CN116706960A - Virtual power plant multi-main-body game control strategy integrating wind-solar storage - Google Patents
Virtual power plant multi-main-body game control strategy integrating wind-solar storage Download PDFInfo
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Abstract
The application belongs to the technical field of new energy optimization operation, and particularly relates to a virtual power plant multi-main-body game control strategy integrating wind and solar energy storage. Comprising the following steps: establishing a virtual power plant based on a wind-solar-storage comprehensive energy system, uniformly participating in electric power market transaction by an aggregation distributed power supply, and analyzing the cost of cold flexible load; through multi-objective optimization, an internal optimization model of a single virtual power plant is built by utilizing loads; establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the virtual power plant optimization model; constructing a cooperative game model of a multi-virtual power plant game, and forming a low-carbon control strategy for actively absorbing renewable energy sources by a power grid on the premise of safe and economic operation; and distributing the electric energy of each device according to the benefit distribution model, and considering a low-carbon operation control strategy into the virtual power plant to participate in the interactive market transaction of the power grid. The application effectively improves the benefits in the area, realizes the maximization of economic benefits, and reduces the carbon emission of renewable energy power generation.
Description
Technical Field
The application belongs to the technical field of new energy optimization operation, and particularly relates to a virtual power plant multi-main-body game control strategy integrating wind and solar energy storage.
Background
In recent years, the power energy strategy reform gradually becomes the core of the power market reform in China, and clean renewable energy mainly comprising wind energy and solar energy has randomness, intermittence and volatility, so that the renewable energy is combined into a power distribution network in a large scale and high proportion to have a great influence on a power grid. The virtual power plant (Virtual Power Plant, VPP) applies advanced communication technology to cooperatively control a plurality of distributed new energy sources with different regions and different types, integrates distributed wind power, roof photovoltaic, energy storage and flexible load, and flexibly schedules a controllable power supply to stabilize randomness and volatility of uncontrollable new energy sources such as wind power, photovoltaic and the like through reasonable construction, coordination and optimization, so that the whole controllability of external output is realized, and the system can participate in electric market transaction and system scheduling like a conventional power plant.
In the field of new energy optimizing operation, game theory is widely applied to different types of power optimizing markets, and shows excellent performance, and the game theory is used as a core of modern micro economics and also applied to various fields such as power system planning, operation control and the like, and can be a benefit body of power market power generation enterprises, power transmission manufacturers, parks, users and the like. Then, in the setting up of virtual power plants and the background of carbon neutralization, the integrated energy system formed by multiple main bodies needs to consider more indexes such as carbon dioxide emission, system running cost and the like. Aiming at large-range areas such as enterprises, parks and the like, all the main bodies in the system form a comprehensive energy system together to realize the optimization of energy, economic maximum and carbon emission together.
The application discloses an operation optimization method of a comprehensive energy system based on multi-main game, which comprises the steps of establishing an environment constraint and benefit constraint establishment model to construct an objective function; and secondly, benefit distribution is carried out aiming at the comprehensive contribution degree of the main body, so that the economic cost and pollutant emission are reduced while the benefits of optimized operation can be reasonably obtained by the cooperative operators. It can provide a better idea for the present application, but it has the following problems:
(1) Only relates to a gas turbine and a photovoltaic main body, and does not apply wind power generation, flexible load and energy storage to a model of a cooperative game;
(2) The user side is not considered to develop a low-carbon control strategy, namely, a low-carbon economic control method based on demand response is researched.
Most of the current research on virtual power plants is focused on scheduling and operation, and relatively few research on virtual power plant energy planning. Therefore, the prior art needs a multi-main-body game strategy capable of covering renewable energy sources, energy storage and flexible loads, and a corresponding low-carbon control strategy is formulated, and the main body forms a large alliance cooperative game to realize reasonable optimization of regional comprehensive energy sources, improve benefits and reduce cost and carbon emission.
For example: the energy flow optimization analysis of the regional power-natural gas-thermal comprehensive energy system considering the operation constraint [ J ]. Chinese motor engineering report 2017,37 (24): 7108-7120+7425.DOI:10.13334/j.0258-8013.pcsee.171240, wang Weiliang, wang Dan and the like are used for researching different constraint conditions of the system operation and exploring the influence of different types of disturbance on the operation.
For another example: the regional comprehensive energy system multi-objective optimal mixed power flow algorithm [ J ]. Chinese motor engineering journal, 2017,37 (20): 5829-5839.DOI:10.13334/j.0258-8013.Pcsee.161886. Lin Wei, xiaolong et al build low-carbon economic models considering economy and environment.
It can be seen that virtual power plants for terminal type comprehensive energy can perform benefit level distribution in a cooperation space by establishing economic and environmental constraints, but the difficulty is in the specific formulation of low-carbon strategies and decision aspect of multi-main cooperative games.
Disclosure of Invention
Aiming at the defects in the prior art, the application provides a virtual power plant multi-main-body game control strategy integrating wind and solar energy storage. The method aims to effectively improve the benefits in the area by establishing a competition strategy of a participation subject on a plurality of problems, maximize the economic benefits, reduce the carbon emission of renewable energy power generation and provide a new thought for subsequent new energy optimization operation research and engineering application.
The technical scheme adopted by the application for achieving the purpose is as follows:
a virtual power plant multi-main-body game control strategy integrating wind-solar storage comprises the following steps:
step 1, building a virtual power plant based on a wind-solar-storage comprehensive energy system, uniformly participating in electric power market transaction by an aggregation distributed power supply, and analyzing the cost of cold flexible load;
step 2, constructing an internal optimization model of a single virtual power plant by utilizing loads through multi-objective optimization; establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the virtual power plant optimization model;
step 3, constructing a multi-virtual power plant game cooperative game model aiming at the whole cooperative space on the basis of the step 1 and the step 2, and taking the maximum profit of each virtual power plant as a target, and self-adjusting the internal members of each virtual power plant to respond to the operation requirement so as to form a low-carbon control strategy for actively consuming renewable energy sources by the power grid on the premise of safe and economic operation;
and 4, reasonably distributing the electric energy of each device according to the benefit distribution model in the step 3, and considering a low-carbon operation control strategy into the virtual power plant to participate in the interactive market transaction of the power grid.
Still further, the cost of the cold flexible load of step 1 includes: distributed wind power, roof photovoltaic, storage battery and cost of cold flexible load of intelligent refrigerator.
Furthermore, the building of the virtual power plant by the comprehensive energy system based on wind-solar energy storage in step 1, the unified participation of the aggregation distributed power supply in the electric market transaction, the analysis of the cost of the cold flexible load, includes:
establishing a cost model of photovoltaic power generation and wind power generation, a cost model of storage battery power generation and cost analysis of demand response;
the photovoltaic power generation expression is as follows:
wherein ,PPV In order to obtain the photovoltaic power generation power,for the rated value of the photovoltaic power generation power, alpha and Beta are parameters of Beta distribution;
the operation cost of photovoltaic power generation is expressed as follows:
wherein ,photovoltaic power generation power denoted as time t; c (C) s The difference value between the online electricity price of the photovoltaic pole and the time-sharing electricity price at the moment is obtained; c (C) sl Cost for running loss;
the wind power generation cost is calculated, and the expression is as follows:
wherein ,the output is expressed as the moment t of the fan; c (C) w The value of the online electricity price and the time-sharing electricity price at the moment of the wind power pole; c (C) wl Cost for running loss;
the energy storage equipment adopted in the VPP is a storage battery, the operation mode is two types of charging and discharging, and when the VPP power generation unit stores redundant electric energy, the storage battery is charged; when the internal power supply of the VPP is insufficient, the storage battery is called to supply electric energy; and then determining the unit storage electric quantity of the storage battery, wherein the electric quantity is related to the charge-discharge efficiency and the loss, and the expression is as follows:
wherein sigma is the self-loss rate of the storage battery, and />Respectively represent the charge and discharge output, eta of the accumulator at the time t Cb and ηFb Respectively representing the charge and discharge efficiency of the accumulator, +.>The power of the storage battery at the time t-1;
the running cost function of the storage battery is obtained according to the charge and discharge cost generated by the full electricity of the storage battery:
wherein, consider the depreciation cost of the energy storage device caused by depth of discharge, discharge rate and frequent charge，C Cb Charge cost for storage battery C Fb The discharging cost of the storage battery is reduced;
each flexible load classification compensation has the expression:
wherein ,CVPP,b To compensate the total price, S r (i) Flexible load clock end, delta, expressed as a degree of importance i r The price is compensated for flexible load units of importance i.
Further, the multi-objective operation optimization model in step 2 includes:
(1) The economic objective, the calculation formula is expressed as:
wherein F is the total running cost of the system,the running state of the photovoltaic power generation at the time t is represented, and the value is 0 or 1, <>Indicating the running state of the storage battery at time t, and the value is 0 or 1 +.>Representing the running state of wind power generation at time t, with a value of 0 or 1 +.>The method comprises the steps of representing an interruption state of flexible load at t time, wherein the value is 0 or 1, and the expression is the cumulative minimum value of each cost of the virtual power plant in 24 hours a day;
(2) The environmental protection goal is represented by the following calculation formula:
wherein ,μc Mu, carbon emission coefficient for exchange with electric network b Carbon emission coefficient for energy storage output consumption, eta is power exchange coefficient, P C Exchanging power for connection line of micro-network and main network, S Db Is the total power of stored energy.
Still further, the determining constraints of the virtual power plant optimization model includes:
(1) Tie limit power constraint:
|P|≤P max
wherein ,PC Exchanging power for connection line of micro-network and main network, P max A power exchange limit value is used for connecting lines of the micro-network and the main network;
(2) The limit of charge and discharge of the accumulator is constrained:
0≤P Db ≤P Db,max ,P Cb,max ≤P Cb ≤0
wherein ,PDb 、P Db,max Is the discharge power and the maximum discharge power of the energy storage battery, P Cb 、P Cb,max Charging power and maximum charging power of the energy storage battery;
(3) SOC constraint:
SOC min ≤SOC≤SOC max
wherein SOC is state of charge, SOC min 、SOC max The upper limit and the lower limit of the allowable electric quantity when the energy storage battery works are set;
(4) Photovoltaic, fan output upper and lower limit constraint:
P s,min ≤P s ≤P s,max
P w,min ≤P w ≤P w,max
wherein ,Ps,min 、P s,max Maximum active output and minimum active output of photovoltaic in MPPT mode, P w,min 、P w,max The maximum active output and the minimum active output of the fan are P s For photovoltaic active power, P w Is the active force of the fan.
Further, step 3, constructing a cooperative game model of multi-virtual power plant game, wherein the pointers game under a protocol that all participants have a certain constraint force, and do not show a complete countermeasure relationship with each other, and assume that three virtual power plants game each other;
suppose that virtual power plant a is optimized alone, its scenario number is S a The probability of scene s isThe scheduling duration is deltat, the total time is T, the total power supply is N, and the output benefit corresponding to the power supply N is +.>
The benefits of the virtual power plant VPP mainly come from the actual output of the distributed power supply and the cost of the VPP for calling the system standby due to the output deviation, so that the maximum benefit expectations of independent optimization of the virtual power plant VPP exist:
wherein ,c+ and c- The distribution represents the back-up prices of the power plant up-and down-regulation,for the output of power source n in the t period of the virtual power plant a under the scene s, +.>To account for the difference between the planned and actual outputs, F (x) is a piecewise function, namely:
for collaborative optimization of multiple virtual power plants, assuming that M virtual power plants make up federation b, there is a maximum benefit of VPP federation b:
wherein ,output benefit corresponding to power plant m, +.>For the output of power supply n in t period under the scene s of virtual power plant m, +.>A difference value between the planned output and the actual output for the alliance;
m virtual Power plants V 1 ,V 2 ,...,V m Can form { V } 1 }，{V 1 ,V 2 ,...V m Etc., so there are characteristic functions of the federation:
v({V m })＝0
wherein c ({ V) 1 ,V 2 ,...V m }) represents the revenue of m VPP federations when optimizing operation, and x in c (x) takes V m Time c ({ V) m -v) represents the revenue for the individual operation of the virtual power plant m;
the overall rationality depends on the cooperative income scheme of each virtual power plant, and is as follows:
x V1 +x V2 +...+x VM ＝v({V 1 ,V 2 ,...,V M })
the individuality is that the total benefit is not lower than the benefit when the operation is carried out singly, and the expression is as follows:
x Vm ≥v({V m })
adopting NSGA-II optimization algorithm, and carrying out subsequent selection, crossover, genetics and iteration by judging the similarity of individuals and whether the population size is reached;
setting various basic data in the system, and after solving a cooperative game model by applying an NSGA-II optimization algorithm, comparing cost and carbon emission of whether to cooperate or not to carry out benefit distribution; searching sub-alliances which can meet the load, solving a characteristic function, and distributing benefits of the whole system by adopting a Shapley value method;
the Shapley value method calculation formula is expressed as:
wherein ,benefits obtained for ith member in federation, S i For the number of participants in the coalition, n is the number of members in the virtual power plant cooperative game system, v (S) is the operation income of the virtual power plant integral coalition, and v (S\ { i }) is the operation income of the cooperative coalition after the coalition S removes i.
Furthermore, the benefit distribution model reasonably distributes the electric energy of each device, considers the low-carbon operation control strategy into the virtual power plant to participate in the interactive market transaction of the power grid, specifically applies the model to the actual situation, considers the total cost and the total carbon emission under the normal operation condition of the actual system and the electric quantity distribution of each device in the virtual power plant, compares each main body after benefits are distributed through the cooperative game with the non-cooperative one, and judges the reliability of the low-carbon model.
A virtual power plant multi-body gaming control device integrating wind and solar energy storage, comprising:
the building module is used for building a virtual power plant based on a wind-solar-storage comprehensive energy system
The energy aggregation module is used for aggregating distributed power supplies to uniformly participate in electric market transaction and analyzing the cost of the cold flexible load;
the independent virtual power plant optimization module is used for constructing an internal optimization model of a single virtual power plant by utilizing loads through multi-objective optimization; establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the virtual power plant optimization model;
the multi-virtual power plant cooperative game module is used for constructing a cooperative game model of multi-virtual power plant games, taking the maximum profit of each virtual power plant as a target, and the internal members of each virtual power plant self-regulate to respond to the operation requirement so as to form a low-carbon control strategy for actively consuming renewable energy sources by the power grid on the premise of safe and economic operation;
and the benefit distribution module is used for reasonably distributing the electric energy of each device according to the benefit distribution model, and taking the low-carbon operation control strategy into consideration for the virtual power plant to participate in the interactive market transaction of the power grid.
The computer equipment comprises a storage medium, a processor and a computer program which is stored on the storage medium and can run on the processor, wherein the processor realizes any one of the steps of integrating the virtual power plant multi-main-body game control strategy and the device of wind-solar storage when executing the computer program.
A computer storage medium, on which a computer program is stored, the computer program when executed by a processor implementing any of the steps of a virtual power plant multi-body game control strategy and device integrating wind and solar energy storage.
The application has the following beneficial effects and advantages:
1. the sub-alliances constructed by different main bodies in the independent VPP in a cooperative mode can effectively improve the energy utilization efficiency and reduce the running cost and carbon dioxide emission in the system;
2. the application applies NSGA-II optimization algorithm to solve the cost-carbon emission function of alliance, and has higher operation efficiency and optimizing capability;
3. the Shapley value method comprehensively considering economy and carbon emission reduction can more reasonably distribute benefits of all main bodies in the system, and can encourage more independent VPPs to participate in building a collaborative VPP alliance;
4. the multi-VPP system constructed based on the cooperative game can better realize the maximum overall benefit and the minimum carbon emission.
Drawings
The foregoing and/or additional aspects and advantages of the application will become apparent and may be better understood from the following description of embodiments taken in conjunction with the accompanying drawings in which:
FIG. 1 is a virtual power plant cooperative game energy flow diagram of an embodiment of the present application;
FIG. 2 is a flow chart of a virtual power plant multi-master gaming solution in accordance with an embodiment of the present application;
fig. 3 is a flow chart of NSGA-II optimization algorithm of an embodiment of the present application.
Detailed Description
In order that the above-recited objects, features and advantages of the present application will be more clearly understood, a more particular description of the application will be rendered by reference to the appended drawings and appended detailed description. It should be noted that, without conflict, the embodiments of the present application and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, however, the present application may be practiced in other ways than those described herein, and therefore the scope of the present application is not limited to the specific embodiments disclosed below.
The following describes some embodiments of the present application with reference to fig. 1-3.
Example 1
The application provides an embodiment, which is a virtual power plant multi-main-body game control strategy integrating wind-solar storage, and specifically comprises the following steps:
and 1, building a virtual power plant based on a wind-solar-storage comprehensive energy system, uniformly participating in electric market transaction by a polymerization distributed power supply, and analyzing the cost of cold flexible loads such as distributed wind power, roof photovoltaic, storage batteries, intelligent refrigerators and the like.
Firstly, building a cost model of photovoltaic power generation and wind power generation, a cost model of storage battery power generation and cost analysis of demand response, and preparing for building an optimized scheduling model of a virtual power plant. The whole multi-energy collaborative optimization control module comprises a plurality of power supply modes such as wind power, photovoltaic, energy storage, commercial power and the like, most of end users can not realize information sharing and multi-energy coupling only by adopting a single power supply mode by using independent equipment, so that roof photovoltaic, distributed wind power, energy storage and cold flexible loads are assembled, and a large number of low-efficiency equipment is avoided.
And solving the strategy and solving flow aiming at the energy flow diagram, wherein the solving flow diagram is shown in fig. 2. All participating subjects form a big alliance, the strategy is a scheduling scheme of each device, the cost to be saved is obtained in the small alliance by comparing with the scheme of whether to cooperate or not, and then the large alliance is distributed with benefits after searching for a feasible small alliance to solve.
The main principle of photovoltaic power generation is that light energy irradiated by solar light onto a battery plate is converted into electric energy, and the photovoltaic power generation has randomness due to the fact that the photovoltaic power generation is obviously influenced by weather, and the photovoltaic power generation belongs to an uncontrollable distributed power source. The priority of the photovoltaic power generation in the VPP is higher than that of other power generation units, and the power generation power is mainly determined by irradiance, so that the expression is as follows:
wherein ,PPV In order to obtain the photovoltaic power generation power,for the rating of the photovoltaic power generation power, α and β are parameters of the Beta distribution.
When the photovoltaic power generation cost is calculated, the electricity price difference value and the loss are considered, so that the operation cost of the photovoltaic power generation can be simplified, and the expression is as follows:
wherein ,photovoltaic power generation power denoted as time t; c (C) s The difference value between the online electricity price of the photovoltaic pole and the time-sharing electricity price at the moment is obtained; c (C) sl Cost for operation.
The wind power generation cost is calculated, and the expression of wind power generation is similar to that of photovoltaic power generation, so that the expression is as follows:
wherein ,the output is expressed as the moment t of the fan; c (C) w The value of the online electricity price and the time-sharing electricity price at the moment of the wind power pole; c (C) wl Cost for operation.
The energy storage equipment adopted in the VPP is mainly a storage battery, the operation modes of the energy storage equipment are charging and discharging, and when the VPP power generation unit stores redundant electric energy, the storage battery is charged; when the internal power supply of the VPP is insufficient, the storage battery is called to supply electric energy.
Then, determining the unit storage electric quantity of the storage battery, wherein the electric quantity is related to the charge-discharge efficiency and the loss, so that the expression is as follows:
wherein sigma is the self-loss rate of the storage battery, and />Respectively represent the charge and discharge output, eta of the accumulator at the time t Cb and ηFb Respectively representing the charge and discharge efficiency of the accumulator, +.>The power of the storage battery at the time t-1.
Further, the running cost function of the storage battery is obtained according to the charge and discharge cost generated by the full electricity of the storage battery:
wherein, C takes into account depreciation cost of the energy storage device caused by depth of discharge, discharge rate and frequent charging Cb Charge cost for storage battery C Fb And discharging the storage battery.
Demand response aims to respond to price or incentive mechanisms by users in the electric market, and change original electricity utilization behaviors. The VPP regulates the power balance of the system by controlling cold flexible loads such as air conditioners, intelligent ice and snow and the like and cutting the loads, but the economic contradiction exists between the flexible loads and operators and users, namely, if the compensation electricity price is fixed, the importance of the cut loads is high, the user compensation is increased, the importance of the cut loads is low, and the operators obtain less economic benefits, so the application compensates each flexible load in a classified way according to the problems, and the expression is as follows:
wherein ,CVPP,b To compensate the total price, S r (i) Flexible load clock end, delta, expressed as a degree of importance i r The price is compensated for flexible load units of importance i.
Step 2, constructing an internal optimization model of a single virtual power plant by multi-objective optimization and applying the part and the interruptible load contained in the step 1; and establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the VPP optimization model.
And establishing an economic target and an environmental protection target, forming all units in the virtual power plant, and establishing an internal model and a constraint function of a single virtual power plant by taking the minimum internal operation cost and the minimum carbon emission of the virtual power plant as targets.
(1) Economic targets.
Firstly, ensuring an economic target, namely the lowest cost of system operation optimization, wherein a calculation formula is expressed as follows:
wherein F is the total running cost of the system,the running state of the photovoltaic power generation at the time t is represented, and the value is 0 or 1, <>Indicating the running state of the storage battery at time t, and the value is 0 or 1 +.>Representing the running state of wind power generation at time t, with a value of 0 or 1 +.>The interruption state of the flexible load at time t is indicated, and the value is 0 or 1. The expression is the cumulative minimum value of each cost of the virtual power plant at 24 hours a day.
(2) Environmental protection targets.
The goal of environmental protection is to ensure that carbon dioxide-based pollutant emissions are minimized during system operation, and the calculation formula is expressed as:
wherein ,μc Mu, carbon emission coefficient for exchange with electric network b Carbon emission coefficient for energy storage output consumption, eta is power exchange coefficient, P C Exchanging power for connection line of micro-network and main network, S Db Is the total power of stored energy.
The virtual power plant is equivalent to a multi-energy coordinated energy supply system, so that the cold, heat and electric loads of the system are required to reach the supply and demand balance in order to internally ensure the energy utilization stability of users and the energy utilization cost is the lowest, and meanwhile, various energy supply devices in the system must meet the running constraint of the energy supply device in the running process. The above together form a constraint condition for the system operation, and the following is concrete:
(5) Tie-line limit power constraints.
|Pc|≤P max
wherein ,PC Exchanging power for connection line of micro-network and main network, P max And (5) connecting line power exchange limit values for the micro network and the main network.
(6) And the charge and discharge limit of the storage battery is restricted.
0≤P Db ≤P Db,max ,P Cb,max ≤P Cb ≤0
wherein ,PDb 、P Db,max Is the discharge power and the maximum discharge power of the energy storage battery, P Cb 、P Cb,max Charging power and maximum charging power of the energy storage battery.
(7) SOC constraints.
SOC min ≤SOC≤SOC max
Wherein SOC is state of charge, SOC min 、SOC max The upper limit and the lower limit of the allowable electric quantity when the energy storage battery works are provided.
(8) Photovoltaic and fan output upper and lower limit constraint.
P s,min ≤P s ≤P s,max
P w,min ≤P w ≤P w,max
wherein ,Ps,min 、P s,max Maximum active output and minimum active output of photovoltaic in MPPT mode, P w,min 、p w,max The maximum active output and the minimum active output of the fan are P s For photovoltaic active power, P w Is the active force of the fan.
And 3, constructing a multi-virtual power plant game cooperative game model on the basis of the step 1 and the step 2 aiming at the whole cooperative space, and taking the maximum profit of the VPPs of each virtual power plant as a target, and enabling the internal members of the VPPs of each virtual power plant to self-regulate to respond to the operation requirement so as to form a low-carbon control strategy for actively absorbing renewable energy sources on the premise of safe and economic operation of the power grid.
Under the condition of mature market, a plurality of VPPs are taken as market main bodies to participate in market competition, and the benefits of the VPPs are improved while the safe and economic operation of the power grid is ensured. According to the multi-subject cooperative game, an NSGA-II optimization algorithm is applied to output a pareto optimal solution set, and then distribution of cooperative benefits is calculated based on the shape value of comprehensive contribution.
The game theory is mainly applied to bidding aspects of the electric power market, and is mainly characterized in that the relevance and conflict of participants in interests; the participants respectively make optimization to ensure that the benefit is maximum; the participant's profits and decisions will affect each other. The application adopts cooperative game, namely, the game is mainly carried out under a protocol with a certain constraint force aiming at all participants, the game does not show a complete countermeasure relationship, three virtual power plants are supposed to game each other, and the three games are shown in figure 3.
Suppose that virtual power plant a is optimized alone, its scenario number is S a The probability of scene s isThe scheduling duration is deltat, the total time is T, the total power supply is N, and the output benefit corresponding to the power supply N is +.>
The main sources of VPP revenues are the same as the actual output revenues of the distributed power supply, and VPP has the maximum benefit expectations of VPP independent optimization because of the cost of the output deviation calling system standby:
wherein ,c+ and c- The distribution represents the back-up prices of the power plant up-and down-regulation,for the power output of the virtual power plant a in the t period of the power source n in the scene s, Δt is the scheduling duration, < ->To account for the difference between the planned and actual outputs, F (x) is a piecewise function, namely:
for collaborative optimization of multiple virtual power plants, assuming that M virtual power plants make up federation b, there is a maximum benefit of VPP federation b:
wherein ,output benefit corresponding to power plant m, +.>For the output of power supply n in t period under the scene s of virtual power plant m, +.>The difference between the planned output and the actual output of the alliance is obtained, and N is the total number of power supplies.
Thus M virtual power plants V 1 ,V 2 ,...,V m Can form { V } 1 }，{V 1 ,V 2 ,...V m Etc., so there are characteristic functions of the federation:
v({V m })＝0
wherein c ({ V) 1 ,V 2 ,...V m }) represents the revenue of m VPP federations when optimizing operation, and x in c (x) takes V m Time c ({ V) m }) is expressed as the benefit of the virtual power plant m operating alone.
And then determining the individual rationality and the overall rationality of the cooperative game, wherein the overall rationality depends on the cooperative income schemes of the virtual power plants, and the overall rationality is as follows:
x V1 +x V2 +...+x VM ＝v({V 1 ,V 2 ,...,V M })
while the individuality is that the total benefit cannot be lower than that of the independent operation, the expression is:
x Vm ≥v({V m })
because the multi-virtual power plant cooperative game model disclosed by the application belongs to a nonlinear multi-objective optimization problem, a NSGA-II optimization algorithm is adopted, and subsequent selection, crossover, inheritance and iteration are performed by judging the similarity of individuals and whether the group size is reached, and a flow chart for solving is shown in figure 3.
NSGA-II is a model that studies the optimization of more than one objective function over a given area, known as multi-objective planning. In order to construct the cooperative game model, the situation that the participation subject does not participate in cooperation and forms sub-alliances exists in the whole regional cooperative alliances can be analyzed, and the excessive or lack of resources can greatly influence the running cost of the system under the condition of low coupling degree of the participation subject and the sub-alliances.
Setting various basic data in the system, and after solving the cooperative game model by applying an NSGA-II optimization algorithm, comparing the cost and carbon emission of the cooperation or not to carry out benefit distribution. Searching sub-alliances which can meet the load, solving the characteristic function, and distributing benefits to the whole system by adopting a Shapley value method.
The idea of the Shapley method is that the gaming principal's benefit distribution value is equal to the sum of the principal's all over contributions to all leagues that it participates in, and the calculation formula is:
wherein ,benefits obtained for ith member in federation, S i For the number of participants in the coalition, n is the number of members in the virtual power plant cooperative game system, v (S) is the operation income of the virtual power plant integral coalition, and v (S\ { i }) is the operation income of the cooperative coalition after the coalition S removes i.
By the Shapley method, the contribution of participation subjects in the federation to the multidimensional contribution of the federation is considered, and more benefits are given to subjects having the multidimensional contribution and larger contribution to the promotion. And then benefits are distributed for comprehensive economy and carbon emission of the energy storage batteries, the heat storage devices, the roof photoelectricity and the distributed wind power in the virtual power plant.
And 4, reasonably distributing the electric energy of each device according to the benefit distribution model in the step 3, and considering a low-carbon operation control strategy into the virtual power plant to participate in the interactive market transaction of the power grid.
The model is specifically applied to the actual situation, and the reliability of the low-carbon model is judged by considering the total cost, the total carbon emission and the electric quantity distribution of all equipment in the virtual power plant under the condition of normal operation of an actual system.
Substituting actual park data, comparing each subject after benefits are distributed through the cooperative game with the subjects before the cooperation is not performed, and proving that the virtual power plant multi-subject game control strategy integrating wind-solar storage can reduce the total cost and carbon dioxide emission of system operation, is scientific and effective in benefit distribution, and can better stimulate cooperation and distribution of participation subjects in the alliance.
Example 2
The application also provides an embodiment, which is a virtual power plant multi-main-body game control device integrating wind-solar storage, comprising:
the step 1 comprises the following steps: the building module is used for building a virtual power plant based on a wind-solar-storage comprehensive energy system
The energy aggregation module is used for aggregating distributed power supplies to uniformly participate in electric market transaction and analyzing the cost of the cold flexible load;
the step 2 comprises the following steps: the independent virtual power plant optimization module is used for constructing an internal optimization model of a single virtual power plant by utilizing loads through multi-objective optimization; establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the virtual power plant optimization model;
the step 3 comprises the following steps: the multi-virtual power plant cooperative game module is used for constructing a cooperative game model of multi-virtual power plant games, taking the maximum profit of each virtual power plant as a target, and the internal members of each virtual power plant self-regulate to respond to the operation requirement so as to form a low-carbon control strategy for actively consuming renewable energy sources by the power grid on the premise of safe and economic operation;
step 4 comprises: and the benefit distribution module is used for reasonably distributing the electric energy of each device according to the benefit distribution model, and taking the low-carbon operation control strategy into consideration for the virtual power plant to participate in the interactive market transaction of the power grid.
Example 3
Based on the same inventive concept, the embodiment of the application also provides a computer device, which comprises a storage medium, a processor and a computer program stored on the storage medium and capable of running on the processor. And the steps of any one of the virtual power plant multi-main-body game control strategy and device integrating wind and solar energy storage as described in the embodiment 1 or 2 are realized when the processor executes the computer program.
Example 4
Based on the same inventive concept, the embodiment of the application further provides a computer storage medium, and a computer program is stored on the computer storage medium, and when the computer program is executed by a processor, the steps of any one of the virtual power plant multi-main-body game control strategy and device integrating wind and solar energy storage described in the embodiment 1 or 2 are realized.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present application and not for limiting the same, and although the present application has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the application without departing from the spirit and scope of the application, which is intended to be covered by the claims.
Claims (10)
1. A virtual power plant multi-main-body game control strategy integrating wind-solar storage is characterized in that: the method comprises the following steps:
step 1, building a virtual power plant based on a wind-solar-storage comprehensive energy system, uniformly participating in electric power market transaction by an aggregation distributed power supply, and analyzing the cost of cold flexible load;
step 2, constructing an internal optimization model of a single virtual power plant by utilizing loads through multi-objective optimization; establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the virtual power plant optimization model;
step 3, constructing a multi-virtual power plant game cooperative game model aiming at the whole cooperative space on the basis of the step 1 and the step 2, and taking the maximum profit of each virtual power plant as a target, and self-adjusting the internal members of each virtual power plant to respond to the operation requirement so as to form a low-carbon control strategy for actively consuming renewable energy sources by the power grid on the premise of safe and economic operation;
and 4, reasonably distributing the electric energy of each device according to the benefit distribution model in the step 3, and considering a low-carbon operation control strategy into the virtual power plant to participate in the interactive market transaction of the power grid.
2. The virtual power plant multi-body game control strategy integrating wind and solar energy storage according to claim 1, wherein the virtual power plant multi-body game control strategy integrating wind and solar energy storage is characterized in that: the cost of the cold flexible load of step 1, comprising: distributed wind power, roof photovoltaic, storage battery and cost of cold flexible load of intelligent refrigerator.
3. The virtual power plant multi-body game control strategy integrating wind and solar energy storage according to claim 1, wherein the virtual power plant multi-body game control strategy integrating wind and solar energy storage is characterized in that: the step 1 of establishing a virtual power plant based on the wind-solar energy storage comprehensive energy system, wherein the aggregation distributed power supply uniformly participates in the electric power market transaction, and the analysis of the cost of the cold flexible load comprises the following steps:
establishing a cost model of photovoltaic power generation and wind power generation, a cost model of storage battery power generation and cost analysis of demand response;
the photovoltaic power generation expression is as follows:
wherein ,PPV In order to obtain the photovoltaic power generation power,for the rated value of the photovoltaic power generation power, alpha and Beta are parameters of Beta distribution;
the operation cost of photovoltaic power generation is expressed as follows:
wherein ,photovoltaic power generation power denoted as time t; c (C) s The difference value between the online electricity price of the photovoltaic pole and the time-sharing electricity price at the moment is obtained; c (C) sl Cost for running loss;
the wind power generation cost is calculated, and the expression is as follows:
wherein ,the output is expressed as the moment t of the fan; c (C) w The value of the online electricity price and the time-sharing electricity price at the moment of the wind power pole; c (C) wl Cost for running loss;
the energy storage equipment adopted in the VPP is a storage battery, the operation mode is two types of charging and discharging, and when the VPP power generation unit stores redundant electric energy, the storage battery is charged; when the internal power supply of the VPP is insufficient, the storage battery is called to supply electric energy; and then determining the unit storage electric quantity of the storage battery, wherein the electric quantity is related to the charge-discharge efficiency and the loss, and the expression is as follows:
wherein sigma is the self-loss rate of the storage battery, and />Respectively represent the charge and discharge output, eta of the accumulator at the time t Cb and ηFb Respectively representing the charge and discharge efficiency of the accumulator, +.>The power of the storage battery at the time t-1;
the running cost function of the storage battery is obtained according to the charge and discharge cost generated by the full electricity of the storage battery:
wherein, consider the depreciation cost of the energy storage device caused by depth of discharge, discharge rate and frequent charge，C Cb Charge cost for storage battery C Fb The discharging cost of the storage battery is reduced;
each flexible load classification compensation has the expression:
wherein ,CVPP,b To compensate the total price, S r (i) Flexible load clock end, delta, expressed as a degree of importance i r The price is compensated for flexible load units of importance i.
4. The virtual power plant multi-body game control strategy integrating wind and solar energy storage according to claim 1, wherein the virtual power plant multi-body game control strategy integrating wind and solar energy storage is characterized in that: the multi-objective operation optimization model in step 2 includes:
(1) The economic objective, the calculation formula is expressed as:
wherein F is the total running cost of the system,the running state of the photovoltaic power generation at the time t is represented, and the value is 0 or 1, <>Indicating the running state of the storage battery at time t, and the value is 0 or 1 +.>Representing the running state of wind power generation at time t, with a value of 0 or 1 +.>The interruption state of the flexible load at the time t is represented as 0 or 1, and the expression is that the virtual power plant accumulates the cost for 24 hours a dayCounting a minimum value;
(2) The environmental protection goal is represented by the following calculation formula:
wherein ,μc Mu, carbon emission coefficient for exchange with electric network b Carbon emission coefficient for energy storage output consumption, eta is power exchange coefficient, P C Exchanging power for connection line of micro-network and main network, S Db Is the total power of stored energy.
5. The virtual power plant multi-body game control strategy integrating wind and solar energy storage according to claim 1, wherein the virtual power plant multi-body game control strategy integrating wind and solar energy storage is characterized in that: the determining constraints of the virtual power plant optimization model includes:
(1) Tie limit power constraint:
|P c |≤P max
wherein ,PC Exchanging power for connection line of micro-network and main network, P max A power exchange limit value is used for connecting lines of the micro-network and the main network;
(2) The limit of charge and discharge of the accumulator is constrained:
0≤P Db ≤P Db,max ,P Cb,max ≤P Cb ≤0
wherein ,PDb 、P Db,max Is the discharge power and the maximum discharge power of the energy storage battery, P Cb 、P Cb,max Charging power and maximum charging power of the energy storage battery;
(3) SOC constraint:
SOC min ≤SOC≤SOC max
wherein SOC is state of charge, SOC min 、SOC max The upper limit and the lower limit of the allowable electric quantity when the energy storage battery works are set;
(4) Photovoltaic, fan output upper and lower limit constraint:
P s,min ≤P s ≤P s,max
P w,min ≤P w ≤P w,max
wherein ,Ps,min 、P s,max Maximum active output and minimum active output of photovoltaic in MPPT mode, P w,min 、P w,max The maximum active output and the minimum active output of the fan are P s For photovoltaic active power, P w Is the active force of the fan.
6. The virtual power plant multi-body game control strategy integrating wind and solar energy storage according to claim 1, wherein the virtual power plant multi-body game control strategy integrating wind and solar energy storage is characterized in that: step 3, constructing a cooperative game model of multi-virtual power plant games, wherein pointers game under a protocol that all participants have a certain constraint force, and the three virtual power plants are supposed to game each other without showing a complete countermeasure relationship;
suppose that virtual power plant a is optimized alone, its scenario number is S a The probability of scene s isThe scheduling duration is deltat, the total time is T, the total power supply is N, and the output benefit corresponding to the power supply N is +.>
The benefits of the virtual power plant VPP mainly come from the actual output of the distributed power supply and the cost of the VPP for calling the system standby due to the output deviation, so that the maximum benefit expectations of independent optimization of the virtual power plant VPP exist:
wherein ,c+ and c- The distribution represents the back-up prices of the power plant up-and down-regulation,for the output of power source n in the t period of the virtual power plant a under the scene s, +.>To account for the difference between the planned and actual outputs, F (x) is a piecewise function, namely:
for collaborative optimization of multiple virtual power plants, assuming that M virtual power plants make up federation b, there is a maximum benefit of VPP federation b:
wherein ,output benefit corresponding to power plant m, +.>For the output of power supply n in t period under the scene s of virtual power plant m, +.>A difference value between the planned output and the actual output for the alliance;
m virtual Power plants V 1 ,V 2 ,...,V m Can form { V } 1 }，{V 1 ,V 2 ,.. M } and so on, there are characteristic functions of the federation:
v({V m })＝0
wherein c ({ V) 1 ,V 2 ,...V m }) represents the revenue of m VPP federations when optimizing operation, and x in c (x) takes V m Time c ({ V) m -v) represents the revenue for the individual operation of the virtual power plant m;
the overall rationality depends on the cooperative income scheme of each virtual power plant, and is as follows:
x V1 +x V2 +...+x VM ＝v({V 1 ,V 2 ,...,V M })
the individuality is that the total benefit is not lower than the benefit when the operation is carried out singly, and the expression is as follows:
x Vm ≥v({V m })
adopting NSGA-II optimization algorithm, and carrying out subsequent selection, crossover, genetics and iteration by judging the similarity of individuals and whether the population size is reached;
setting various basic data in the system, and after solving a cooperative game model by applying an NSGA-II optimization algorithm, comparing cost and carbon emission of whether to cooperate or not to carry out benefit distribution; searching sub-alliances which can meet the load, solving a characteristic function, and distributing benefits of the whole system by adopting a Shapley value method;
the Shapley value method calculation formula is expressed as:
wherein ,benefits obtained for ith member in federation, S i For the number of participants in the coalition, n is the number of members in the virtual power plant cooperative game system, v (S) is the operation income of the virtual power plant integral coalition, and v (S\ { i }) is the operation income of the cooperative coalition after the coalition S removes i.
7. The virtual power plant multi-body game control strategy integrating wind and solar energy storage according to claim 1, wherein the virtual power plant multi-body game control strategy integrating wind and solar energy storage is characterized in that: the benefit distribution model reasonably distributes electric energy of each device, considers a low-carbon operation control strategy into the virtual power plant to participate in the interactive market transaction of the power grid, specifically applies the model to actual conditions, considers total cost and total carbon emission under the normal operation condition of an actual system and electric quantity distribution of each device in the virtual power plant, compares each main body after benefits are distributed through a cooperative game with the main body before the main body is not cooperated, and judges the reliability of the low-carbon model.
8. A virtual power plant multi-main-body game control device integrating wind-solar storage is characterized in that: comprising the following steps:
the building module is used for building a virtual power plant based on a wind-solar-storage comprehensive energy system
The energy aggregation module is used for aggregating distributed power supplies to uniformly participate in electric market transaction and analyzing the cost of the cold flexible load;
the independent virtual power plant optimization module is used for constructing an internal optimization model of a single virtual power plant by utilizing loads through multi-objective optimization; establishing an objective function by using economic benefit maximization and carbon emission minimization, establishing a multi-objective operation optimization model, and determining each constraint of the virtual power plant optimization model;
the multi-virtual power plant cooperative game module is used for constructing a cooperative game model of multi-virtual power plant games, taking the maximum profit of each virtual power plant as a target, and the internal members of each virtual power plant self-regulate to respond to the operation requirement so as to form a low-carbon control strategy for actively consuming renewable energy sources by the power grid on the premise of safe and economic operation;
and the benefit distribution module is used for reasonably distributing the electric energy of each device according to the benefit distribution model, and taking the low-carbon operation control strategy into consideration for the virtual power plant to participate in the interactive market transaction of the power grid.
9. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the steps of a virtual power plant multi-body gaming control strategy and apparatus integrating wind and solar storage as claimed in any one of claims 1-8 when the computer program is executed by the processor.
10. A computer storage medium, characterized by: the computer storage medium is provided with a computer program, and the computer program when executed by a processor realizes the steps of the virtual power plant multi-main-body game control strategy and device for integrating wind and solar energy storage according to any one of claims 1-8.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117477660A (en) * | 2023-10-16 | 2024-01-30 | 广州高新区能源技术研究院有限公司 | Soft light storage and filling system joint regulation and control method and system based on VPP (virtual private point) demand response |
| CN117541300A (en) * | 2024-01-08 | 2024-02-09 | 国网浙江省电力有限公司宁波供电公司 | Virtual power plant transaction management method, system, equipment and storage medium |
| CN117810980A (en) * | 2023-12-28 | 2024-04-02 | 南京理工大学 | Optical storage virtual grid game optimization method based on free transaction of energy storage system |
| CN118070988A (en) * | 2024-04-25 | 2024-05-24 | 国网山东省电力公司营销服务中心(计量中心) | Virtual power plant distributed photovoltaic energy storage system configuration optimization method and device |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117477660A (en) * | 2023-10-16 | 2024-01-30 | 广州高新区能源技术研究院有限公司 | Soft light storage and filling system joint regulation and control method and system based on VPP (virtual private point) demand response |
| CN117477660B (en) * | 2023-10-16 | 2024-05-28 | 广州高新区能源技术研究院有限公司 | Soft light storage and filling system joint regulation and control method and system based on VPP (virtual private point) demand response |
| CN117810980A (en) * | 2023-12-28 | 2024-04-02 | 南京理工大学 | Optical storage virtual grid game optimization method based on free transaction of energy storage system |
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