a system state in the power system. And an objective function setting unit that sets one or more objective functions in the partial system set by the partial system setting unit, and a system of the partial system based on the objective function set by the objective function setting unit A partial system calculation unit for obtaining a state, and a priority setting unit for setting a weight based on a priority for each partial system, the system state of two or more partial systems obtained by the partial system calculation unit, and The system state of the electric power system is obtained based on the weight set by the priority setting unit.

  ADVANTAGE OF THE INVENTION According to this invention, it becomes possible to calculate the optimal amount of state of an electric power system according to the structure and state of an electric power system which differ for every area, and an operator's needs.

It is a block diagram which shows the function block diagram of this electric power system management apparatus. It is an example of a block diagram of the electric power system management system which concerns on this invention. It is an example of the flowchart of the whole process of this electric power system management apparatus. It is an example of the data structure of the system characteristic information used as the input / output of this electric power system management apparatus. It is an example of the data structure of the partial system | strain information used as the input / output of this electric power system management apparatus. It is an example of the data structure of the objective function information used as the input / output of this electric power system management apparatus. It is an example of the data structure of the system state information used as the input / output of this electric power system management apparatus.

  Hereinafter, preferred examples for carrying out the present invention will be described. It should be noted that the following is merely an example of implementation and is not intended to limit the invention itself to the following specific contents.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 shows a functional configuration diagram of a power system management apparatus to which an embodiment of the present invention is applied. As shown in FIG. 1, the power system management apparatus according to the present embodiment includes a system state calculation unit 10 and an information storage unit 20.

  The system state calculation unit 10 includes a partial system setting unit 11, an objective function setting unit 12, a partial state calculation unit 13, a priority setting unit 14, and an overall state calculation unit 15. The

  The partial system setting unit 11 classifies the power system for calculating the state into a plurality of partial systems, and determines which partial system the system elements such as the generator, the phase adjusting device, and the transmission line that configure the power system belong to. The information is stored in the system characteristic information storage unit 21. A sub-system is defined using the amount or rate of introduction of a distributed power source to be linked, controllability information on generators and phase adjusting devices, power status monitoring availability information, possible power flow fluctuations or voltage fluctuations, etc. . The partial system to which the system element belongs is determined by comparing the partial system classification information stored in the partial system information storage unit 22 with the system information stored in the system characteristic information storage unit 21 and the system state information storage unit 24. Is determined by

  The objective function setting unit 12 sets an objective function for each partial system determined by the partial system setting unit 11. The set objective function is stored in the objective function information storage unit 23. At this time, a plurality of objective function candidates may be stored in the objective function information storage unit 23, and the weight of each objective function may be set for each partial system.

  The partial state calculation unit 13 uses the objective function corresponding to each partial system set in the objective function setting unit 12 to calculate the system state for each partial system.

  The priority setting unit 14 sets weighting based on the priority for each partial system.

  The overall state calculation unit 15 uses the system state for each partial system calculated by the partial state calculation unit 13 and the priority weight for each partial system set by the priority setting unit 14 to use the system state of the power system. Is calculated.

  Note that the priority can be set by another index in addition to setting based on the measurement or estimation accuracy of the system state of the partial system described later.

  The information storage unit 20 includes a system characteristic information storage unit 21, a partial system information storage unit 22, an objective function information storage unit 23, and a system state information storage unit 24.

  The system characteristic information storage unit 21 stores characteristic information of system elements that do not vary with variations in power generation amount, load amount, and the like.

  FIG. 2 is a configuration diagram of a power system management system to which an embodiment of the present invention is applied. As shown in FIG. 2, the power system management system in the present embodiment includes a generator 101, a substation 102, a phase adjusting device 103, a power load 104, an external power system 105, a control monitoring device 106, The monitoring apparatus 107, the information communication network 108, and the electric power system management apparatus 200 are comprised.

  The generator 101 is a generator that generates electric power, and is a generator that generates electric power by any one of power generation methods including thermal power generation, hydroelectric power generation, nuclear power generation, solar power generation, wind power generation, biomass power generation, and tidal current power generation. is there. The generator 101a is a large-scale generator including thermal power generation, hydroelectric power generation, nuclear power generation and the like installed on the high voltage side of the power system, and the state quantity including the power generation amount is transmitted through the control monitoring device 106 and the information communication network 108. It transmits to the electric power system management apparatus 200. Moreover, the generator 101a receives the control command information transmitted from the power system management device 200 through the control monitoring device 106 and the information communication network 108, and changes the state quantity including the power generation amount according to the control command information. The generator 101b is a small-scale generator including solar power generation, wind power generation, cogeneration, etc. installed on the low voltage side of the power system, and the state quantity including the power generation amount is obtained through the monitoring device 107 and the information communication network 108. It transmits to the electric power system management apparatus 200.

  The substation 102 is installed between transmission lines in the power system, changes the voltage value of the power transmitted from the high voltage side where the generator 101a which is a large-scale generator is installed, and the power load 104 is installed. Power is transmitted to the low voltage side. The substation 102 is connected to a phase adjusting device 103 such as a power capacitor or a shunt reactor.

  The phase adjusting device 103 is a device that controls the voltage distribution in the power system by changing reactive power in the power system, and includes a power capacitor, a shunt reactor, STATCOM, SVC, and the like. Some phase adjusting devices 103 receive the control command information transmitted from the power system management device 200 through the control monitoring device 106 and the information communication network 108, and change the state quantity including the power generation amount according to the control command information. .

  The electric power load 104 represents a home, factory, building, or facility that includes an electric motor, a lighting device, or the like that consumes electric power.

  The external power system 105 is an external power system that cannot be controlled from the power system management apparatus 200, and is connected to the own system through a connection line.

  The control monitoring device 106 includes sensors for measuring state quantities such as the power generation amount in the generator 101a and the phase adjustment amount in the phase adjusting device 103, and the power system management device 200 through the information communication network 108 with the measured state quantities. Send to. Further, the control monitoring device 106 receives control command information transmitted from the power system management device 200 through the information communication network 108, and generates power in the generator 101a and phase adjustment amount in the phase adjusting device 103 in accordance with the control command information. Change the state quantity.

  The monitoring device 107 includes sensors for measuring state quantities such as power flow values and voltage values in the power transmission line, and transmits the measured state quantities to the power system management apparatus 200 through the information communication network 108.

  The information communication network 108 is a network capable of transmitting data in both directions. The information communication network 108 is configured by, for example, a wired network, a wireless network, or a combination thereof. The information communication network 108 may be a so-called Internet or a dedicated line network.

  The power system management apparatus 200 is an apparatus for realizing the power system management function shown in FIG. The power system management apparatus 200 receives the state quantities measured by the control monitoring apparatus 106 and the monitoring apparatus 107 through the information communication network 108. In addition, the power system management apparatus 200 transmits control command information calculated using the transmitted state quantity of the system and information stored therein to the control monitoring apparatus 106 through the information communication network 108.

  As an internal configuration of the power system management device 200, a CPU (Central Processing Unit) 201, a display device 202, a communication unit 203, an input unit 204, a memory 205, and a storage device 206 are connected to a bus line 211. ing. The CPU 201 executes a calculation program to calculate a system state, generate a control signal, and the like. The memory 205 is a memory that temporarily stores display image data, system state calculation result data, and the like, and is configured using, for example, a RAM (Random Access Memory). The memory 205 generates necessary image data by the CPU 201 and displays it on the display device 202. The communication unit 203 acquires state quantities such as a power flow value and a voltage value from the control monitoring device 106 and the monitoring device 107 through the communication network 108.

  The user can set and change parameters such as various thresholds through a predetermined interface of the input unit 204, and can appropriately set the operation of the power system management apparatus 200. In addition, the user can select a type of data to be confirmed through a predetermined interface of the input unit 204 and can display the data on the display device 202.

  The storage device 206 holds various programs and data. The storage device 206 is configured by, for example, an HDD (Hard Disk Drive) or a flash memory. The storage device 206 holds, for example, programs and data that can realize various functions to be described later. Programs and data stored in the storage device 206 are read out and executed by the CPU 201 as necessary. The storage device 206 is composed of various databases DB.

  Next, the system state calculation process of the power system in the power system management apparatus 200 will be described using the flowchart shown in FIG.

  First, a partial system is set for the power system to be controlled. (S31) At this time, the power system is classified using the partial system classification condition stored in the partial system information storage unit 22, and the system elements such as the generator, the phase adjusting device, and the transmission line constituting the power system are identified. Decide if it belongs to a partial system. As sub-system classification conditions, the amount of natural energy introduced, the rate of introduction of natural energy with respect to the power load, the power generation amount prediction accuracy of natural energy, the amount of power flow change in the power system, or the amount of voltage change in the power system It is desirable to include at least one of them. By selecting this condition as the setting condition for the partial system, the system is classified according to the amount of tidal current fluctuation or voltage fluctuation that is difficult to control, monitor, and predict due to natural energy or distributed power sources. It is possible to calculate a system state in which different objective functions are set.

  Next, an objective function is set for each partial system set in S31. (S32) At this time, the amount of introduction of natural energy, the introduction rate of natural energy with respect to the power load, the accuracy of power generation prediction of natural energy, the amount of change in tidal current in the power system, or the power selected as the partial system classification condition When the value is large for at least one of the voltage changes in the system, it is desirable to increase the weight of the objective function for maximizing the stability. By doing this, when the amount of power flow fluctuation or voltage fluctuation that is difficult to control, monitor, or predict due to natural energy or distributed power source is large, the system status is calculated to increase the system stability. It becomes possible to do. In addition, when the amount of fluctuation in power flow or the amount of voltage fluctuation is small, it is possible to calculate a desirable system state for other objective functions by increasing the weight of the objective function other than the stability maximization. For example, by increasing the weight of the objective function for minimizing the fuel cost, it becomes possible to operate the system economically.

Next, the system state based on the objective function set in S32 is calculated for each partial system. (S33) At this time, the state quantity of the controllable system element is varied for each partial system, and a solution of the state quantity that makes the objective function set in S32 minimum or maximum is searched. Here, when the weight of the objective function fk in the sub-system pn is set to wnk and the vector of the state quantity that can be controlled in the sub-system pn is set to xn, the value calculated from the following (Equation 1) is used as the objective function. A solution of the state quantity xn that minimizes the objective function is calculated for the subsystem pn.
Σwnk × fk (xn) (Formula 1)

  As a specific method, it is desirable to use any of linear programming, nonlinear programming, interior point method, genetic algorithm, evolutionary programming, tabu search, neural network, and PSO. Furthermore, a solution that can be realized as a state of the entire system can be calculated by obtaining a solution in consideration of the constraint condition in the interconnection line between the partial systems. This is to adjust the tidal flow flowing through the interconnection line in the system state calculated for p11 and the system state calculated for p12 when there is an interconnection line connecting the partial system p11 and the partial system p12. .

  Next, the priority for each partial system is set. (S34) At this time, as the priority setting condition for each partial system, measurement or estimation accuracy of the system state of the partial system from the power system management device, controllability of the partial system, or the like is desirable. This is because a more accurate system state can be calculated by setting the weight of a system that can be controlled or monitored under this setting condition to be large and the weight of a system that is difficult to control or monitor to be small.

Next, the overall system state is calculated using the system state for each partial system calculated in S33 and the weight for each partial system set in S34. (S35) Here, the partial systems are p1, p2,..., The system state for each partial system calculated in S33 is xn, and the weights based on the priorities for each partial system set in S34 are W1, W2,.・ ・ When the weight of the objective function fk in the sub-system pn is set to wnk, the solution Xn that minimizes the objective function for the entire target power system is calculated using the value calculated from the following equation as the objective function To do. As a specific solution searching method, the method mentioned in the description of S33 is used.
Σ [pn × {Σwnk × (fk (xn) −fk (Xn))] (Equation 2)

  By calculating the system state of the entire power system using the above mathematical formula, the state change from the system state of each partial system calculated in S33 is small, and in particular, the partial system in which the weight of each partial system is set large is S33. It is possible to calculate the system state of the entire system so that the state change from the system state of each partial system calculated in (2) is reduced. Therefore, it is possible to calculate a system state that minimizes the deviation from the operator's needs by weighting each partial system while considering the operator's intention expressed by the objective function set for each partial system. .

  FIG. 4 shows an example of the data structure of the system characteristic information.

  FIG. 4A shows an example of node information indicating information on nodes in the power system, and generators, power loads, and phase adjusting devices connected to each node. In the example of FIG. 4 (a), a generator is linked to nodes A and B, node A has a thermal power generator with a rated capacity of 100 named G1, and node B has a name G2. It shows that a wind power generator with a rated capacity of 200 is linked. In the example of FIG. 4 (a), a power load is connected to nodes with names AA and BB, a node AA has a rated capacity of 1000 named L1, and node BB has a name L2. This shows that factories with a rated capacity of 2000 are linked. In the example of FIG. 4 (a), a phase adjusting device is linked to nodes named AAA and BBB, and SC (power capacitor) having a rated capacity of 10 named D1 is connected to node AAA. The BBB shows that a ShR (shunt reactor) with a rated capacity of 20 named D2 is connected.

  FIG. 4B shows an example of transmission line information indicating the characteristics of the transmission line in the power system. In the example of FIG. 4 (b), there is a transmission line with the name a between the node A and the node B, the positive phase resistance is 0.01, the positive phase reactance is 0.2, and the positive phase capacitance is 0.1. Yes.

  FIG.4 (c) has shown an example of the constraint condition about the system | strain element in an electric power grid | system. In the example of FIG. 4C, the first constraint condition indicates that the maximum value is 100 and the minimum value is 10 for the effective power generation amount of the generator G1. Further, the phase adjustment amount of the phase adjuster D1 indicates that the maximum value is 10 and the minimum value is 0. Similarly, the maximum value of the power flow rate a is 500.

  Here, the data configuration shown in FIGS. 4A, 4B, and 4C is an example, and more detailed system characteristic information may be stored. For example, dynamic characteristics such as a governor constant may be stored as information on nodes to which the thermal power generator of FIG. Moreover, even if stochastic power generation amount fluctuation characteristics calculated by statistical analysis using past history are stored as information on nodes to which generators by natural energy such as the wind power generator of FIG. good. Moreover, dynamic characteristics such as the maximum output change speed may be stored as a constraint condition as a constraint condition regarding the generator of FIG.

  The partial system information storage unit 22 stores information on partial systems having different system characteristics.

  FIG. 5 shows an example of the data structure of the partial system information.

  FIG. 5A shows an example of classification conditions when setting a partial system. In the example of Fig. 5 (a), the classification name P1 classifies the system according to the amount of power generation equipment introduced by natural energy, and for the partial system p11, the introduction quantity is larger than the threshold E1 and the partial system p12 It is defined as a partial system whose introduction amount is smaller than the threshold value E1 and equal to or larger than the threshold value E2.

  In addition, the classification name P2 classifies the system with the state monitoring accuracy from the own system, and the partial system p21 defines what is determined to be easy to monitor from the own system from the measurement results and the measurement frequency, On the other hand, the partial system p22 defines a case where it is determined that the measurement accuracy is low due to the absence of measurement means or the communication environment is bad, and that monitoring from the own system is difficult.

  FIG. 5B shows which partial system each system element belongs to the system elements included in the system characteristic information illustrated in FIGS. 4A and 4B. In the example shown in FIG. 5B, the generator G1, the power load L1, and the phase adjusting device D1 connected to the node A belong to the partial system p11, and the transmission line a belongs to the partial system p12. A case where two or more partial systems correspond to one system element is also conceivable.

  The objective function information storage unit 23 stores information related to the objective function. The objective function is a mathematical expression of the operator's intention when calculating the system state.

  FIG. 6 shows an example of the data structure of the objective function information.

  FIG. 6A is an example of a data configuration showing the objective function candidates set in advance. In the example of FIG. 6A, the objective function O1 indicates the operator's intention to minimize the fuel cost, and by minimizing the mathematical formula f1 (x1) representing the fuel cost with the power generation amount x1 as an input. , Calculate the system status according to the operator's intention. Similarly, the objective function O2 indicates the operator's intention to maximize the voltage stability, and the mathematical expression f2 (x1, x2,...) Representing the voltage stability with the voltage x1, the tidal flow x2,.・ ・) By maximizing the system state, the system state in line with the operator's intention is calculated. As objective function candidates, it is desirable to store fuel cost minimization, power transmission loss minimization, system stability maximization, phase adjusting device operation frequency minimization, and the like.

  FIG. 6B is an example of a data configuration showing the weight of the partial system (priority) and the weight of the objective function set for each partial system. In the example of FIG. 6B, when the classification P2 is selected, the weight for each partial system is p21 is 1 and p22 is 0.6. The weight of the objective function is the weight of the objective function O1 in the partial system p21. 80, the weight of the objective function O2 is 20,..., And in the sub-system p22, the weight of the objective function O1 is 100, the weight of the objective function O2 is 0,. Here, the weight of the objective function is determined in consideration of the characteristics of the partial system. For example, when a large amount of natural energy power is introduced into the target partial system, the stability of the system tends to decrease. Therefore, the weight of the objective function for maximizing the stability is increased for the sub-system with a large amount of introduction of renewable energy power, and the stability for the sub-system with a small amount of introduction of renewable energy power. It is possible to reduce the weight of the objective function for maximizing. Further, the weights of the partial systems are determined by comparing the measurement accuracy of each partial system. For example, if there are a large number of power sensors installed in the local grid, it is possible to grasp the status relatively accurately, or conversely, because there are only a few power sensors installed in the grid, it is relatively difficult to grasp the status. It may be accurate. In such a case, if the objective function can be accurately evaluated, the weight of the partial system may be set large, and if the evaluation of the objective function becomes inaccurate, the weight of the partial system may be set small. As a result, the optimum state quantity of the entire power system in accordance with the purpose of the operator can be obtained.

  The system state information storage unit 24 stores state amount information of system elements linked to the power system. The state quantity includes the power generation amount in the generator, the phase adjustment amount in the phase adjusting device, the tidal flow in the transmission line, and the like.

  FIG. 7 shows an example of the data structure of the system state information.

  In the example shown in FIG. 7, the state quantities of the generator G1, the phase adjusting device D1, and the transmission line a are stored. The information stored for the generator G1 is the amount of power generated, and the past statistical information of peak time and bottom time, measurement information, partial calculation results, and overall calculation results are stored.

  Here, the past statistical information in the example of FIG. 7 is a value calculated by statistically processing the value of the state quantity measured in the sensor installed on the power system or in the device that is the system element at the past time point. In the example of FIG. 7, a plurality of measured state quantities at a plurality of past points in time regarding a peak time at which the power load is maximum in one day and a state quantity at the bottom time at which the power load is minimum in one day. Is stored as a result of statistical processing such as averaging. Here, a value subjected to statistical processing in which more detailed conditions are set may be stored. For example, with respect to the state quantities in the time zone every hour of the day, statistical processing may be performed, and 24 values may be stored for one system element. Furthermore, in order to reflect the variation of the state quantity for each season and for each month in the power system control, a value subjected to statistical processing for each season and for each month may be stored.

  Moreover, the measurement information in the example of FIG. 7 is the value of the state quantity measured in the sensor installed in the apparatus which is an electric power system or a system element.

  Moreover, the partial calculation result in the example of FIG. 7 is the value of the state quantity in the system state calculated using the objective function for each partial system, calculated by the partial state calculation unit 13 of the power system management apparatus 200.

  In addition, the overall calculation result in the example of FIG. 7 is the state in the system state calculated for the entire system using the weight for each partial system based on the priority calculated in the overall state calculation unit 15 of the power system management apparatus 200. It is a quantity value.

DESCRIPTION OF SYMBOLS 10 System state calculation part 11 Partial system | strain setting part 12 Objective function setting part 13 Partial state calculation part 14 Priority setting part 15 Overall state calculation part 20 Information storage part 21 System characteristic information storage part 22 Partial system | strain information storage part 23 Objective function information Storage unit 24 System state information storage unit 101 Generator 102 Substation 103 Phase adjusting device 104 Distributed generator 105 External power system 106 Control monitoring device 107 Monitoring device 108 Information communication network 200 Power system management device

Claims (10)

In the power system management device that manages the system state in the power system,
Based on system information acquired from the power system, a partial system setting unit for classifying into two or more partial systems, and an objective function setting for setting one or more objective functions in the partial system set by the partial system setting unit A sub-system calculation unit that obtains a system state of the partial system based on the objective function set by the objective function setting unit, and a priority setting unit that sets weighting based on the priority for each partial system And
An electric power system management apparatus that obtains a system state of the electric power system based on a system state of two or more partial systems obtained by the partial system calculation unit and a weight set by the priority setting unit. In the power system management device according to claim 1,
The partial system calculation unit weights the objective function set by the objective function setting unit,
A power system management apparatus for obtaining a system state of the partial system. In the electric power system management apparatus in any one of Claim 1 or 2,
The power system management apparatus according to claim 1, wherein the objective function includes one or more of functions related to fuel cost, power transmission loss, system stability, and control device operation frequency. In the electric power system management apparatus according to claim 1,
The priority includes information based on measurement or estimation accuracy of a system state of the partial system. In the electric power system management apparatus according to claim 1,
The partial system setting unit includes a natural energy introduction amount, a natural energy introduction rate with respect to a load, a natural energy generation amount prediction accuracy, a power flow change amount in a power system, a voltage change amount in a power system, and the power system management. A power system management apparatus, wherein the power system is classified into two or more partial systems based on information including at least one of controllability of the apparatus and availability of status monitoring of the power system management apparatus. In the electric power system management apparatus according to claim 1,
Furthermore, the power system management apparatus provided with the communication part which acquires the information containing the system state in an electric power system. In the electric power system management apparatus according to claim 1,
A power system management apparatus that transmits a control command to a control device of the power system based on a system state of the power system determined by the power system management apparatus. In the electric power system management apparatus according to claim 1,
The power system management apparatus further comprises a display unit that displays a system state of the power system obtained by the power system management apparatus. In the electric power system management apparatus according to claim 1,
The partial system calculation unit uses a method including any of linear programming, nonlinear programming, interior point method, genetic algorithm, evolutionary programming, tabu search, neural network, PSO, and the objective function setting unit. A power system management apparatus for obtaining a system state of a partial system that minimizes or maximizes a set objective function. In the power system management method for managing the system state in the power system,
Based on the system information acquired from the power system, the step of classifying into two or more partial systems, the step of setting one or two or more objective functions in the partial system, and based on the objective function, A step of obtaining a system state; a step of setting a weight based on a priority for each of the partial systems; a step of obtaining a system state of the power system based on the system states of the two or more partial systems and the weighting A power system management method comprising: