Integrated energy system scheduling method based on master-slave game

Abstract

The invention discloses an integrated energy system scheduling method based on a master-slave game, and belongs to the field of integrated energy system scheduling. The method comprises the following steps: step 1, constructing an integrated energy system architecture; 2, establishing a comprehensive energy system model, and regulating and controlling each component in the system by using the comprehensive energy system model; 3, establishing a master-slave game framework; and step 4, solving game equilibrium. According to the method, the operation efficiency and reliability of the system can be effectively improved, and high robustness is shown in the aspect of coping with different load fluctuations and energy price changes.

Description

Technical Field

[0001] The present invention relates to the field of integrated energy system scheduling, and particularly to an integrated energy system scheduling method based on master-slave game. Background Art

[0002] Integrated Energy Systems (IES) is an important development direction in the modern energy field. It aims to improve the overall efficiency, reliability, and economy of the energy system through the coupling and coordinated optimization of multiple energy forms. Traditional energy systems usually operate independently, such as power systems, natural gas systems, and thermal systems. Integrated energy systems break this isolation state, integrate multiple energy forms such as electricity, heat, cold, and gas, and achieve multi-energy complementarity and coordinated optimization. This integration can not only make full use of renewable energy resources, but also improve energy utilization efficiency, reduce energy costs, and reduce environmental pollution.

[0003] The core of the integrated energy system is the coordinated and optimized scheduling of multiple energy forms. Through the coordinated control of each energy subsystem in the system (such as photovoltaic power generation system, wind power generation system, gas turbine, energy storage system, etc.), the optimal allocation of energy can be achieved to meet various load demands. At the same time, the integrated energy system also involves complex issues such as multi-energy flow, multi-time and space scales, and multi-agent interactions, requiring advanced optimization scheduling technologies to ensure the stability and economy of the system.

[0004] Game Theory is a theoretical framework for studying the behavior of decision-makers under different strategies and their mutual influences. Since its birth, Game Theory has been widely applied in fields such as economics, political science, military strategy, and engineering. In recent years, with the increasing complexity of integrated energy systems, the application of Game Theory in this field has received more and more attention and research.

[0005] In an integrated energy system, different energy subsystems and participants (such as energy producers, consumers, energy storage system operators, etc.) often have different goals and constraints. This diversification of demands and goals makes it difficult for traditional centralized optimization scheduling to meet the multi-agent decision-making needs. Summary of the Invention

[0006] The technical problem to be solved by the present invention is mainly an integrated energy system scheduling method based on master-slave game, which improves the energy system efficiency, reduces the operating cost, and enhances the system stability.

[0007] An integrated energy system scheduling method based on master-slave game includes the following steps:

[0008] Step 1: Construct the integrated energy system architecture;

[0009] Step 2: Establish an integrated energy system model and use the integrated energy system model to regulate each component within the system;

[0010] Step 3: Establish a master - slave game framework;

[0011] Step 4: Solve the game equilibrium.

[0012] Preferably, the construction of the integrated energy system architecture includes the following parts: an energy production and conversion unit, an energy transmission and distribution network, an energy consumption unit, an energy management and control system, and information and communication technology facilities.

[0013] Preferably, Step 2: Establish an integrated energy system model, including:

[0014] Solar Photovoltaic (PV): Convert solar energy into electrical energy through photovoltaic panels;

[0015] P PV = η PV ·A PV ·G T

[0016] Where P PV is the power generation power of the photovoltaic system, η PV is the conversion efficiency of the photovoltaic panel, A PV is the area of the photovoltaic panel, G T is the solar radiation intensity;

[0017] Wind energy: Convert wind energy into electrical energy through wind turbines;

[0018]

[0019] Where P W is the wind power generation power, ρ is the air density, A is the swept area of the wind turbine, v is the wind speed, C p is the power coefficient;

[0020] Gas Turbine (GT): Generate electricity and heat by burning natural gas;

[0021]

[0022] Where P GT is the power generation power of the gas turbine, η GT is the gas turbine efficiency, is the natural gas flow rate, LHV NG is the lower heating value of natural gas;

[0023] Coal - fired power plant: Generate electricity by burning coal;

[0024]

[0025] Among them, P Coal is the power generation capacity of a coal-fired power plant, and η Coal is the efficiency of a coal-fired power plant, is the coal flow rate, and LHV Coal is the lower heating value of coal;

[0026] Nuclear power: Electricity is generated through nuclear reactions;

[0027] P Nuclear = η Nuclear ·Q Nuclear

[0028] Among them, P Nuclear is the nuclear power generation capacity, η Nuclear is the efficiency of a nuclear power plant, and Q Nuclear is the thermal energy generated by nuclear reactions;

[0029] Combined heat and power (CHP) system: Electricity and heat are generated simultaneously;

[0030]

[0031] Among them, η CHP is the efficiency of the combined heat and power system, P CHP is the power generation capacity of the CHP system, and Q CHP is the heat supply of the combined heat and power system, is the fuel flow rate, and LHV Fuel is the lower heating value of the fuel;

[0032] Combined cooling, heat and power (CCHP) system: Electricity, heat and cooling are generated simultaneously;

[0033]

[0034] Among them, η CCHP is the efficiency of the combined cooling, heat and power system, P CCHP is the power generation capacity of the combined cooling, heat and power system, and Q CCHP is the heat supply of the combined cooling, heat and power system, and C CCHP is the cooling supply of the combined cooling, heat and power system;

[0035] Energy storage devices: Include heat accumulators, cold accumulators and battery energy storage;

[0036] E Storage = E In - E Out - Loss

[0037] Among them, E Storage is the energy storage capacity of the energy storage device, E In is the input energy, and E OutOutput energy, Loss is the energy lost during the energy storage process;

[0038] Power grid: for the transmission and distribution of electricity;

[0039] P Load = P Generation - P Loss

[0040] Wherein, P Load is the load demand power, P Generation is the power generation power, P Loss is the transmission loss;

[0041] Thermal network: for the transmission and distribution of heat energy;

[0042] Q Load = Q Generation - Q Loss

[0043] Wherein, Q Load is the heat load demand, Q Generation is the heat energy generation, Q Loss is the transmission loss;

[0044] Cold energy network: for the transmission and distribution of cold energy;

[0045] C Load = C Generation - C Loss

[0046] Wherein, C Load is the cold load demand, C Generation is the cold energy generation, C Loss is the transmission loss;

[0047] Natural gas pipeline network: for the transmission and distribution of natural gas;

[0048] NG Load = NG Supply - NG Loss

[0049] Wherein, NG Load is the natural gas demand, NG Supply is the natural gas supply, NG Loss is the transmission loss;

[0050] Energy consumption of residential users: for power supply, heat supply and cold supply to households;

[0051] E Residential = P Electricity + Q Heat + C Cooling

[0052] Among them, E Residential is the energy demand of residential users, P Electricity is the electricity demand, Q Heat is the heat demand, and C Cooling is the cooling energy demand;

[0053] Energy consumption of commercial users: It is the electricity, heat, and cooling energy demands of commercial buildings and office buildings;

[0054] E Commercial = P Electricity + Q Heat + C Cooling

[0055] Among them, E Commercial is the energy demand of commercial users, P Electricity is the electricity demand, Q Heat is the heat demand, and C Cooling is the cooling energy demand;

[0056] Energy consumption of industrial users: It is the various energy demands in the industrial production process;

[0057] E Industrial = P Electricity + Q Heat + C Cooling + NG Fuel

[0058] Among them, E Industriai is the energy demand of industrial users, P Electricity is the electricity demand, Q Heat is the heat demand, C Cooling is the cooling energy demand, and NG Fuel is the natural gas demand.

[0059] Preferably, it further includes:

[0060] Central Energy Management System (EMS): It is used for global energy scheduling and optimization;

[0061] C Total = ∑(C Generation + C Transmission + C Storage + C Consumption )

[0062] Among them, C Total is the total system cost, C Generation is the power generation cost, C Transmission is the transmission cost, C Storage is the energy storage cost, and C Consumption is the consumption cost;

[0063] Distributed Energy Management System (DEMS): Used for energy management in a region or a local area;

[0064] C Local = ∑(C LocalGeneration + C LocalTransmission + C LococalStorage + C LocalConsumption )

[0065] where C Local is the total cost of the local system, C LocalGeneration is the local power generation cost, C LocalTransmission is the local transmission cost, C LocalStorage is the local energy storage cost, C LocalConsumption is the local consumption cost;

[0066] Intelligent Metering and Monitoring System: Used for real-time monitoring of the operating status and energy consumption of each energy unit.

[0067] Preferably, in step 3, the main problem is to minimize the system cost:

[0068]

[0069] where

[0070] C Leader : the total cost of the system (to be minimized), C Generation (t): the cost of power generation at time t, C Transmission (t): the electricity at time t

[0071]

[0072] where P Generation (t): the power generation power at time t; the discharge power of the energy storage system at time t; the charging power of the energy storage system at time t; P Load (t): the load demand power at time t;

[0073]

[0074] where SOC BESS (t): the state of the energy storage system at time t; the minimum allowable state of the energy storage system; the maximum allowable state of the energy storage system;

[0075] P Loss (t) ≤ P Generation (t) · η Transmission ,

[0076] where P Loss(t): Transmission loss power at time t; η Transmission : Efficiency of power transmission.

[0077]

[0078] Preferably, in step 3, the problem is a local optimal scheduling:

[0079]

[0080] Wherein, Total cost of the i-th subsystem; Local power generation cost of the i-th subsystem at time t; Local consumption cost of the i-th subsystem at time t;

[0081]

[0082] Wherein, Local power generation power of the i-th subsystem at time t; Local energy storage discharge power of the i-th subsystem at time t; Local energy storage charging power of the i-th subsystem at time t; Local load demand power of the i-th subsystem at time t;

[0083]

[0084] Wherein, Energy storage state of the i-th subsystem at time t; Minimum allowable state of the energy storage system of the i-th subsystem; Maximum allowable state of the energy storage system of the i-th subsystem;

[0085]

[0086] Wherein, Local load demand of the i-th subsystem at time t; f i (·): Represents the function relationship between the local load and the system power generation P G eneration(t) and the energy storage system discharge P B ESS out (t).

[0087] Preferably, in step 4, the master-slave game solution process:

[0088] 1): Initialization, determine the initial state and parameters of the system; initialize the variables of the master problem and the slave problem;

[0089] 2): Solve the sub-problem. Given the decision variables of the main problem, solve the sub-problem; obtain the optimal solution of the sub-problem as the response of the sub-problem to the main problem.

[0090] 3): Update the main problem. Based on the response of the sub-problem, update the variables and constraints of the main problem.

[0091] Solve the main problem to obtain a new optimal solution.

[0092] 4): Iterative solution. Pass the new optimal solution of the main problem to the sub-problem.

[0093] Repeat steps 2) and 3) until the solutions of the main and sub-problems converge to achieve game equilibrium.

[0094] Preferably, the objective function of the main problem is:

[0095]

[0096] Preferably, the objective function of the sub-problem is:

[0097]

[0098] Preferably, the solutions of the main and sub-problems satisfy the following equilibrium conditions:

[0099]

[0100] Among them, represents the partial derivative with respect to the variable. Here, it is for P Generation′ and calculate the gradient of the objective function; P Generation : The decision variable of the power generation power in the global system, which is optimized by the main problem; The decision variable of the charging power of the energy storage system; The decision variable of the discharging power of the energy storage system; λ is the Lagrange multiplier used to connect the main problem and the sub-problem.

[0101] Beneficial effects:

[0102] The integrated energy system scheduling method based on master-slave game disclosed in the present invention solves the complex problems in the collaborative optimal scheduling of multi-energy systems. By constructing a multi-objective optimization model of the integrated energy system, it covers the supply-demand balance of various energy forms such as electricity and heat. The master-slave game theory is adopted to decompose the complex optimization problem into multiple sub-problems. The master problem is responsible for the global optimization of the system, while the slave problems optimize each subsystem respectively. Through the strategic interaction in game theory, the master and slave problems are solved alternately, and finally the global optimal scheduling of the integrated energy system is achieved. The method of the present invention can effectively improve the operation efficiency and reliability of the system, and shows strong robustness in dealing with different load fluctuations and energy price changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0103] Figure 1 It is the daily power curve of the embodiment of the present invention;

[0104] Figure 2 It is the electric load curve before and after demand response of the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0105] In order to describe the present invention more specifically, the present invention will be further described below in conjunction with the drawings and specific implementation cases.

[0106] An integrated energy system scheduling method based on master-slave game includes the following steps:

[0107] Step 1: Construct the integrated energy system architecture.

[0108] The integrated energy system (IES) is a system that collaboratively optimizes the management of various energy forms such as electricity, heat, cold energy, and natural gas. Its main objectives are to improve energy utilization efficiency, reduce carbon emissions, enhance the flexibility and reliability of the system, and analyze the energy production and conversion units, energy transmission and distribution networks, and energy consumption units in the integrated energy system.

[0109] The construction of the integrated energy system architecture includes the following parts:

[0110] Energy production and conversion units, including renewable energy such as solar photovoltaic, wind energy, geothermal energy, etc.; traditional energy such as gas turbines, coal-fired power plants, nuclear power, etc.; energy conversion equipment such as combined heat and power (CHP) systems, combined cooling, heating and power (CCHP) systems, heat accumulators, cold accumulators, battery energy storage, etc.

[0111] Energy transmission and distribution networks, including power networks for power transmission and distribution; heat networks for heat energy transmission and distribution; cold energy networks for cold energy transmission and distribution; natural gas pipelines responsible for natural gas transmission and distribution.

[0112] Energy consumption units, including residential users, which have household power supply, heating, cooling, etc.; commercial users, which have power, heat, and cooling energy demands in commercial buildings and office buildings; and industrial users, which have various energy demands during the industrial production process.

[0113] Energy management and control systems, including a central energy management system (EMS) for global energy scheduling and optimization; a distributed energy management system (DEMS) for regional or local energy management; and an intelligent metering and monitoring system for real-time monitoring of the operating status and energy consumption of each energy unit.

[0114] Information and communication technology (ICT) facilities: including a network for collecting the operating data of each part of the energy system; communication equipment for data transmission and instruction sending; and a big data and cloud computing platform for data storage, analysis, and processing.

[0115] Optionally, the market and policy environment, including energy markets such as the electricity market and natural gas market, which provide price signals and trading platforms; and policies and regulations, which are the energy policies and regulations formulated by the government and affect the operation and development of the integrated energy system.

[0116] The integrated energy system architecture realizes the efficient utilization of energy, the minimization of costs, and the reduction of environmental impacts through the complementarity and coordination of various energy forms, and the coordinated operation of each part realizes the optimized operation of the integrated energy system.

[0117] Step 2: Establish an integrated energy system model and use the integrated energy system model to regulate each component within the system.

[0118] Including: The energy production and conversion unit includes renewable energy, traditional energy, and energy conversion equipment. Solar photovoltaic (PV): Converts solar energy into electrical energy through photovoltaic panels.

[0119] P PV =η PV ·A PV ·G T

[0120] Where P PV is the power generation power of the photovoltaic system, η PV is the conversion efficiency of the photovoltaic panel, A PV is the area of the photovoltaic panel, and G T is the solar radiation intensity.

[0121] Wind energy: Converts wind energy into electrical energy through wind turbines.

[0122]

[0123] Where PW where \(P\) is the wind power generation, \(\rho\) is the air density, \(A\) is the swept area of the wind turbine, \(v\) is the wind speed, and \(C\) p is the power coefficient.

[0124] Gas turbine (GT): Generates electricity and heat by burning natural gas.

[0125]

[0126] where \(P\) GT is the power generation of the gas turbine, \(\eta\) GT is the efficiency of the gas turbine, is the natural gas flow rate, and \(LHV\) NG is the lower heating value of natural gas.

[0127] Coal-fired power plant: Generates electricity by burning coal.

[0128]

[0129] where \(P\) Coal is the power generation of the coal-fired power plant, \(\eta\) Coal is the efficiency of the coal-fired power plant, is the coal flow rate, and \(LHV\) Coal is the lower heating value of coal.

[0130] Nuclear power: Generates electricity through nuclear reactions.

[0131] \(P\) Nuclear =\(\eta\) Nuclear \(\cdot Q\) Nuclear

[0132] where \(P\) Nuclear is the nuclear power generation, \(\eta\) Nuclear is the efficiency of the nuclear power plant, and \(Q\) Nuclear is the heat energy generated by the nuclear reaction.

[0133] Combined heat and power (CHP) system: Generates electricity and heat simultaneously.

[0134]

[0135] where \(\eta\) CHP is the efficiency of the CHP system, \(P\) CHP is the power generation of the CHP system, \(Q\) CHP is the heat supply of the CHP system, is the fuel flow rate, and \(LHV\) Fuel is the lower heating value of the fuel.

[0136] Combined cooling, heat and power (CCHP) system: Generates electricity, heat and cooling simultaneously.

[0137]

[0138] Among them, η CCHP is the efficiency of the combined heat and power (CHP) system, P CCHP is the power generation of the CHP system, Q CCHP is the heat supply of the CHP system, C CCHP is the cooling supply of the CHP system.

[0139] Energy storage device: including a heat accumulator, a cold accumulator and a battery energy storage.

[0140] E Storage = E In - E Out - Loss

[0141] Among them, E Storage is the energy storage of the energy storage device, E In is the input energy, E Out is the output energy, and Loss is the energy lost during the energy storage process.

[0142] Power grid: used for the transmission and distribution of electricity.

[0143] P Load = P Generation - P Loss

[0144] Among them, P Load is the load demand power, P Generaton is the power generation, P Loss is the transmission loss.

[0145] Thermal network: used for the transmission and distribution of heat energy.

[0146] Q Load = Q Generation - Q Loss

[0147] Among them, Q Load is the heat load demand, Q Generation is the heat energy generation, Q Loss is the transmission loss.

[0148] Cold energy network: used for the transmission and distribution of cold energy.

[0149] C Load = C Generation - C Loss

[0150] Among them, C Load is the cold load demand, C Generation is the cold energy generation, C Loss is the transmission loss.

[0151] Natural gas pipeline network: used for the transmission and distribution of natural gas.

[0152] NG Load = NG Supply - NG Loss

[0153] Wherein, NG Load is the natural gas demand, NG Supply is the natural gas supply, NG Loss is the transmission loss.

[0154] Energy consumption of residential users: for power supply, heating, cooling, etc. in households.

[0155] E Residential = P Electricity + Q Heat + C Cooling

[0156] Wherein, E Residential is the energy demand of residential users, P Electricity is the electricity demand, Q Heat is the heat demand, C Cooling is the cold energy demand.

[0157] Energy consumption of commercial users: for electricity, heat, and cold energy demands in commercial buildings and office buildings.

[0158] E Commercial = P Electricity + Q Heat + C Cooling

[0159] Wherein, E Commercial is the energy demand of commercial users, P Electricity is the electricity demand, Q Heat is the heat demand, C Cooling is the cold energy demand.

[0160] Energy consumption of industrial users: for various energy demands in the industrial production process.

[0161] E Industrial = P Electricity + Q Heat + C Cooling + NG Fuel

[0162] Wherein, E Industrial is the energy demand of industrial users, P Electricity is the electricity demand, Q Heat is the heat demand, C Cooling is the cold energy demand, NG Fuel is the natural gas demand.

[0163] Central Energy Management System (EMS): Used for global energy scheduling and optimization.

[0164] C Total = ∑(C Generation + C Transmission + C Storage + C Consumption )

[0165] Where C Total is the total system cost, C Generation is the power generation cost, C Transmission is the transmission cost, C Storage is the energy storage cost, C Consumption is the consumption cost.

[0166] Distributed Energy Management System (DEMS): Used for regional or local energy management.

[0167] C Local = ∑(C LocalGeneration + C LocalTransmission + C LococalStorage + C LocalConsumption )

[0168] Where C Local is the total local system cost, C LocalGenmeration is the local power generation cost, C LocalTransmission is the local transmission cost, C LocalStorage is the local energy storage cost, C LocalConsumption is the local consumption cost.

[0169] Intelligent Metering and Monitoring System: Used to monitor the operating status and energy consumption of each energy unit in real time.

[0170] Through the coordinated operation of the above architecture, the integrated energy system can achieve the efficient utilization of various energy forms, minimize the operating cost, and reduce the environmental impact. The optimization and coordination of each component are the key to achieving the overall goals of the system.

[0171] Step 3: Establish a leader-follower game framework.

[0172] The leader-follower game framework is a method used in game theory to solve hierarchical optimization problems. In the integrated energy system scheduling, the leader-follower game framework can effectively decompose complex optimization problems. The main problem is globally optimized by the leader, and the subordinate problem is locally optimized by the follower.

[0173] The main problem is the responsibility of the system operator or the dispatch center, and the goal is the optimal scheduling of the global system.

[0174]

[0175] Among them,

[0176] C Leader : The total cost of the system (to be minimized), C Generation (t): The cost of power generation at time t, C Transmission (t): The electricity at time t

[0177]

[0178] Among them, P Generation (t): The power generation power at time t; The discharge power of the energy storage system at time t; The charging power of the energy storage system at time t; P Load (t): The load demand power at time t.

[0179]

[0180] Among them, SOC BESS (t): The state of the energy storage system at time t; The minimum allowable state of the energy storage system; The maximum allowable state of the energy storage system.

[0181]

[0182] Among them, P Loss (t): The transmission loss power at time t. η Transmission : The efficiency of power transmission.

[0183]

[0184] The problem is the responsibility of each subsystem or user, and the goal is the local optimal scheduling of each system.

[0185]

[0186] Among them, The total cost of the i-th subsystem. At time t, the local power generation cost of the i-th subsystem. At time t, the local consumption cost of the i-th subsystem.

[0187]

[0188] Among them, At time t, the local power generation power of the i-th subsystem. At time t, the local energy storage discharge power of the i-th subsystem. The local energy storage charging power of the i-th subsystem at time t. The local load demand power of the i-th subsystem at time t.

[0189]

[0190] Where, The energy storage state of the i-th subsystem at time t. The minimum allowable state of the energy storage system of the i-th subsystem. The maximum allowable state of the energy storage system of the i-th subsystem.

[0191]

[0192] Where, The local load demand of the i-th subsystem at time t. f i (·): Represents the function relationship between the local load and the system power generation P G eneration(t) and the energy storage system discharge P B ESS out (t).

[0193] The following is the solution process of the master-slave game:

[0194] 1): Initialization, determine the initial state and parameters of the system. Initialize the variables of the master problem and the slave problem.

[0195] 2): Solve the slave problem, given the decision variables of the master problem, solve the slave problem. Obtain the optimal solution of the slave problem as the response of the slave problem to the master problem.

[0196] 3): Update the master problem, based on the response of the slave problem, update the variables and constraints of the master problem.

[0197] Solve the master problem to obtain a new optimal solution.

[0198] 4): Iterative solution, transfer the new optimal solution of the master problem to the slave problem.

[0199] Repeat steps 2) and 3) until the solutions of the master and slave problems converge to reach the game equilibrium.

[0200] The objective function of the master problem is:

[0201]

[0202] The objective function of the slave problem is:

[0203]

[0204] The solutions of the master and slave problems must satisfy the following equilibrium conditions:

[0205]

[0206] Among them, represents the partial derivative with respect to the variable, here for P Generation′ and calculate the gradient of the objective function; P Generation : The decision variable of the power generation power in the global system, which is optimized by the master problem; The decision variable of the charging power of the energy storage system. The decision variable of the discharging power of the energy storage system; λ is the Lagrange multiplier used to connect the master problem and the slave problem.

[0207] Step 4: Solve the game equilibrium. Use the genetic algorithm, an optimization algorithm, to solve the above master-slave game problem.

[0208] The objective of the master problem is to minimize the total cost of the system while satisfying all constraints. Assume the objective function of the master problem is C Leader , and the constraint condition is C' Leader .

[0209] Minimize C Leader

[0210] Subject to C' Leader

[0211] KKT conditions: Solve the Karush-Kuhn-Tucker (KKT) conditions to find the solution that satisfies all KKT conditions.

[0212]

[0213] Among them, represents that the gradient of the objective function or the Lagrangian function with respect to the decision variable x is zero, that is, it satisfies the first-order optimality condition. g i (x) = 0: Represents the i equality constraints in the problem. h j (x) ≤ 0: Represents the j inequality constraints in the problem; λ i ≥ 0 and μ j ≥ 0: The non-negativity conditions of the Lagrange multipliers λ i and μ j . The non-negativity condition of λ i g i (x) = 0 and μ j h j (x) = 0: Means that if a certain constraint is not binding, the corresponding Lagrange multiplier is zero.

[0214] The objective of the problem is to minimize the total cost of the system while satisfying all constraints. Assume the objective function of the problem is C Follower , and the constraints are

[0215] Minimize C Follower

[0216] Subject to C' Follower

[0217] In the leader-follower game, the solution to the leader-follower problem needs to satisfy the Nash equilibrium condition.

[0218]

[0219]

[0220] where x i represents the strategy of the i-th participant, and x-i represents the strategies of the other participants.

[0221] In the leader-follower game, the Stackelberg equilibrium means that the leader selects the strategy that maximizes its payoff given the response of the follower.

[0222]

[0223]

[0224] where C i (x i , x -i ): represents the objective function of the i-th participant. arg min: represents finding the parameter value that minimizes the objective function. represents for all i.

[0225] Determine the follower's response strategy: Solve the follower's problem to find the optimal solution of the follower's problem given the leader's strategy x L .

[0226] Construct the leader's objective function: Substitute the follower's response strategy into the leader's objective function to obtain a new objective function

[0227] where represents the optimal strategy combination of the follower obtained by solving the follower's problem given the leader's strategy x L .

[0228] Solve the leader's problem: Optimize the new objective function to find the optimal strategy

[0229] Verify the equilibrium condition: Check whether the strategies of the leader and the follower satisfy the Stackelberg equilibrium condition, that is, the leader's strategy is the strategy that maximizes its payoff, and the follower's strategy is the optimal response to the leader's strategy.

[0230] The genetic algorithm is a heuristic algorithm based on natural selection and genetic mechanisms, suitable for solving global optimization problems. It iteratively optimizes the objective function through selection, crossover, and mutation operations.

[0231] The steps are as follows:

[0232] Initialize the population: Randomly generate the initial population, where each individual represents a feasible solution.

[0233] Evaluate the fitness: Calculate the fitness of each individual, that is, the objective function value.

[0234] Selection operation: Select individuals according to the fitness to form a new population.

[0235] Crossover operation: Perform crossover operations on the selected individuals to generate new individuals.

[0236] Mutation operation: Perform mutation operations on the individuals after crossover to introduce randomness.

[0237] Update the population: Replace part of the old population with the newly generated individuals.

[0238] Check for convergence: If the preset number of iterations is reached or the change in population fitness is less than the threshold, stop the iteration.

[0239] Case study, including: Create a specific integrated energy system model and use the aforementioned optimization algorithm to solve and analyze it.

[0240] Set up an integrated energy system that includes the following components: renewable energy (solar and wind), traditional energy (gas turbine), energy storage system (battery), and electrical load.

[0241] Write a scheduling program for the integrated energy system in MATLAB. The steps are as follows: Initialize the parameters and system status of each component. Calculate the power generation of solar and wind energy. Select the genetic algorithm to solve the above optimization problem.

[0242] Figure 1This is the daily power curve, which shows the 24-hour variations of photovoltaic prediction, wind turbine prediction, electrical load, and thermal load. The photovoltaic power generation increases significantly during the day (approximately from 6:00 to 18:00), especially reaching its peak at noon (approximately from 12:00 to 14:00). The wind turbine prediction has two obvious power generation peaks in the morning (approximately from 7:00 to 10:00) and in the evening (approximately from 19:00 to 22:00), while the power generation is relatively low during the remaining time periods. The electrical load exhibits a double-peak characteristic throughout the day, with two peaks in the morning (approximately from 7:00 to 10:00) and in the evening (approximately from 18:00 to 22:00). The thermal load is relatively stable throughout the day, but it slightly increases in the morning (approximately from 6:00 to 10:00) and in the evening (approximately from 18:00 to 22:00). From this graph, it can be seen that the power generations of photovoltaic and wind turbine have significant fluctuations, which are respectively affected by solar radiation and wind speed changes. The electrical load and thermal load are closely related to people's daily life schedules and show certain regularities. The dispatching of the integrated energy system needs to fully consider these changes to achieve efficient utilization of energy and balance of load. In this way, the energy supply can be optimized, energy waste can be reduced, and the reliability and economy of the system can be improved.

[0243] Figure 2 This is the electrical load curve before and after demand response, which shows the variations of the electrical load before optimization, the electrical load after optimization, and the load curtailment amount within 24 hours. The electrical load before optimization exhibits significant fluctuations throughout the day, especially with two obvious peaks in the morning and evening. The morning peak appears around 8:00, and the evening peak appears around 20:00, indicating that the electricity demand is very high during these time periods. Between 12:00 and 16:00 at noon, the electrical load is relatively stable but still high. The electrical load after optimization is smoother compared to that before optimization, especially significantly reduced during the peak hours. The electrical load after optimization drops significantly during the peak hours (around 8:00 and 20:00), indicating that the optimization process effectively reduces the peak load. The electrical load after optimization slightly increases during the low-load periods (such as early morning), which helps to achieve a smooth transition of the load. The load curtailment amount shows the amount of electrical load curtailed per hour. It can be seen from the graph that the load curtailment amount is the largest during the morning and evening peak hours, corresponding to the load difference before and after optimization. This indicates that significant load curtailment measures are taken during the peak hours to reduce the grid pressure and improve the power supply stability. Generally speaking, through optimized dispatching, the integrated energy system can achieve effective management of the load, improve the stability and economy of the power supply system, and provide more reliable and efficient energy services for users.

[0244] The present invention discloses a dispatching method for an integrated energy system based on master-slave game, so as to solve the complex problems in the collaborative optimal dispatching of multi-energy systems. First, the present invention constructs a multi-objective optimization model for the integrated energy system, covering the supply-demand balance of various energy forms such as electricity and heat. Then, the master-slave game theory is adopted to decompose the complex optimization problem into multiple sub-problems. The master problem is responsible for the global optimization of the system, while the slave problems optimize each subsystem respectively. Through the strategy interaction in game theory, the master and slave problems are solved alternately, and finally the global optimal dispatching of the integrated energy system is achieved. The simulation experimental results show that this method can effectively improve the operation efficiency and reliability of the system, and shows strong robustness in dealing with different load fluctuations and energy price changes.

Claims

1. A method for scheduling an integrated energy system based on master-slave game, characterized in that: The following steps are involved: Step 1: Build an integrated energy system architecture; Step 2: Establish an integrated energy system model and use it to regulate each component of the system; Step 3: Establish a master-slave game framework; Step 4: Solve the game equilibrium.

2. The method according to claim 1, characterized in that The integrated energy system architecture includes the following parts: energy production and conversion units, energy transmission and distribution networks, energy consumption units, energy management and control systems, and information and communication technology facilities.

3. The method according to claim 1, characterized in that Step 2: Build a comprehensive energy system model, including: Solar Photovoltaic (PV): Converting solar energy into electricity through photovoltaic panels; P PV =the PV ·A PV ·G T Among them, P PV is the power generated by the photovoltaic system, η PV is the conversion efficiency of the photovoltaic panel, A PV is the photovoltaic panel area, G T is the solar radiation intensity; Wind energy: converting wind energy into electricity through wind turbines; Among them, P W is the wind power, ρ is the air density, A is the rotor swept area, v is the wind speed, C p is the power coefficient; Gas turbine (GT): produces electricity and heat by burning natural gas; Among them, P GT is the power generated by the gas turbine, η GT is the gas turbine efficiency, is the natural gas flow rate, LHV NG is the lower calorific value of natural gas; Coal-fired power plants: generate electricity by burning coal; Among them, P Coal is the power generation capacity of the coal-fired power plant, η Coal is the coal-fired power plant efficiency, is the coal flow, LHV Coal It is the lower calorific value of coal; Nuclear power: electricity is produced through nuclear reactions; P Nuclear =η Nuclear ·Q Nuclear Among them, P Nuclear is the nuclear power generation power, η Nuclear is the nuclear power plant efficiency, Q Nuclear It is the heat energy produced by nuclear reactions; Combined power and heat (CHP) system: produces electricity and heat at the same time; Among them, η CHP is the combined power-heat system efficiency, P CHP is the power generated by the CHP system, Q CHP It is the heat supply of the combined heat and power generation system. is the fuel flow rate, LHV Fuel is the lower heating value of the fuel; Combined power and cooling (CCHP) system: produces electricity, heat and cooling at the same time; Among them, η CCHP is the efficiency of the combined power-cooling system, P CCHP is the power generation of the combined power-cooling system, Q CCHP is the heat supply of the combined power-cooling system, C CCHP is the cooling capacity of the combined power-cooling system; Energy storage equipment: including heat storage, cold storage and battery storage; E Storage =E In -E Out -Loss Among them, E Storage is the storage energy of the energy storage device, E In is the input energy, E Out is the output energy, and Loss is the energy lost during the energy storage process; Power network: used for the transmission and distribution of electricity; P Load =P Generation -P Loss Among them, P Load is the load demand power, P Generation is the generated power, P Loss is the transmission loss; Thermal network: used for the transmission and distribution of thermal energy; Q Load =Q Generation -Q Loss Among them, Q Load is the heat load demand, Q Geberation is the amount of heat energy generated, Q Loss is the transmission loss; Cold energy network: used for transmission and distribution of cold energy; C Load =C Generation -C Loss Among them, C Load is the cooling load demand, C Generation is the amount of cold energy generated, C Loss is the transmission loss; Natural gas pipeline network: used for the transmission and distribution of natural gas; OF Load =OF Supply -OF Loss Among them, NG Load is the natural gas demand, NG Supply is the natural gas supply, NG Loss is the transmission loss; Energy consumption by residential users: electricity, heating and cooling for households; E Residential =P Electricity +Q Heat +C Cooling Among them, E Residential is the energy demand of residential users, P Electricity is the power demand, Q Heat is the heat demand, C Cooling is the cooling energy demand; Commercial user energy consumption: electricity, heat and cooling energy demand for commercial buildings and office buildings; E Commercial =P Electricity +Q Heat +C Cooling Among them, E Commercial is the energy demand of commercial users, P Electricity is the power demand, Q Heat is the heat demand, C Cooling is the cooling energy demand; Energy consumption by industrial users: various energy needs in the industrial production process; E Industrial =P Electricity +Q Heat +C Cooling +OF Fuel Among them, R Industrial is the energy demand of industrial users, P Electricity is the power demand, Q Heat is the heat demand, C Cooling is the cooling energy demand, NG Fuel It is the demand for natural gas.

4. The method according to claim 3, characterized in that Also includes: Central Energy Management System (EMS): used for global energy scheduling and optimization; C Tptal =∑(C Generation +C Transmission +C Storage +C Consumption ) Among them, C Total is the total system cost, C Generation is the cost of electricity generation, C Transmission is the transmission cost, C Storage is the energy storage cost, C Consumption is the consumption cost; Distributed Energy Management System (DEMS): used for regional or local energy management; C Local =∑(C LocalGeneration +C LocalTransmission +C LococalStorage +C LocalConsumption ) Among them, C Local is the total local system cost, C LocalGeneration is the local generation cost, C LocalTransmission is the local transmission cost, C LocalStorage is the local energy storage cost, C LocalConsumption is the local consumption cost; Intelligent metering and monitoring system: used to monitor the operating status and energy consumption of each energy unit in real time.

5. The method according to claim 1, characterized in that The main problem in step 3 is to minimize the system cost: in, C Leader : The total cost of the system (needs to be minimized), C Generation (t): The cost of electricity generation at time t, C Transmission (t): Electricity at time t Among them, P Generation (t): power generation at time t; The discharge power of the energy storage system at time t; The charging power of the energy storage system at time t; P Load (t): load power demand at time t; Among them, SOC BESS (t): the state of the energy storage system at time t; The minimum permissible state of the energy storage system; The maximum permissible state of the energy storage system; P Loss (t)≤P Generation (t)·η Transmission , Among them, P Loss (t): transmission loss power at time t; η Transmission :Efficiency of power transmission; 6. The method according to claim 1, characterized in that In step 3, the problem is local optimal scheduling: in, The total cost of the ith subsystem; The local generation cost of the ith subsystem at time t; The local consumption cost of the ith subsystem at time t; in, The local power generation of the ith subsystem at time t; The local energy storage discharge power of the i-th subsystem at time t; The local energy storage charging power of the i-th subsystem at time t; At time t, the local load demand power of the i-th subsystem; in, Energy storage state of the ith subsystem at time t; The minimum permissible state of the energy storage system of the ith subsystem; The maximum permissible state of the energy storage system of the ith subsystem; in, At time t, the local load demand of the ith subsystem; f i (·): represents the local load and system power generation P G eneration(t) and energy storage system discharge P B ESS out The functional relationship between (t).

7. The method according to claim 6, characterized in that In step 4, the master-slave game solution process: 1): Initialization, determine the initial state and parameters of the system; initialize the variables of the master problem and the slave problem; 2): Solve the subordinate problem. Given the decision variables of the main problem, solve the subordinate problem. Obtain the optimal solution of the slave problem as the response of the slave problem to the master problem; 3): Update the master problem. Based on the response of the slave problem, update the variables and constraints of the master problem. Solve the main problem and obtain a new optimal solution; 4): Iterate and solve, passing the new optimal solution of the master problem to the slave problem; Repeat steps 2) and 3) until the solution to the master-slave problem converges and reaches game equilibrium.

8. The method according to claim 7, characterized in that The objective function of the main problem is:

9. The method according to claim 8, characterized in that The objective function of the problem is:

10. The method according to claim 9, characterized in that The solution to the master-slave problem satisfies the following equilibrium conditions: in, Represents the partial derivative of the variable, here for P Generation′ and Calculate the gradient of the objective function; P Generation : The decision variable of the power generation in the global system is optimized by the master problem; Decision variables for charging power of energy storage system; The decision variable of the discharge power of the energy storage system; λ is the Lagrange multiplier used to connect the master problem and the slave problem.

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