CN112651105A - Micro-grid capacity configuration optimization method based on game theory - Google Patents

Abstract

The disclosure provides a microgrid capacity configuration optimization method based on game theory, which comprises the following steps: step S110, establishing a structure and an output function of the independent wind/light/storage/diesel generator microgrid, and determining an energy scheduling strategy; step S120, modeling a revenue function of each investment unit in the independent wind/light/storage/diesel generator microgrid; step S130, establishing corresponding non-cooperative game models and wind-light-leading game models for each unit main body according to the actual operation mode of the independent wind/light/storage/diesel generator micro-grid system; and S140, solving the established game model by combining the particle swarm algorithm and the iterative algorithm to obtain an optimization scheme of capacity allocation. The method considers the relation among the unit investment subjects in the system, and considers the mutual influence among the subject behaviors through the idea of the game theory, so that the method is favorable for dealing with the subject diversity of the microgrid system.

Description

Micro-grid capacity configuration optimization method based on game theory

Technical Field

The disclosure belongs to the technical field of microgrid optimization, and particularly relates to a microgrid capacity configuration optimization method based on a game theory.

Background

Energy is a power of social development, and with energy exhaustion caused by wide use of fossil energy and a series of increasingly serious environmental problems, it is a popular research direction to seek renewable energy to replace fossil energy and a distributed energy mode to replace traditional centralized power generation. The independent wind/light/storage/diesel generator micro-grid system combines the complementarity of wind power and photoelectric renewable energy sources and an energy storage technology, and is a feasible development direction for realizing the utilization of the renewable energy sources in remote areas and islands. At present, the problems of high manufacturing cost and operation and maintenance cost of the wind-solar energy storage power generation system, low actual fund return rate, unstable output and the like restrict the development of the project. Therefore, on the premise of pre-configuring the diesel generator, the rated capacities of wind, light and storage in the microgrid are reasonably and effectively configured, the requirement of matching the output of the system with the load can be met, the stability of the power system is ensured, and the actual benefit is improved. On the one hand, the reasonable configuration wind, light capacity ratio can effectively utilize the scene resource, avoid the scene alone to generate electricity and exert oneself unstably and the energy waste that causes reduces the input cost, and on the other hand combines scene capacity to carry out reasonable configuration to energy memory, can level and smooth output power, reduces the load and lacks the electric rate, reduces the energy storage construction cost.

In conclusion, how to realize reasonable capacity planning of wind, light and storage is researched, which is of great significance to the development of wind-light storage power generation systems, and many scholars have researched and made important progress in this respect. Regarding capacity allocation, the existing common multi-objective optimization method aggregates all units in the system into a whole, and establishes an optimization model of the microgrid capacity allocation by using a plurality of objectives of optimal overall economic benefit of the microgrid system, lowest overall operation cost of the system and the like.

However, in consideration of the fact that wind, light and storage equipment may belong to different investors in the actual planning process, the overall optimal idea may be contradictory to the idea that investors pursue respective optimal benefits, and therefore the multi-objective optimization method has certain limitations.

Disclosure of Invention

The present disclosure is directed to solve at least one of the technical problems in the prior art, and provides a microgrid capacity configuration optimization method based on a game theory.

In one aspect of the present disclosure, a microgrid capacity configuration optimization method based on game theory is provided, the method includes:

step S110, establishing a structure and an output function of the independent wind/light/storage/diesel generator microgrid, and determining an energy scheduling strategy;

step S120, modeling a revenue function of each investment unit in the independent wind/light/storage/diesel generator microgrid;

step S130, establishing corresponding non-cooperative game models and wind-light-leading game models for each unit main body according to the actual operation mode of the independent wind/light/storage/diesel generator micro-grid system;

and S140, solving the established game model by combining the particle swarm algorithm and the iterative algorithm to obtain an optimization scheme of capacity allocation.

In some optional embodiments, in step S110, the established structure of the independent wind/light/storage/diesel generator microgrid comprises a wind generating set, a photovoltaic generating set, an energy storage battery set and a diesel generator; wherein,

the wind generating set is connected to a DC bus through a rectifier, and the photovoltaic generating set is connected to the DC bus through a DC/DC converter;

the energy storage battery pack receives instructions of the controller to charge and discharge according to the real-time power generation power and the load, and the diesel generator is connected to the AC bus through the inverter to supply power to the load.

In some optional embodiments, the establishing the structure and the output function of the independent wind/light/storage/diesel generator microgrid comprises:

step S111, establishing a wind turbine generator output model:

in an independent wind/light/storage/diesel generator microgrid system, the output of a wind turbine generator is constrained by the installed scale and the actual situation; when the installed capacity is determined, the maximum value of the wind power output at each moment is determined by actual conditions such as weather, environment and the like, and the fan output and the wind speed satisfy the following nonlinear relation (1):

in the formula ,p_WG(t) wind power generation output at time t, v (t) real-time wind speed at time t, v_iFor wind turbines cut-in wind speed, v_oCut-out wind speed v for wind turbines_rRated wind speed, P, of the wind turbine_WGThe installed capacity value of the wind turbine generator is obtained;

step S112, establishing a photovoltaic output model:

similarly, the photovoltaic output is also constrained by the installed scale and the practical situation; when the installed capacity is determined, the photovoltaic output is related to the illumination intensity and the temperature, and can be represented by the following relation (2):

in the formula ,p_PV(t) is the photovoltaic power generation output at time t, alpha_PVFor a power derating factor, P, of the unit_PVInstalled capacity for photovoltaics, A_tIs the actual irradiance of the photovoltaic generator set at the moment t, A_sIs the irradiance (unit: k) under standard conditionsW/m²)；α_TIs the power temperature coefficient, T_stpIs the temperature under standard conditions; due to alpha_TThe value of (A) is relatively very small, the influence of temperature variation on the output of the photovoltaic is approximately 0, so that the output of the photovoltaic generator set can be approximately proportional to the actual irradiance A_tThe following relation (3):

step S113, establishing an output model of the power storage system:

the SOC of the battery is a ratio of the remaining battery capacity to the full battery capacity, and is represented by the following relation (4):

in the formula ,C_e(t) is the residual capacity of the battery at time t, C_fullIs the battery capacity;

definition of p_e(t) is the charge/discharge power of the battery, when p_eWhen t is less than or equal to 0, it indicates that the accumulator is charging, when p_eWhen (t) > 0, the battery is discharging, and the energy storage state of the battery can be expressed by the following relation (5)

Where α is the self-discharge efficiency of the battery, β_c and β_dThe charge and discharge efficiency of the storage battery is respectively;

step S114, establishing constraint conditions

A supply balance constraint, as in relation (6) below:

p_WG(t)+p_PV(t)+p_de(t)＝p_d(t) (6)

in the formula ,p_de(t) the output of the diesel generator at time t, p_d(t) is the load demand at time t;

the unit output constraint is as follows in relation (7) to (11):

0≤p_WG(t)≤P_WG (7)

0≤p_PV(t)≤P_PV (8)

SOC_min≤SOC≤SOC_max (9)

|p_e(t)|≤p_e,max (10)

0≤p_de(t)≤p_de,max (11)

in the formula ,SOC_min、SOC_maxLower and upper limits of SOC, p_e,maxIs the maximum charge-discharge power, p, of the energy storage battery_de,maxIs the maximum power at which the diesel generator operates.

In some optional embodiments, the determining the energy scheduling policy includes:

step S115, making an independent wind/light/storage/diesel generator microgrid energy scheduling strategy:

the wind generating set and the photovoltaic generating set jointly generate power and output electric energy for supplying a load and an energy storage battery pack; the digestible power of the microgrid at the time t is represented by the following relation (12):

in the formula ,S_ess(t) is the electric energy stored by the energy storage device at the moment t;

a) when the wind-solar power generation output at the t moment of the microgrid is greater than the absorbable power of the microgrid at the t moment, namely p_WG(t)+p_PV(t)＞P_mar(t), wind power and photoelectricity respectively abandon part of electric energy according to the generated energy, namely wind abandon or light abandon phenomenon is generated; the energy that wind and light are respectively accepted by the micro-grid at the moment is as the following relational expressions (13) and (14):

in the formula ,p_WG.S(t)、p_PV.S(t) respectively receiving wind power generation capacity by the microgrid and receiving photovoltaic power generation capacity by the microgrid at the moment t;

b) when p is_d(t)≤p_WG(t)+p_PV(t)≤P_mar(t), the microgrid receives all renewable power generation, and redundant electric energy is used for charging the energy storage battery;

c) when p is_WG(t)+p_PV(t)＜p_dAnd (t) the energy storage battery starts to discharge, and because the renewable energy sources have randomness and volatility, if the renewable energy sources generate power and the energy storage battery still cannot meet the load requirement, the small diesel generator starts to work, the output interval is 0 to rated power, and if the diesel generator still cannot meet the load requirement when reaching the rated power, a part of load needs to be cut off at the moment so as to ensure the normal operation of important loads.

In some optional embodiments, the step S120 specifically includes:

the power generation system is once invested in construction cost in the initial stage, income is continuously acquired in the operation life period, and the annual average economic benefit in the whole life cycle of the wind and light storage equipment is considered to be more practical; solving the game model needs to optimize the annual economic benefit of investors, and meanwhile, the reliability of micro-grid power supply needs to meet the requirement; wind-solar-energy-storage respective annual economic benefit function U_xAs in the following relation (15):

U_x＝I_x-C_x-E_x (15)

in the formula, subscript x is WG, PV and b; i is_x、C_x、E_xRespectively the income, the construction, operation and maintenance cost and the cost required to be paid due to insufficient power supply in the whole life cycle of the equipment;

step S121, annual income function

Step S1211, wind power generation income

The income of the wind generating set is the following relational expression (16):

I_WG＝I_WG.s+I_WG.sub+I_WG.d (16)

in the formula I_WG.s、I_WG.sub、I_WG.dRespectively selling income for electric energy, subsidies for governments and residual value of the equipment reaching the year of operation;

supposing that the government subsidies wind power investors by unit electric energy, the subsidy coefficient can be converted into unit wind power on-line electricity price, and the electric energy selling income containing the government subsidy income is the following relational expression (17):

in the formula ,R_WGT represents the total number of hours of operation in order to take account of the electricity price for power generation and internet surfing subsidized by the government;

the wind driven generator can not work after the service life of the equipment is reached, but has residual value, the fund withdrawal rate needs to be considered when the annual income is calculated, the income needs to be converted into each year, and the residual value of the equipment is represented by the following relation (18):

in the formula ,i_WG.dIs the residual value of the fan per unit capacity, r is the cash rate of capital, L_WGThe operating life of the fan is prolonged;

photovoltaic power generation income calculation is similar to wind power generation;

step S1212, storing energy storage battery:

the energy storage equipment balances the energy supply and demand relation between the system and the load through charge and discharge control, and plays a role in smoothing the output force of the power generation system, and when the energy storage equipment is calculated to receive, the energy storage electricity price income I is calculated_b.sGovernment subsidy I_b.subAlso considering the auxiliary service income I of the energy storage battery_b.eThe revenue function is the following relation (19):

I_b＝I_b.s+I_b.sub+I_b.e (19)

aiming at the randomness and the fluctuation of wind and light power generation output, the energy storage battery can be regarded as the spare capacity of new energy power generation in a power grid, redundant renewable energy power generation is stored when the load of the power grid is low, electric energy output is provided when the output of the renewable energy is insufficient, the load curve of a system can be leveled, and the payment cost of auxiliary service of the energy storage battery is in the following relation (20):

in the formula R_b.eA unit auxiliary service revenue coefficient;

step S122, annual construction and operation cost function

The annual construction and operation costs of the investors include annual construction cost C_x.conAnd annual operating maintenance costs C_x.mSpecifically, the following relational expression (21) is satisfied;

C_x＝C_x.con+C_x.m (21)

the construction cost of the equipment is one-time investment cost, the time value of currency needs to be considered when calculating the annual construction cost, taking a fan as an example, the annual construction cost and the annual operation maintenance cost considering the fund return coefficient are the following relational expressions (22) to (24):

C_WG.con＝c_WG.conP_WGf_WG.cr (22)

C_WG.m＝c_WG.mP_WG (24)

in the formula ,c_WG.conThe construction cost of the unit capacity fan, c_WG.mFor the unit capacity fan operating maintenance cost, f_WG.crReporting the coefficient for the fan capital;

step S123, power supply shortage cost function

When the wind, light and storage three do not satisfy the areaWhen the regional power utilization is required, the diesel generator needs to be started, and for the energy consumption of the diesel generation and the generated environmental pollution, the wind, light and storage three parties need to pay corresponding electricity purchasing cost E to the diesel generator_c(ii) a Related expenses are jointly borne by three parties, a specific distribution method is that the wind-solar-energy storage three parties discuss at first to determine the distribution payment proportion, and the method selects to distribute according to the rated capacity;

taking wind power as an example, the cost required to be paid due to insufficient power supply is the following relational expressions (25) and (26):

in the formula ,R_cThe cost coefficient of purchasing electricity for generating electricity from diesel oil.

In some optional embodiments, the step S130 specifically includes:

each main body of the unit in the independent wind/light/storage/diesel generator microgrid system is regarded as a player, the output of the unit is a game strategy, and the main bodies in an actual operation mode can be cooperative or non-cooperative; in the non-cooperative game, because no protocol with binding force exists among players, the players respectively seek a strategy for maximizing the benefits of the players to execute; in the cooperative game, on the basis of collective rationality, the profits of the alliances are maximized, and then the profits of the players are maximized through reasonable distribution of the profits;

step S131, wind-solar-storage non-cooperative game model

In the wind-solar-energy-storage non-cooperative game, rated installed capacities are selected by the wind-solar-energy-storage three parties respectively, the decision target is that the annual economic benefit of each party is optimal, and the economic benefit of a single party in the micro-grid depends on the rated capacity of the party and is related to the capacities of the other parties; in the game, investors of the wind, light and storage equipment simultaneously select the rated installed capacity (or the rated installed capacity selected by other people is not known before decision making), the investors are rational and know that other investors are rational, and the investors completely know the relevant information such as the income function, the decision making space and the like of other investors; the wind-solar-storage non-cooperative game forms a static complete information game, comprises the factors of participants, decisions, income functions, game solutions and the like of the game, and is described as follows:

a) the participants of the game are investors of wind, light and storage, and are marked as WG, PV and b;

b) the decision of the participants is wind, light and the respective installed capacity P_WG、P_PV、P_b；

c) The game has the income function of wind, light and storage of the annual economic benefits U of each_WG、U_PV、U_b；

d) Nash equilibrium solution with pure strategy

As a solution to the game;

in the game, the strategy selected by each participant must be the optimal reaction aiming at the strategies selected by other participants, namely, the participants voluntarily select a pure strategy Nash equilibrium solution as the own strategy, no participant is willing to deviate from the solution alone and select other strategies, and if a certain participant independently selects other strategies, the income of the participant is necessarily reduced; the pure strategy nash equilibrium is defined as follows:

remember u_iAs a function of the profitability of participant i, s_iPolicy for participant i, S_iFor the decision space of participant i, the game standard expression G ═ S in n players₁，...,S_n；u₁,...u_nIn the theory, the strategic combination of pure strategy Nash equilibrium

In (1)

For S_iAll policies s in_i，

The optimal solution to the following optimization problem is the following relation (27):

pure strategy nash equilibrium S^*Is calculated as follows in relation (28):

step S132, wind-solar cooperation leading master-slave game model

In the independent wind/light/storage/diesel generator microgrid, wind power and photoelectricity are preferentially used because a wind generating set and a photovoltaic generating set have no power generation cost, and an energy storage system provides electric energy output when the wind power and the photovoltaic power supply cannot meet the load; to a certain extent, the installed capacities of the wind generating set and the photovoltaic generating set are configured for the capacity of the energy storage battery system to guide investors of the energy storage battery system to determine the capacity of the energy storage battery after observing that wind power and photoelectric investors select the capacities of the wind generating set and the photovoltaic generating set; based on the method, a master-slave game model with wind-solar cooperation dominance can be established, and in the game, wind power investors and photovoltaic investors select cooperation to seek the maximization of the comprehensive income of the wind power investors and the photovoltaic investors; the main characteristic of the master-slave game is that the leader first selects a proper strategy, and the follower knows the strategy made by the leader before making a decision; the game is described as:

a) the game leader is a wind-solar alliance investor, and the follower is an energy storage battery investor which is marked as WG + PV and b;

b) the decision of the participants is wind-light alliance, and the installed capacity (P) of the energy storage battery_WG、P_PV)、P_b；

c) The game revenue function is the years of wind-light alliance and energy storage batteryEconomic benefit U_WG+PV、U_b；

The wind-solar investor obtains the income according to the contribution in the alliance, namely the total income obtained in the game is distributed by using a Shapley value in a cooperative game theory, and the income U obtained by the individual i participating in the alliance Z_iThe calculation is as follows for relations (29) and (30):

wherein S is all subsets containing the member i in the coalition Z, | Z | and | S | are the numbers of the members in the coalition and the subsets respectively, U (S) is coalition income of the coalition S, and U (S \ i) is coalition income without the member i;

the action sequence in the primary-secondary game is

a) Wind and light alliance determination of installed capacity P_WG、P_PV；

b) The investor of the energy storage battery knows the wind and light installed capacity and determines the capacity U of the energy storage battery_b。

In some optional embodiments, the step S140 specifically includes:

step S141, wind-solar-storage non-cooperative game solving

The iterative algorithm for solving the pure strategy Nash equilibrium solution is as follows:

a) establishing a profit model U of each party participating in the game_WG，U_PV，U_b；

b) Inputting relevant parameters and relevant historical data required by calculation and determining strategy space S_WG、S_PV、S_b；

c) Determining the number of groups and initializing the strategy of the participants (P)_WG0，P_PV0，P_b0) The setting of this initial value can be a reasonable value empirically;

d) the calculation formula of the fitness function is the following relational expressions (31) to (34):

minf＝min(Δ_WG+Δ_PV+Δ_b) (34)

e) updating the population and judging the condition of exiting iteration, wherein the judgment condition is that the set iteration times are reached or f is less than or equal to epsilon, and epsilon is used for expressing the approximation degree of Nash equilibrium solution;

step S142, solving of master-slave game model of wind-solar cooperation leader

The master-slave game process of the wind-solar cooperation leader is as follows:

a) wind and light alliance determination of installed capacity (P)_WG0，P_PV0)；

b) Selecting proper energy storage battery capacity P after the energy storage equipment obtains the wind and light installed capacity information_b1Maximizing self-revenue, as shown in the following relationship (35):

as all parties in the game mutually know respective income functions, the wind-solar alliance can predict the selection P of the investor of the energy storage battery_b0The wind-solar alliance will adjust its decision accordingly, as the following relation (36):

in another aspect of the disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, is adapted to carry out the method according to the above.

According to the microgrid capacity configuration optimization method based on the game theory, all units in the independent wind/light/storage/diesel generator microgrid are not regarded as a whole to be optimized, the relationship among all unit investment subjects in the system is considered, the mutual influence among the behaviors of the subjects is considered by the idea of the game theory, and the method is favorable for dealing with the subject diversity of the microgrid system. The method takes the benefit maximization of each main body in the independent wind/light/storage/diesel generator microgrid as an optimization target, establishes a cooperative game model and a non-cooperative game model of capacity allocation, can realize the optimization of the multi-main-body multi-target problem, and obtains a solution satisfying each main body.

Drawings

Fig. 1 is a flowchart of a microgrid capacity configuration optimization method based on game theory in an embodiment of the present disclosure;

fig. 2 is a schematic structural diagram of an independent wind/light/storage/diesel generator microgrid according to another embodiment of the present disclosure;

FIG. 3 is a diagram of the implementation of two gaming models according to another embodiment of the present disclosure;

FIG. 4 is a schematic diagram of a typical daily curve of a unit power wind power output according to another embodiment of the present disclosure;

FIG. 5 is a schematic diagram of a typical daily curve of a unit power photovoltaic power generation output according to another embodiment of the present disclosure;

FIG. 6 is a schematic view of a typical daily load curve according to another embodiment of the present disclosure.

Detailed Description

For a better understanding of the technical aspects of the present disclosure, reference is made to the following detailed description taken in conjunction with the accompanying drawings.

As shown in fig. 1, a microgrid capacity configuration optimization method based on game theory includes:

step S110, establishing a structure and an output function of the independent wind/light/storage/diesel generator microgrid, and determining an energy scheduling strategy;

step S120, modeling a revenue function of each investment unit in the independent wind/light/storage/diesel generator microgrid;

step S130, establishing corresponding non-cooperative game models and wind-light-leading game models for each unit main body according to the actual operation mode of the independent wind/light/storage/diesel generator micro-grid system;

and S140, solving the established game model by combining the particle swarm algorithm and the iterative algorithm to obtain an optimization scheme of capacity allocation.

According to the microgrid capacity configuration optimization method based on the game theory, all units in the independent wind/light/storage/diesel generator microgrid are not regarded as a whole to be optimized, the relationship among all unit investment subjects in the system is considered, the mutual influence among the behaviors of the subjects is considered by the idea of the game theory, and the method is favorable for dealing with the subject diversity of the microgrid system. The method takes the benefit maximization of each main body in the independent wind/light/storage/diesel generator microgrid as an optimization target, establishes a cooperative game model and a non-cooperative game model of capacity allocation, can realize the optimization of the multi-main-body multi-target problem, and obtains a solution satisfying each main body.

In some optional embodiments, in step S110, in combination with fig. 2, the structure of the independent wind/light/storage/diesel generator microgrid is built up to include a wind generating set 1, a photovoltaic generating set 2, an energy storage battery pack 5 and a diesel generator 8. The wind generating set 1 is connected to a DC bus through a rectifier 3, and the photovoltaic generating set 2 is connected to the DC bus through a DC/DC converter 4. The energy storage battery pack 5 is connected to the DC bus through the controller 6, and is connected to the AC bus through the controller 6 and the inverter 7. The energy storage battery 6 set receives the instructions of the controller to charge and discharge according to the real-time power generation power and the load, and the diesel generator 8 is connected to the AC bus through the inverter 7 to supply power to the load.

In some optional embodiments, the establishing the structure and the output function of the independent wind/light/storage/diesel generator microgrid comprises:

step S111, establishing a wind turbine generator output model:

in an independent wind/light/storage/diesel generator microgrid system, the output of a wind turbine generator is constrained by the installed scale and the actual situation; when the installed capacity is determined, the maximum value of the wind power output at each moment is determined by actual conditions such as weather, environment and the like, and the fan output and the wind speed satisfy the following nonlinear relation (1):

in the formula ,p_WG(t) wind power generation output at time t, v (t) real-time wind speed at time t, v_iFor wind turbines cut-in wind speed, v_oCut-out wind speed v for wind turbines_rRated wind speed, P, of the wind turbine_WGThe installed capacity value of the wind turbine generator is obtained;

step S112, establishing a photovoltaic output model:

similarly, the photovoltaic output is also constrained by the installed scale and the practical situation; when the installed capacity is determined, the photovoltaic output is related to the illumination intensity and the temperature, and can be represented by the following relation (2):

in the formula ,p_PV(t) is the photovoltaic power generation output at time t, alpha_PVFor a power derating factor, P, of the unit_PVInstalled capacity for photovoltaics, A_tIs the actual irradiance of the photovoltaic generator set at the moment t, A_sIs irradiance (unit: kW/m) under standard conditions²)；α_TIs the power temperature coefficient, T_stpIs the temperature under standard conditions; due to alpha_TThe value of (A) is relatively very small, the influence of temperature variation on the output of the photovoltaic is approximately 0, so that the output of the photovoltaic generator set can be approximately proportional to the actual irradiance A_tThe following relation (3):

step S113, establishing an output model of the power storage system:

the SOC of the battery is a ratio of the remaining battery capacity to the full battery capacity, and is represented by the following relation (4):

in the formula ,C_e(t) is the residual capacity of the battery at time t, C_fullIs the battery capacity;

definition of p_e(t) is the charge/discharge power of the battery, when p_eWhen t is less than or equal to 0, it indicates that the accumulator is charging, when p_eWhen (t) > 0, the battery is discharging, and the energy storage state of the battery can be expressed by the following relation (5)

Where α is the self-discharge efficiency of the battery, β_c and β_dThe charge and discharge efficiency of the storage battery is respectively;

step S114, establishing constraint conditions

A supply balance constraint, as in relation (6) below:

p_WG(t)+p_PV(t)+p_de(t)＝p_d(t) (6)

in the formula ,p_de(t) the output of the diesel generator at time t, p_d(t) is the load demand at time t;

the unit output constraint is as follows in relation (7) to (11):

0≤p_WG(t)≤P_WG (7)

0≤p_PV(t)≤P_PV (8)

SOC_min≤SOC≤SOC_max (9)

|p_e(t)|≤p_e,max (10)

0≤p_de(t)≤p_de,max (11)

in the formula ,SOC_min、SOC_maxLower and upper limits of SOC, p_e,maxIs the maximum charge-discharge power, p, of the energy storage battery_de,maxIs the maximum power at which the diesel generator operates.

In some optional embodiments, the determining the energy scheduling policy includes:

step S115, making an independent wind/light/storage/diesel generator microgrid energy scheduling strategy:

the wind generating set and the photovoltaic generating set jointly generate power and output electric energy for supplying a load and an energy storage battery pack; the digestible power of the microgrid at the time t is represented by the following relation (12):

in the formula ,S_ess(t) is the electric energy stored by the energy storage device at the moment t;

a) when the wind-solar power generation output at the t moment of the microgrid is greater than the absorbable power of the microgrid at the t moment, namely p_WG(t)+p_PV(t)＞P_mar(t), wind power and photoelectricity respectively abandon part of electric energy according to the generated energy, namely wind abandon or light abandon phenomenon is generated; the energy that wind and light are respectively accepted by the micro-grid at the moment is as the following relational expressions (13) and (14):

in the formula ,p_WG.S(t)、p_PV.S(t) respectively adopting the microgrid to receive wind power generation capacity and the microgrid to receive photovoltaic power generation capacity at the moment tGenerating capacity;

b) when p is_d(t)≤p_WG(t)+p_PV(t)≤P_mar(t), the microgrid receives all renewable power generation, and redundant electric energy is used for charging the energy storage battery;

c) when p is_WG(t)+p_PV(t)＜p_dAnd (t) the energy storage battery starts to discharge, and because the renewable energy sources have randomness and volatility, if the renewable energy sources generate power and the energy storage battery still cannot meet the load requirement, the small diesel generator starts to work, the output interval is 0 to rated power, and if the diesel generator still cannot meet the load requirement when reaching the rated power, a part of load needs to be cut off at the moment so as to ensure the normal operation of important loads.

In some optional embodiments, the step S120 specifically includes:

the power generation system is once invested in construction cost in the initial stage, income is continuously acquired in the operation life period, and the annual average economic benefit in the whole life cycle of the wind and light storage equipment is considered to be more practical; solving the game model needs to optimize the annual economic benefit of investors, and meanwhile, the reliability of micro-grid power supply needs to meet the requirement; wind-solar-energy-storage respective annual economic benefit function U_xAs in the following relation (15):

U_x＝I_x-C_x-E_x (15)

in the formula, subscript x is WG, PV and b; i is_x、C_x、E_xRespectively the income, the construction, operation and maintenance cost and the cost required to be paid due to insufficient power supply in the whole life cycle of the equipment;

step S121, annual income function

Step S1211, wind power generation income

The income of the wind generating set is the following relational expression (16):

I_WG＝I_WG.s+I_WG.sub+I_WG.d (16)

in the formula I_WG.s、I_WG.sub、I_WG.dRespectively selling income for electric energy, subsidies for governments and residual value of the equipment reaching the year of operation;

supposing that the government subsidies wind power investors by unit electric energy, the subsidy coefficient can be converted into unit wind power on-line electricity price, and the electric energy selling income containing the government subsidy income is the following relational expression (17):

in the formula ,R_WGT represents the total number of hours of operation in order to take account of the electricity price for power generation and internet surfing subsidized by the government;

the wind driven generator can not work after the service life of the equipment is reached, but has residual value, the fund withdrawal rate needs to be considered when the annual income is calculated, the income needs to be converted into each year, and the residual value of the equipment is represented by the following relation (18):

in the formula ,i_WG.dIs the residual value of the fan per unit capacity, r is the cash rate of capital, L_WGThe operating life of the fan is prolonged;

photovoltaic power generation income calculation is similar to wind power generation;

step S1212, storing energy storage battery:

the energy storage equipment balances the energy supply and demand relation between the system and the load through charge and discharge control, and plays a role in smoothing the output force of the power generation system, and when the energy storage equipment is calculated to receive, the energy storage electricity price income I is calculated_b.sGovernment subsidy I_b.subAlso considering the auxiliary service income I of the energy storage battery_b.eThe revenue function is the following relation (19):

I_b＝I_b.s+I_b.sub+I_b.e (19)

aiming at the randomness and the fluctuation of wind and light power generation output, the energy storage battery can be regarded as the spare capacity of new energy power generation in a power grid, redundant renewable energy power generation is stored when the load of the power grid is low, electric energy output is provided when the output of the renewable energy is insufficient, the load curve of a system can be leveled, and the payment cost of auxiliary service of the energy storage battery is in the following relation (20):

in the formula R_b.eA unit auxiliary service revenue coefficient;

step S122, annual construction and operation cost function

The annual construction and operation costs of the investors include annual construction cost C_x.conAnd annual operating maintenance costs C_x.mSpecifically, the following relational expression (21) is satisfied;

C_x＝C_x.con+C_x.m (21)

the construction cost of the equipment is one-time investment cost, the time value of currency needs to be considered when calculating the annual construction cost, taking a fan as an example, the annual construction cost and the annual operation maintenance cost considering the fund return coefficient are the following relational expressions (22) to (24):

C_WG.con＝c_WG.conP_WGf_WG.cr (22)

C_WG.m＝c_WG.mP_WG (24)

in the formula ,c_WG.conThe construction cost of the unit capacity fan, c_WG.mFor the unit capacity fan operating maintenance cost, f_WG.crReporting the coefficient for the fan capital;

step S123, power supply shortage cost function

When the output of the wind-solar-energy storage three parties does not meet the regional power demand, the diesel generator needs to be started, and the wind-solar-energy storage three parties need to pay corresponding electricity purchasing cost E to the diesel generator for the energy consumption of diesel generation and the generated environmental pollution_c(ii) a The related cost is shared by three parties, and the specific distribution method is started by the wind, light and storage partiesThe payment proportion is determined by initial discussion, and the method selects to distribute according to rated capacity;

taking wind power as an example, the cost required to be paid due to insufficient power supply is the following relational expressions (25) and (26):

in the formula ,R_cThe cost coefficient of purchasing electricity for generating electricity from diesel oil.

In some optional embodiments, the step S130 specifically includes:

each main body of the unit in the independent wind/light/storage/diesel generator microgrid system is regarded as a player, the output of the unit is a game strategy, and the main bodies in an actual operation mode can be cooperative or non-cooperative; in the non-cooperative game, because no protocol with binding force exists among players, the players respectively seek a strategy for maximizing the benefits of the players to execute; in the cooperative game, on the basis of collective rationality, the profits of the alliances are maximized, and then the profits of the players are maximized through reasonable distribution of the profits;

step S131, wind-solar-storage non-cooperative game model

In the wind-solar-energy-storage non-cooperative game, rated installed capacities are selected by the wind-solar-energy-storage three parties respectively, the decision target is that the annual economic benefit of each party is optimal, and the economic benefit of a single party in the micro-grid depends on the rated capacity of the party and is related to the capacities of the other parties; in the game, investors of the wind, light and storage equipment simultaneously select the rated installed capacity (or the rated installed capacity selected by other people is not known before decision making), the investors are rational and know that other investors are rational, and the investors completely know the relevant information such as the income function, the decision making space and the like of other investors; the wind-solar-storage non-cooperative game forms a static complete information game, comprises the factors of participants, decisions, income functions, game solutions and the like of the game, and is described as follows:

a) the participants of the game are investors of wind, light and storage, and are marked as WG, PV and b;

b) the decision of the participants is wind, light and the respective installed capacity P_WG、P_PV、P_b；

c) The game has the income function of wind, light and storage of the annual economic benefits U of each_WG、U_PV、U_b；

d) Nash equilibrium solution with pure strategy

As a solution to the game;

in the game, the strategy selected by each participant must be the optimal reaction aiming at the strategies selected by other participants, namely, the participants voluntarily select a pure strategy Nash equilibrium solution as the own strategy, no participant is willing to deviate from the solution alone and select other strategies, and if a certain participant independently selects other strategies, the income of the participant is necessarily reduced; the pure strategy nash equilibrium is defined as follows:

remember u_iAs a function of the profitability of participant i, s_iPolicy for participant i, S_iFor the decision space of participant i, the game standard expression G ═ S in n players₁，...,S_n；u₁,...u_nIn the theory, the strategic combination of pure strategy Nash equilibrium

In (1)

For S_iAll policies s in_i，

The optimal solution to the following optimization problem is the following relation (27):

pure strategy nash equilibrium S^*Is calculated as follows in relation (28):

step S132, wind-solar cooperation leading master-slave game model

In the independent wind/light/storage/diesel generator microgrid, wind power and photoelectricity are preferentially used because a wind generating set and a photovoltaic generating set have no power generation cost, and an energy storage system provides electric energy output when the wind power and the photovoltaic power supply cannot meet the load; to a certain extent, the installed capacities of the wind generating set and the photovoltaic generating set are configured for the capacity of the energy storage battery system to guide investors of the energy storage battery system to determine the capacity of the energy storage battery after observing that wind power and photoelectric investors select the capacities of the wind generating set and the photovoltaic generating set; based on the method, a master-slave game model with wind-solar cooperation dominance can be established, and in the game, wind power investors and photovoltaic investors select cooperation to seek the comprehensive income maximization of the wind power investors and the photovoltaic investors. The main characteristic of the master-slave game is that the leader first selects a proper strategy, and the follower knows the strategy made by the leader before making a decision; the game is described as:

a) the game leader is a wind-solar alliance investor, and the follower is an energy storage battery investor which is marked as WG + PV and b;

b) the decision of the participants is wind-light alliance, and the installed capacity (P) of the energy storage battery_WG、P_PV)、P_b；

c) The game income function is the annual economic benefit U of the wind-solar alliance and the energy storage battery_WG+PV、U_b；

The wind-solar investor obtains the income according to the contribution in the alliance, namely the total income obtained in the game is distributed by using a Shapley value in a cooperative game theory, and the income U obtained by the individual i participating in the alliance Z_iThe calculation is as follows for relations (29) and (30):

wherein S is all subsets containing the member i in the coalition Z, | Z | and | S | are the numbers of the members in the coalition and the subsets respectively, U (S) is coalition income of the coalition S, and U (S \ i) is coalition income without the member i;

the action sequence in the primary-secondary game is

a) Wind and light alliance determination of installed capacity P_WG、P_PV；

b) The investor of the energy storage battery knows the wind and light installed capacity and determines the capacity U of the energy storage battery_b。

In some optional embodiments, the step S140 specifically includes:

step S141, wind-solar-storage non-cooperative game solving

The iterative algorithm for solving the pure strategy Nash equilibrium solution is as follows:

a) establishing a profit model U of each party participating in the game_WG，U_PV，U_b；

b) Inputting relevant parameters and relevant historical data required by calculation and determining strategy space S_WG、S_PV、S_b；

c) Determining the number of groups and initializing the strategy of the participants (P)_WG0，P_PV0，P_b0) The setting of this initial value can be a reasonable value empirically;

d) the calculation formula of the fitness function is the following relational expressions (31) to (34):

minf＝min(Δ_WG+Δ_PV+Δ_b) (34)

e) updating the population and judging the condition of exiting iteration, wherein the judgment condition is that the set iteration times are reached or f is less than or equal to epsilon, and epsilon is used for expressing the approximation degree of Nash equilibrium solution;

step S142, solving of master-slave game model of wind-solar cooperation leader

The master-slave game process of the wind-solar cooperation leader is as follows:

a) wind and light alliance determination of installed capacity (P)_WG0，P_PV0)；

b) Selecting proper energy storage battery capacity P after the energy storage equipment obtains the wind and light installed capacity information_b1Maximizing self-revenue, as shown in the following relationship (35):

as all parties in the game mutually know respective income functions, the wind-solar alliance can predict the selection P of the investor of the energy storage battery_b0The wind-solar alliance will adjust its decision accordingly, as the following relation (36):

the implementation process of the above two game models is shown in fig. 3.

The following describes a process of the microgrid capacity configuration optimization method based on the game theory according to the present disclosure by using a specific example:

considering that the output and load data volume of one year is large, and the conditions of adjacent days in the same season have similarity, wind power, photovoltaic and load data of a typical day are selected for analysis to represent the average condition of one year in order to simplify calculation. Typical daily wind speed, light intensity, load, etc. data selected from a certain region are shown in fig. 4 to 6. A wind-light micro-grid is established to supply power to the region, wind, light and gas equipment belongs to different investors, and wind, light and gas non-cooperative game model calculation is established for the system as an example, namely, each investor plays a game by taking the maximum income of the investor as a target. Data relating to the respective working devices and electricity prices are shown in the following tables 1 and 2:

TABLE 1 wind-solar energy storage of the relevant parameters of each power supply

TABLE 2 operating parameters of each unit

The pre-configured rated power of the diesel generator is 60kW, and the initial residual capacity is the lower limit value of the SOC. In the calculation process, relevant information of each structure of the microgrid is given in table 1, the energy storage cost coefficient is measured and calculated reasonably, and other relevant parameters are as follows: r_b.e0.04 yuan/(kW h), R_c0.43 yuan/(kW. h), R_out1.5 yuan/(kW h).

The optimized results (device capacity and corresponding revenues) for the two gaming models are shown in table 3:

table 3 wind/light/storage/diesel generator micro-grid capacity optimization results in different game modes

No matter which kind of investment pattern, the installed capacity and the income of fan all are higher than photovoltaic and energy storage battery, indicate that wind-powered electricity generation is the main contributor of microgrid power output. In the example, the local wind resources are rich, the wind power construction cost is relatively low, which is a direct reason for large wind power scale, and the wind power and photoelectric prices only play a secondary role in the game model, and the change of the prices can affect the wind and solar power scale to a certain extent, but the result that the wind power is dominant cannot be changed. .

In addition, due to uncertainty of wind and light, the sum of the capacities of the fan and the photovoltaic exceeds the maximum value in a typical daily load curve in order to obtain larger benefits.

According to the income change, wind and light investors are more inclined to a game mode dominated by wind and light, and energy storage investors are inclined to a wind, light and storage non-cooperative game mode. It should be noted that the game mode among the wind, light and storage parties is determined by the market environment, in the principal and subordinate game theory, the leader needs to make a decision first and cannot withdraw the decision, if the leader has the advantage of being undisputable in the industry, the initiative is possible, and the principal and subordinate game among the wind, light and storage parties is possible.

In another aspect of the disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which, when being executed by a processor, is adapted to carry out the method according to the above.

The computer readable medium may be included in the apparatus, device, system, or may exist separately.

The computer readable storage medium may be any tangible medium that can contain or store a program, and may be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, more specific examples of which include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, an optical fiber, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

The computer readable storage medium may also include a propagated data signal with computer readable program code embodied therein, for example, in a non-transitory form, such as in a carrier wave or in a carrier wave, wherein the carrier wave is any suitable carrier wave or carrier wave for carrying the program code.

It is to be understood that the above embodiments are merely exemplary embodiments that are employed to illustrate the principles of the present disclosure, and that the present disclosure is not limited thereto. It will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the disclosure, and these are to be considered as the scope of the disclosure.

Claims (8)

1. A microgrid capacity configuration optimization method based on game theory is characterized by comprising the following steps:

step S110, establishing a structure and an output function of the independent wind/light/storage/diesel generator microgrid, and determining an energy scheduling strategy;

step S120, modeling a revenue function of each investment unit in the independent wind/light/storage/diesel generator microgrid;

step S130, establishing corresponding non-cooperative game models and wind-light-leading game models for each unit main body according to the actual operation mode of the independent wind/light/storage/diesel generator micro-grid system;

and S140, solving the established game model by combining the particle swarm algorithm and the iterative algorithm to obtain an optimization scheme of capacity allocation.

2. The method of claim 1, wherein in step S110, the established structure of the independent wind/light/storage/diesel generator microgrid comprises a wind generating set, a photovoltaic generating set, an energy storage battery set and a diesel generator; wherein,

the wind generating set is connected to a DC bus through a rectifier, and the photovoltaic generating set is connected to the DC bus through a DC/DC converter;

the energy storage battery pack receives instructions of the controller to charge and discharge according to the real-time power generation power and the load, and the diesel generator is connected to the AC bus through the inverter to supply power to the load.

3. The method of claim 1, wherein establishing the structure and the output function of the independent wind/light/storage/diesel generator microgrid comprises:

step S111, establishing a wind turbine generator output model:

in an independent wind/light/storage/diesel generator microgrid system, the output of a wind turbine generator is constrained by the installed scale and the actual situation; when the installed capacity is determined, the maximum value of the wind power output at each moment is determined by actual conditions such as weather, environment and the like, and the fan output and the wind speed satisfy the following nonlinear relation (1):

in the formula ,p_WG(t) wind power generation output at time t, v (t) real-time wind speed at time t, v_iFor wind turbines cut-in wind speed, v_oCut-out wind speed v for wind turbines_rRated wind speed, P, of the wind turbine_WGThe installed capacity value of the wind turbine generator is obtained;

step S112, establishing a photovoltaic output model:

similarly, the photovoltaic output is also constrained by the installed scale and the practical situation; when the installed capacity is determined, the photovoltaic output is related to the illumination intensity and the temperature, and can be represented by the following relation (2):

in the formula ,p_PV(t) is the photovoltaic power generation output at time t, alpha_PVFor a power derating factor, P, of the unit_PVInstalled capacity for photovoltaics, A_tIs the actual irradiance of the photovoltaic generator set at the moment t, A_sIs irradiance under standard conditions (single)Bit: kW/m²)；α_TIs the power temperature coefficient, T_stpIs the temperature under standard conditions; due to alpha_TThe value of (A) is relatively very small, the influence of temperature variation on the output of the photovoltaic is approximately 0, so that the output of the photovoltaic generator set can be approximately proportional to the actual irradiance A_tThe following relation (3):

step S113, establishing an output model of the power storage system:

the SOC of the battery is a ratio of the remaining battery capacity to the full battery capacity, and is represented by the following relation (4):

in the formula ,C_e(t) is the residual capacity of the battery at time t, C_fullIs the battery capacity;

definition of p_e(t) is the charge/discharge power of the battery, when p_eWhen t is less than or equal to 0, it indicates that the accumulator is charging, when p_eWhen (t) > 0, the battery is discharging, and the energy storage state of the battery can be expressed by the following relation (5)

Where α is the self-discharge efficiency of the battery, β_c and β_dThe charge and discharge efficiency of the storage battery is respectively;

step S114, establishing constraint conditions

A supply balance constraint, as in relation (6) below:

p_WG(t)+p_PV(t)+p_de(t)＝p_d(t) (6)

in the formula ,p_de(t) the output of the diesel generator at time t, p_d(t) isLoad demand at time t;

the unit output constraint is as follows in relation (7) to (11):

0≤p_WG(t)≤P_WG (7)

0≤p_PV(t)≤P_PV (8)

SOC_min≤SOC≤SOC_max (9)

|p_e(t)|≤p_e,max (10)

0≤p_de(t)≤p_de,max (11)

in the formula ,SOC_min、SOC_maxLower and upper limits of SOC, p_e,maxIs the maximum charge-discharge power, p, of the energy storage battery_de,maxIs the maximum power at which the diesel generator operates.

4. The method of claim 3, wherein the determining the energy scheduling policy comprises:

step S115, making an independent wind/light/storage/diesel generator microgrid energy scheduling strategy:

the wind generating set and the photovoltaic generating set jointly generate power and output electric energy for supplying a load and an energy storage battery pack; the digestible power of the microgrid at the time t is represented by the following relation (12):

in the formula ,S_ess(t) is the electric energy stored by the energy storage device at the moment t;

a) when the wind-solar power generation output at the t moment of the microgrid is greater than the absorbable power of the microgrid at the t moment, namely p_WG(t)+p_PV(t)＞P_mar(t), wind power and photoelectricity respectively abandon part of electric energy according to the generated energy, namely wind abandon or light abandon phenomenon is generated; the energy that wind and light are respectively accepted by the micro-grid at the moment is as the following relational expressions (13) and (14):

in the formula ,p_WG.S(t)、p_PV.S(t) respectively receiving wind power generation capacity by the microgrid and receiving photovoltaic power generation capacity by the microgrid at the moment t;

b) when p is_d(t)≤p_WG(t)+p_PV(t)≤P_mar(t), the microgrid receives all renewable power generation, and redundant electric energy is used for charging the energy storage battery;

c) when p is_WG(t)+p_PV(t)＜p_dAnd (t) the energy storage battery starts to discharge, and because the renewable energy sources have randomness and volatility, if the renewable energy sources generate power and the energy storage battery still cannot meet the load requirement, the small diesel generator starts to work, the output interval is 0 to rated power, and if the diesel generator still cannot meet the load requirement when reaching the rated power, a part of load needs to be cut off at the moment so as to ensure the normal operation of important loads.

5. The method according to claim 4, wherein the step S120 specifically comprises:

the power generation system is once invested in construction cost in the initial stage, income is continuously acquired in the operation life period, and the annual average economic benefit in the whole life cycle of the wind and light storage equipment is considered to be more practical; solving the game model needs to optimize the annual economic benefit of investors, and meanwhile, the reliability of micro-grid power supply needs to meet the requirement; wind-solar-energy-storage respective annual economic benefit function U_xAs in the following relation (15):

U_x＝I_x-C_x-E_x (15)

in the formula, subscript x is WG, PV and b; i is_x、C_x、E_xRespectively the income, the construction, operation and maintenance cost and the cost required to be paid due to insufficient power supply in the whole life cycle of the equipment;

step S121, annual income function

Step S1211, wind power generation income

The income of the wind generating set is the following relational expression (16):

I_WG＝I_WG.s+I_WG.sub+I_WG.d (16)

in the formula I_WG.s、I_WG.sub、I_WG.dRespectively selling income for electric energy, subsidies for governments and residual value of the equipment reaching the year of operation;

supposing that the government subsidies wind power investors by unit electric energy, the subsidy coefficient can be converted into unit wind power on-line electricity price, and the electric energy selling income containing the government subsidy income is the following relational expression (17):

in the formula ,R_WGT represents the total number of hours of operation in order to take account of the electricity price for power generation and internet surfing subsidized by the government;

the wind driven generator can not work after the service life of the equipment is reached, but has residual value, the fund withdrawal rate needs to be considered when the annual income is calculated, the income needs to be converted into each year, and the residual value of the equipment is represented by the following relation (18):

in the formula ,i_WG.dIs the residual value of the fan per unit capacity, r is the cash rate of capital, L_WGThe operating life of the fan is prolonged;

photovoltaic power generation income calculation is similar to wind power generation;

step S1212, storing energy storage battery:

the energy storage equipment balances the energy supply and demand relation between the system and the load through charge and discharge control, and plays a role in smoothing the output force of the power generation system, and when the energy storage equipment is calculated to receive, the energy storage electricity price income I is calculated_b.sGovernment subsidy I_b.subAlso considering the auxiliary service income I of the energy storage battery_b.eThe revenue function is the following relation (19):

I_b＝I_b.s+I_b.sub+I_b.e (19)

aiming at the randomness and the fluctuation of wind and light power generation output, the energy storage battery can be regarded as the spare capacity of new energy power generation in a power grid, redundant renewable energy power generation is stored when the load of the power grid is low, electric energy output is provided when the output of the renewable energy is insufficient, the load curve of a system can be leveled, and the payment cost of auxiliary service of the energy storage battery is in the following relation (20):

in the formula R_b.eA unit auxiliary service revenue coefficient;

step S122, annual construction and operation cost function

The annual construction and operation costs of the investors include annual construction cost C_x.conAnd annual operating maintenance costs C_x.mSpecifically, the following relational expression (21) is satisfied;

C_x＝C_x.con+C_x.m (21)

the construction cost of the equipment is one-time investment cost, the time value of currency needs to be considered when calculating the annual construction cost, taking a fan as an example, the annual construction cost and the annual operation maintenance cost considering the fund return coefficient are the following relational expressions (22) to (24):

C_WG.con＝c_WG.conP_WGf_WG.cr (22)

C_WG.m＝c_WG.mP_WG (24)

in the formula ,c_WG.conThe construction cost of the unit capacity fan, c_WG.mIs a unit volumeMeasurement of the running and maintenance cost of the blower, f_WG.crReporting the coefficient for the fan capital;

step S123, power supply shortage cost function

When the output of the wind-solar-energy storage three parties does not meet the regional power demand, the diesel generator needs to be started, and the wind-solar-energy storage three parties need to pay corresponding electricity purchasing cost E to the diesel generator for the energy consumption of diesel generation and the generated environmental pollution_c(ii) a Related expenses are jointly borne by three parties, a specific distribution method is that the wind-solar-energy storage three parties discuss at first to determine the distribution payment proportion, and the method selects to distribute according to the rated capacity;

taking wind power as an example, the cost required to be paid due to insufficient power supply is the following relational expressions (25) and (26):

in the formula ,R_cThe cost coefficient of purchasing electricity for generating electricity from diesel oil.

6. The method according to claim 5, wherein the step S130 specifically comprises:

each main body of the unit in the independent wind/light/storage/diesel generator microgrid system is regarded as a player, the output of the unit is a game strategy, and the main bodies in an actual operation mode can be cooperative or non-cooperative; in the non-cooperative game, because no protocol with binding force exists among players, the players respectively seek a strategy for maximizing the benefits of the players to execute; in the cooperative game, on the basis of collective rationality, the profits of the alliances are maximized, and then the profits of the players are maximized through reasonable distribution of the profits;

step S131, wind-solar-storage non-cooperative game model

In the wind-solar-energy-storage non-cooperative game, rated installed capacities are selected by the wind-solar-energy-storage three parties respectively, the decision target is that the annual economic benefit of each party is optimal, and the economic benefit of a single party in the micro-grid depends on the rated capacity of the party and is related to the capacities of the other parties; in the game, investors of the wind, light and storage equipment simultaneously select the rated installed capacity (or the rated installed capacity selected by other people is not known before decision making), the investors are rational and know that other investors are rational, and the investors completely know the relevant information such as the income function, the decision making space and the like of other investors; the wind-solar-storage non-cooperative game forms a static complete information game, comprises the factors of participants, decisions, income functions, game solutions and the like of the game, and is described as follows:

a) the participants of the game are investors of wind, light and storage, and are marked as WG, PV and b;

b) the decision of the participants is wind, light and the respective installed capacity P_WG、P_PV、P_b；

c) The game has the income function of wind, light and storage of the annual economic benefits U of each_WG、U_PV、U_b；

d) Nash equilibrium solution with pure strategy

As a solution to the game;

in the game, the strategy selected by each participant must be the optimal reaction aiming at the strategies selected by other participants, namely, the participants voluntarily select a pure strategy Nash equilibrium solution as the own strategy, no participant is willing to deviate from the solution alone and select other strategies, and if a certain participant independently selects other strategies, the income of the participant is necessarily reduced; the pure strategy nash equilibrium is defined as follows:

remember u_iAs a function of the profitability of participant i, s_iPolicy for participant i, S_iFor the decision space of participant i, the game standard expression G ═ S in n players₁，...,S_n；u₁,...u_nIn the theory, the strategic combination of pure strategy Nash equilibrium

In (1)

For S_iAll policies s in_i，

The optimal solution to the following optimization problem is the following relation (27):

pure strategy nash equilibrium S^*Is calculated as follows in relation (28):

step S132, wind-solar cooperation leading master-slave game model

In the independent wind/light/storage/diesel generator microgrid, wind power and photoelectricity are preferentially used because a wind generating set and a photovoltaic generating set have no power generation cost, and an energy storage system provides electric energy output when the wind power and the photovoltaic power supply cannot meet the load; to a certain extent, the installed capacities of the wind generating set and the photovoltaic generating set are configured for the capacity of the energy storage battery system to guide investors of the energy storage battery system to determine the capacity of the energy storage battery after observing that wind power and photoelectric investors select the capacities of the wind generating set and the photovoltaic generating set; based on the method, a master-slave game model with wind-solar cooperation dominance can be established, and in the game, wind power investors and photovoltaic investors select cooperation to seek the maximization of the comprehensive income of the wind power investors and the photovoltaic investors; the main characteristic of the master-slave game is that the leader first selects a proper strategy, and the follower knows the strategy made by the leader before making a decision; the game is described as:

a) the game leader is a wind-solar alliance investor, and the follower is an energy storage battery investor which is marked as WG + PV and b;

b) the decision of the participants is wind-light alliance, and the installed capacity (P) of the energy storage battery_WG、P_PV)、P_b；

c) The game income function is the annual economic benefit U of the wind-solar alliance and the energy storage battery_WG+PV、U_b；

The wind-solar investor obtains the income according to the contribution in the alliance, namely the total income obtained in the game is distributed by using a Shapley value in a cooperative game theory, and the income U obtained by the individual i participating in the alliance Z_iThe calculation is as follows for relations (29) and (30):

wherein S is all subsets containing the member i in the coalition Z, | Z | and | S | are the numbers of the members in the coalition and the subsets respectively, U (S) is coalition income of the coalition S, and U (S \ i) is coalition income without the member i;

the action sequence in the primary-secondary game is

a) Wind and light alliance determination of installed capacity P_WG、P_PV；

b) The investor of the energy storage battery knows the wind and light installed capacity and determines the capacity U of the energy storage battery_b。

7. The method according to claim 6, wherein the step S140 specifically includes:

step S141, wind-solar-storage non-cooperative game solving

The iterative algorithm for solving the pure strategy Nash equilibrium solution is as follows:

a) establishing the benefits of parties participating in a gameModel U_WG，U_PV，U_b；

b) Inputting relevant parameters and relevant historical data required by calculation and determining strategy space S_WG、S_PV、S_b；

c) Determining the number of groups and initializing the strategy of the participants (P)_WG0，P_PV0，P_b0) The setting of this initial value can be a reasonable value empirically;

d) the calculation formula of the fitness function is the following relational expressions (31) to (34):

minf＝min(Δ_WG+Δ_PV+Δ_b) (34)

e) updating the population and judging the condition of exiting iteration, wherein the judgment condition is that the set iteration times are reached or f is less than or equal to epsilon, and epsilon is used for expressing the approximation degree of Nash equilibrium solution;

step S142, solving of master-slave game model of wind-solar cooperation leader

The master-slave game process of the wind-solar cooperation leader is as follows:

a) wind and light alliance determination of installed capacity (P)_WG0，P_PV0)；

b) Selecting proper energy storage battery capacity P after the energy storage equipment obtains the wind and light installed capacity information_b1Maximizing self-revenue, as shown in the following relationship (35):

as all parties in the game mutually know respective income functions, the wind-solar alliance can predict the selection P of the investor of the energy storage battery_b0The wind-solar alliance will adjust its decision accordingly, as the following relation (36):

8. a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, is able to carry out a method according to any one of claims 1 to 7.

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