CN110135613B - Multi-virtual power plant collaborative optimization operation scheme based on Nash negotiation - Google Patents
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Abstract
The invention discloses a collaborative optimization operation scheme of multiple virtual power plants based on Nash negotiation, which relates to the field of collaborative optimization operation of multiple virtual power plants and comprises a plurality of virtual power plants, wherein the virtual power plants form a comprehensive energy cooperative community, and the coordination interaction among the virtual power plants is constructed as a collaborative interaction model based on Nash negotiation:subject to: the internal constraints of the virtual power plant i,(6):(9)variables:on the basis of the cooperative operation of multiple virtual power plants, the cooperative operation model of the multiple virtual power plants under the background of comprehensive energy is further considered, so that the completeness and the advancement of the model are improved; a Nash negotiation mechanism and an alternative direction multiplier method are introduced, and the decision independence and the information privacy of each virtual power plant are guaranteed on the basis of promoting the cooperation and interaction of different virtual power plants.
Description
Technical Field
The invention relates to the field of collaborative optimization operation of multiple virtual power plants, in particular to a collaborative optimization operation scheme of multiple virtual power plants based on Nash negotiation.
Background
With the popularization of concepts such as an integrated energy system and an energy internet, the energy industry is continuously developing towards a safe, efficient and sustainable multi-energy integrated energy utilization mode. The cogeneration System based on distributed energy realizes multifunctional targets of higher energy utilization rate, lower energy cost, better environmental protection and the like through the cascade utilization of energy, and also becomes an important direction and form of a future energy System (see document 1: singing, wu Geng, li Ran, and the like, key problems and prospects of comprehensive demand-side response in the energy internet [ J ] Power grid Technology,2016,40 (11): 3391-3398.ZENG Ming, WU Geng, LI Ran, et al.Key schemes and protocols of integrated demand in energy internet J ]. Power System Technology,2016,40 (11): 3391-3398. Due to the fact that geographical positions of different types of distributed energy sources are scattered and lack of coordination, the problems that resource allocation is unreasonable, the overall safety of a system is not strong and the like are inevitable. Based on advanced communication, metering and control technologies, virtual power plant technologies (see documents 2: zhou Yizhou, sun Guojiang, yellow text, and the like. Multi-region virtual power plant integrated energy coordinated scheduling optimization model [ J ]. Chinese Motor engineering report, 2017,37 (23): 6780-6790+7069.ZHOU Yizou, SUN guoqiang, HUANG Wenjin, et al. Optimized multi-regional integrated energy coordinated scheduling of a virtual power plant [ J ]. Proceedings of CSEE,2017,37 (23): 6780-6790 7069.) can also be used for aggregating distributed energy of different regions, and the coordinated optimization control of the integrated energy systems of different regions is realized through higher-level software control, so that higher economic and environmental protection benefits are obtained. The virtual power plant can reasonably adjust an internal optimization strategy according to the operation requirement or the power market requirement of the distributed power supply, realize internal cooperative operation and meet the power market requirement, and achieve the optimal environmental and economic benefits.
The system belongs to different benefit agents, and different virtual power plants participate in market operation according to self operation targets and integrally different distributed resources. In the operation decision of the virtual power plant, internal resources of the virtual power plant need to be reasonably integrated and controlled, and competition or cooperation interaction with other virtual power plants is considered according to external conditions.
At present, most of research of virtual power plants focuses on optimized operation in a single virtual power plant market environment, and the research rules for interaction relations of multiple virtual power plants are relatively blank. Document [4] (Fu H, zhang X p. Mark equivalent in Active Distribution System with μ VPPs: a coevolutional Approach [ J ]. IEEE Access,2017, 8194-8204.) a double-layer non-cooperative game model of multiple virtual power plants in an Active power Distribution market is established, the upper layer represents that different virtual power plants operate as independent quotation main bodies in an autonomous optimization manner, and the lower layer represents that the social benefit of market clearing is maximized. The result shows that the bidding/quotation strategy of the virtual power plant not only depends on the grid connection level of the distributed power supply, but also is influenced by the quotation strategy of an opponent (other virtual power plants). Document [5] (Zhou Bo, lv Lin, gao Gongjun, etc.. Multiple virtual Power plant day-ahead robust trading strategy research [ J ]. Grid Technology,2018,42 (08): 2694-2703.ZHOU Bo, LV Lin, GAO hongjun, et al, robust day-ahead tracking strategy for multi-virtual Power plant [ J ]. Power System Technology,2018,42 (08): 2694-2703.) also constructs a multiple virtual Power plant non-cooperative game model, each virtual Power plant body fully considers the strategy influence of the rest competitors to pursue the maximization of the benefit of the competitors. It should be noted that the interaction relationship of the virtual power plants in the above research is a non-cooperative competition relationship, and each virtual power plant independently operates to seek the maximization of its own benefit without considering the cooperative complementary relationship among different virtual power plants. In consideration of the source-load difference in different Virtual Power Plants, some Virtual Power Plants may generate surplus Power at the same time, and some Virtual Power Plants may have Power shortage, and the document [6] (Wang Y, ai X, tan Z, et al. Interactive Dispatch models and double Stratage of Multiple Virtual Power Plants Based on Demand Response and Game Theory [ J ]. IEEE Transactions on Smart Grid,2016,7 (1): 510-519.) constructs a collaborative interaction model of Multiple Virtual Power Plants, thereby fully utilizing the complementary difference characteristics among different Virtual Power Plants. However, the different virtual power plants in document [6] are controlled by the same coordination control center, which is actually equivalent to a larger virtual power plant, and neglects the independence of the decision subjects of the different virtual power plants. The document [7] (Liu Saiyuan, ai Qian, zheng Jianping, etc.. Multiple time scale multiple virtual plant double layer coordination mechanism and operation strategy [ J ]. Chinese Motor engineering report, 2018,38 (03): 753-761.LIU siyuan, AI Qian, ZHEN Jianging, et al. Bilevel coordination mechanism and operation strategy of multiple-time scale multiple virtual power plant places [ J ]. Proceedings of CESS,2018,38 (03): 753-761.) also considers the possibility of direct transaction of cooperation of different virtual plants and constructs the cooperative interaction of virtual plants as a cooperative game model. It should be noted that although the establishment of the profit sharing mechanism in the cooperative game ensures the independence of the earnings of different virtual power plants, the profit sharing mechanism still depends on a common regulation center during the cooperative scheduling. Document [8] (Liu Jichun, tang Hu, oriented moon, etc.. Consider a multi-stage market trading approach [ J ] Power Construction involving multiple virtual Power plants, 2017,38 (03): 137-144.Liu jichun, tang hu, xiang yue, et al. Multi-stage mark transfer method with separation of virtual Power plants [ J ]. Electric Power configuration, 2017,38 (03): 137-144.) also consider the case of complementary Power supply among multiple virtual Power plants: the surplus electric quantity of the virtual power plant is shared among different virtual power plants on the basis that the internal supply and demand are met. And a sequential negotiation relationship is presented between the buyer virtual power plant and the seller virtual power plant. The above documents discuss interaction situations among multiple virtual power plants from the perspective of competition or cooperation, however, it should be noted that the above research mainly focuses on optimization of electric quantity interaction form, and the electric-thermal coupling situation in the context of comprehensive energy sources is not involved. The cogeneration unit, as one of the common members of the virtual power plant, has a great proportion in the development of the energy internet, and will influence the energy type of the virtual power plant in the future. Meanwhile, the research on the cooperation of the virtual power plant ignores the decision independence and the information privacy in the cooperation process of the virtual power plant. Unlike a single virtual power plant operation controlled by one operation control center, cooperative interaction of multiple virtual power plants involves coordinated optimization of multiple benefit agents with multiple control centers. Because different virtual power plants belong to different operation subjects, the difference of benefit demands of participating subjects must be ensured in cooperation operation among multiple virtual power plants. Meanwhile, with the development of information management technology, the requirements of participants on information privacy are gradually improved, and the cooperation operation among multiple virtual power plants should ensure the information privacy in the cooperation process of each virtual power plant as much as possible. Therefore, on the basis of encouraging the cooperation and interaction of multiple virtual power plants, how to ensure the independence and the information privacy of decision-making main bodies of the virtual power plants has important significance.
Other references of interest include:
document 9: liu N, he L, yu X, et al, multi-part energy management for grid-connected microorganisms with a heat and electric coupled controlled response [ J ]. IEEE Transactions on Industrial information, 2018,14 (5): 1887-1897.
Document 10: s. Boyd, N.Parikh, E.Chu, B.Peleot, and J.Eckstein.distributed optimization and statistical Learning of the adapting direction methods of multipliers [ J ]. Foundations and Trends in Machine Learning,2011,3 (1): 1-122.
Document 11: wang Cheng, liu Nian. Interconnection micro-grid system distributed optimization scheduling based on the alternating direction multiplier method [ J ] power grid technology,2016,40 (09): 2675-2681.
Document 12: wano, ai Qian, wu Junhong, and the like, a micro-grid group double-layer distributed scheduling method [ J ] based on an alternating direction multiplier method, a power grid technology,2018,42 (06): 1718-1727.
The prior art has the following defects:
1. the existing research schemes mostly focus on the situation that a single virtual power plant is traded with an external power market, but the research on the competition or cooperation relationship of multiple virtual power plants in a diversified competition environment is insufficient.
2. Most of the virtual power plants in the current multi-virtual power plant research scheme are in competition non-cooperative relationship (under the condition of considering adversary strategy, the virtual power plants are directly traded with an external market), and the consideration of trading and cooperation among different virtual power plants is relatively insufficient.
3. In the current research on the multi-virtual power plant cooperative cooperation, it is generally assumed that all cooperative virtual power plants are controlled by the same regulation and control center, and the decision independence and the information privacy of the virtual power plants cannot be guaranteed.
4. At present, research on multiple virtual power plants is about single electric energy scheduling transaction, and the thermoelectric coordination scheduling of the virtual power plants under the background of comprehensive energy sources is not considered sufficiently.
Therefore, those skilled in the art are dedicated to develop a new multi-virtual power plant collaborative optimization operation scheme to solve the problems existing in the prior art.
Disclosure of Invention
In view of the above-mentioned drawbacks of the prior art, the technical problems to be solved by the present invention are:
1. the coordination optimization problem of multiple virtual power plants under the background of the comprehensive energy system is established, and based on the flexible aggregation characteristic of the virtual power plants, the traditional pure power generation type distributed power supply aggregation is expanded to distributed energy aggregation under the background of comprehensive energy;
2. the source-load difference complementation among different virtual power plants is considered, so that the influence of uncertainty in the operation of the virtual power plants can be effectively reduced, and the operation benefit of the virtual power plants can be improved, and in the scheme, the interaction relationship among multiple virtual power plants is a cooperative relationship;
3. in order to ensure decision independence and information privacy in the multi-virtual power plant cooperation and interaction process, a Nash negotiation mechanism and an alternating direction multiplier method are introduced to promote energy exchange and cooperation transaction among different virtual power plants on the basis of ensuring independent operation of each virtual power plant.
In order to achieve the above object, the present invention provides a collaborative optimization operation scheme for multiple virtual power plants based on nash negotiations, which is a collaborative optimization operation strategy for multiple virtual power plants under an integrated energy context, and guarantees decision independence and information privacy of operation of each virtual power plant on the basis of promoting energy interaction and cooperation transactions among different virtual power plants, wherein the collaborative optimization operation scheme comprises a plurality of virtual power plants, the plurality of virtual power plants form an integrated energy cooperation community, coordination interaction among the plurality of virtual power plants is constructed as a collaborative interaction model based on nash negotiations, and an objective function of the collaborative interaction model is as follows:
in the formula: n is the number of virtual power plants;the cost of the virtual power plant i running independently in non-cooperation mode is the known input parameter, the virtual power plant i calculates independently, and the running transaction cost with other virtual power plants is not includedIn order to simulate the trading cost of the power plant i and the power grid,the electric quantity purchased from the main network and sold to the main network of the virtual power plant i in the period t do not change along with the scene,the electricity purchasing cost and the electricity selling cost are corresponding units;in order to simulate the gas purchase cost of the power plant i,is the price of the gas sold by the natural gas company,the natural gas consumption of the in-i cogeneration unit and the gas boiler of the virtual power plant under the scene s of the t time period is respectively; user utility functionConsisting of two parts, i.e. the electric utility of the userLess the discomfort cost of the userFor the electricity consumption and the heat removal of the i users of the virtual power plant under the scene s of the t periodAmount, k i 、a i Is the corresponding preference coefficient;corresponding to the unit operation cost of the cogeneration unit, the gas boiler, the electricity energy storage and heat energy storage equipment in the sub-area;for the electric quantity purchased and sold by the virtual power plant i from other virtual power plants under the scene s of the time t,for the corresponding community transaction, the electricity price is bought and sold, for the t period, the quantity of heat purchased and sold by the virtual power plant i from other virtual power plants,trading prices for corresponding heat energy;
transaction costs and transaction amounts among the plurality of virtual power plants present a community equilibrium state within the integrated energy collaborative community: i.e. at any timeThen, the community transaction energy of all the buyer virtual power plants is equal to the community transaction energy of all the seller virtual power plants; and the community transaction cost of all the buyer virtual power plants is equal to the community transaction income of all the seller virtual power plants, as shown in formulas (2) to (5):
community transaction electric energyThe community transaction electric energy is positive, which means that a virtual power plant i purchases electric energy from the comprehensive energy cooperation community, and the community transaction electric energy is negative, which means that the virtual power plant i sells electric energy to the comprehensive energy cooperation community; heat energy for community transactionThe community transaction heat energy is positive, which means that the virtual power plant i purchases heat energy from the comprehensive energy cooperation community, and the community transaction heat energy is negative, which means that the virtual power plant i sells heat energy to the comprehensive energy cooperation community; formulae (2) and (3) can be converted to:
community electric energy transaction cost of virtual power plant iCommunity thermal energy trading cost of virtual power plant iFormulae (4) and (5) can be converted to:
the cooperation interaction model is as follows:
further, the virtual power plant maintains decision independence and information privacy.
Further, the solution of the cooperation interaction model adopts an alternative direction multiplier method;
the general form of the hypothetical criteria optimization problem is as follows:
in the formula: x is a local variable, z is a global variable, and the corresponding augmented Lagrangian function is as follows:
in the formula: lambda is Lagrange multiplier, rho is penalty factor;
the iterative process of the alternating direction multiplier method is expressed as follows:
λ [k+1] =λ [k] +ρ(Ax [k+1] +Bz [k+1] -c) (15)
in the iterative process, the local variable x and the global variable z are alternately solved;
introducing a consistency constraint as an auxiliary variable:
decoupling and separating the community interaction variables of the virtual power plants from the formulas (6) to (9);
the cooperation interaction model is further converted into:
(6):(9)
converting the objective function into a minimized form, namely:
(6):(9)
in the formula (21), variablesLocal variable x, variable corresponding to the criteria optimization problem (equation 11)Corresponding to the global variable z in the criteria optimization problem (equation 11);
in the constraint of couplingUnder the condition, a =1,B = -1, c =0 corresponding to Ax + Bz = c in the standard optimization problem (formula 11); the augmented lagrange function for equation (21) is:
in the formula:is the Lagrange multiplier, p 1 、ρ 2 、ρ 3 、ρ 4 The penalty factors are respectively corresponding to the consistency constraints (16) to (19);
based on the principle of the alternative direction multiplier method, equation (22) can be further decomposed into two layers of subproblems: the lower layer corresponds to the self optimization problem of each virtual power plant; the upper layer corresponds to a coordination layer of the comprehensive energy cooperation community and is used for carrying out coordination updating on community transaction variables of each virtual power plant;
the self-optimization sub-problems of each virtual power plant are expressed as follows:
the sub-problems of the coordination layer are specifically as follows:
further, the virtual power plant is equipped with an independent energy management system.
Further, the virtual power plant comprises a controllable unit, an uncontrollable unit, an energy storage and a load; the controllable unit comprises a combined heat and power generation unit (CHP) and a gas boiler, the uncontrollable unit comprises a fan and a photovoltaic, the energy storage comprises electric energy storage and heat energy storage, and the load comprises an electric load and a heat load.
Further, the cooperative operation between the different virtual power plants is realized only by common information transfer.
Further, the electrical loads include critical electrical loads and transferable electrical loads.
Further, the thermal load includes a critical thermal load and a disconnectable thermal load.
Further, in the virtual power plant, the virtual power plant autonomously decides an operation scheme of its own distributed energy unit according to the energy demand of an internal user.
Furthermore, redundant energy can be interacted among different virtual power plants to form cooperative community type transaction, the purchase quantity of the virtual power plants from power companies or natural gas companies independently is reduced, the uncertain influence of renewable energy sources is reduced, and the running cost of the whole comprehensive energy source cooperative community is reduced.
The invention provides a collaborative optimization operation scheme of a multi-virtual power plant based on Nash negotiation, which achieves the following technical effects:
1. on the basis of the cooperative operation of multiple virtual power plants, a multiple virtual power plant cooperative operation model under the background of comprehensive energy is further considered, so that the completeness and the advancement of the model are improved;
2. a Nash negotiation mechanism and an alternative direction multiplier method are introduced, and the decision independence and the information privacy of each virtual power plant are guaranteed on the basis of promoting the cooperation and interaction of different virtual power plants.
The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.
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FIG. 1 is a schematic diagram of an overall framework of a plurality of virtual power plants.
Detailed Description
The technical contents of the preferred embodiments of the present invention will be more clearly and easily understood by referring to the drawings attached to the specification. The present invention may be embodied in many different forms of embodiments and the scope of the invention is not limited to the embodiments set forth herein.
In the drawings, structurally identical elements are represented by like reference numerals, and structurally or functionally similar elements are represented by like reference numerals throughout the several views. The size and thickness of each component shown in the drawings are arbitrarily illustrated, and the present invention is not limited to the size and thickness of each component. The thickness of the components has been exaggerated in some places in the drawings where appropriate for clarity of illustration.
As shown in FIG. 1, a collaborative optimization operation scheme of multiple virtual power plants based on Nash negotiation comprises a plurality of virtual power plants from VPP 1, VPP 2, … to VPP N. And considering the cooperative union of a plurality of virtual power plants as a virtual energy cooperative community. Each virtual power plant is provided with an independent energy management system uEMS, so that scheduling optimization of internal energy conversion facilities of the virtual power plants can be performed, cooperation interaction with other virtual power plants in the community can be performed, and energy purchasing decision with external power companies and natural gas companies can be made. Each virtual power plant comprises a controllable unit (a combined heat and power generation unit CHP and a gas boiler), an uncontrollable unit (a fan and a photovoltaic), energy storage (electric energy storage and thermal energy storage) and a load (an electric load and a thermal load). Considering the response participation of the demand side of the user, the electric loads are divided into important electric loads and transferable electric loads; and the thermal load includes a critical thermal load and a disconnectable thermal load.
Different from a centralized scheduling mode, each virtual power plant in the structure enjoys an autonomous decision making right, and the cooperative operation among different virtual power plants is realized only through public information transmission. In the virtual power plant, a virtual power plant operator autonomously decides an operation scheme of a self distributed energy unit according to the energy demand of an internal user; redundant energy can be interacted among different virtual power plants to form cooperative community type transaction, the purchase quantity of the virtual power plants from an electric power company or a natural gas company is reduced, the uncertain influence of renewable energy sources is reduced, the running cost of the whole comprehensive energy source cooperative community is reduced, and the running cost of the whole virtual comprehensive energy source community is promoted to be the lowest.
In fig. 1, there are information, thermal, electrical and natural gas energy flows. Information flows bidirectionally between each virtual power plant, the electric utility, and the natural gas utility. The heat energy flows flow in each virtual power plant, part of heat energy generated by the combined heat and power generation unit CHP enters the heat energy storage, and the other part of heat energy is combined with the heat energy generated by the gas boiler to flow to the heat load in a one-way mode. The heat energy generated by the gas boiler does not need to be stored thermally. The source of the electric energy has three sources, namely renewable energy, power companies and a combined heat and power generation unit CHP. A part of the electric energy flow generated by the renewable energy source enters the electric energy storage, and a part of the electric energy flow is combined with the electric energy generated by the power company and the combined heat and power generation unit CHP to flow to the electric load in a unidirectional way. Natural gas energy flows from the natural gas company to the cogeneration units CHP and gas boilers of the respective virtual power plants.
Because the virtual power plants need to negotiate the income distribution obtained after cooperation, the bargaining and price reducing relationship under the cooperation game is formed. Assuming independent operating costs of each virtual power plant in non-cooperationAs a negotiation starting point, i.e.Under the cooperation condition, the cooperation operation cost of each virtual power plant is C i Corresponding to an operational utility level of u i =-C i . In the process of cooperation negotiation, each virtual power plant operator wants to maximize benefit increase brought by cooperation as much as possible, so that coordination interaction among multiple virtual power plants is constructed into a cooperation interaction model based on Nash negotiation, and an objective function of the coordination interaction model is constructed as follows:
in the formula: n is the number of virtual power plants;the cost of the virtual power plant i running independently in non-cooperation mode is the known input parameter, the virtual power plant i calculates independently, and the running transaction cost with other virtual power plants is not includedIn order to simulate the trading cost of the power plant i and the power grid,the electric quantity purchased from the main network and sold to the main network of the virtual power plant i in the period t do not change along with the scene,the electricity purchasing cost and the electricity selling cost are corresponding units;in order to simulate the gas purchase cost of the power plant i,is the price of the gas sold by the natural gas company,the natural gas consumption of the in-i cogeneration unit and the gas boiler of the virtual power plant under the scene s of the t time period is respectively; user utility functionConsisting of two parts, i.e. the electric utility of the userLess the discomfort cost of the userFor the power consumption and the heat rejection k of the i users of the virtual power plant under the scene s of the t time period i 、a i Is the corresponding preference coefficient;corresponding to the unit operation cost of the cogeneration unit, the gas boiler, the electricity energy storage and heat energy storage equipment in the sub-area;for the electric quantity purchased and sold by the virtual power plant i from other virtual power plants under the scene s of the t period,buying and selling electricity price for corresponding community transaction, for the t period, the quantity of heat purchased and sold by the virtual power plant i from other virtual power plants,the price is traded for the corresponding heat energy.
It should be noted that the non-cooperative running cost in the objective function (1)The known input parameters are obtained by independent calculation of each virtual power plant operator, and the operation transaction cost with other virtual power plants is not includedUnder the cooperative interaction, the operation cost of each virtual power plant comprises the operation transaction cost with other virtual power plants, and the operation transaction cost can influence the internal operation plan of each virtual power plant. Since there is no third party to earn a profitIndividual, trading costs and trading volume between virtual power plants present a community equilibrium state within the integrated energy collaborative community: i.e. at any timeThen, the community transaction energy of all the buyer virtual power plants is equal to the community transaction energy of all the seller virtual power plants; and the community transaction cost of all the buyer virtual power plants is equal to the community transaction income of all the seller virtual power plants, and the specific formulas are shown in the formulas (2) to (5):
in order to simplify variables, the electric energy purchase amount of each virtual power plant in the community under the same scene at the same timeAnd selling electricity to the communityInto a common variable-community trading power, i.e.The community trading electric energy is positive, which means that the virtual power plant i purchases electric energy from the comprehensive energy cooperation community, and the community trading electric energy is negative, which means that the virtual power plant i sells electric energy to the comprehensive energy cooperation community; society of societyDistrict trading heat energyThe fact that the community transaction heat energy is positive means that the virtual power plant i purchases heat energy from the comprehensive energy cooperation community, and the fact that the community transaction heat energy is negative means that the virtual power plant i sells heat energy to the comprehensive energy cooperation community; further, formulae (2) and (3) may be further converted into:
correspondingly, the corresponding electric energy transaction cost of each virtual power plant and other virtual power plants in the transaction interaction process isThis equation is reasonable because the community trading process is equivalent to a virtual clearing market, and the energy purchase price faced by a virtual power plant is generally equal to the energy sale price at that moment. Correspondingly, the heat energy trading cost of each virtual power plant in the community isThus, formulae (4) and (5) can be further converted into:
therefore, the multi-virtual power plant cooperation interaction model based on Nash negotiation is as follows:
considering decision independence and information privacy of each virtual power plant, the scheme is designed to solve the joint interaction problem of the multiple virtual power plants by using a distributed optimization method, and autonomous decisions of each virtual power plant in the cooperation interaction process are guaranteed. And decomposing the collaborative optimization model (10) of the multi-virtual power plant by using an alternating direction multiplier method.
The general form of the hypothetical criteria optimization problem is as follows:
in the formula: x is a local variable, z is a global variable, and the corresponding augmented Lagrangian function is as follows:
in the formula: lambda is Lagrange multiplier, rho is penalty factor;
the iterative process of the alternating direction multiplier method is expressed as follows:
λ [k+1] =λ [k] +ρ(Ax [k+1] +Bz [k+1] -c) (15)
in the iteration process, a local variable x and a global variable z are alternately solved;
the joint interaction model of multiple virtual power plants based on Nash negotiation comprises a plurality of constraint conditions, and it is noted that a single virtual internal constraint can be separated into each virtual power plant, and the expressions (6) to (9) couple community transaction variables of different virtual power plants together.
Introducing a consistency constraint as an auxiliary variable:
decoupling and separating community interaction variables of each virtual power plant from the formulas (6) to (9);
thus, the model (10) can be further converted into:
(6):(9)
the objective function is converted to a minimized form, namely:
(6):(9)
in the formula (21), variablesLocal variable x, variable corresponding to the criteria optimization problem (equation 11)Global variable z in the corresponding criteria optimization problem (equation 11);
in the constraint of couplingUnder the condition, A =1,B = -1, c =0 corresponding to Ax + Bz = c in the standard optimization problem (formula 11); the augmented lagrange function for equation (21) is:
in the formula:is the Lagrange multiplier, p 1 、ρ 2 、ρ 3 、ρ 4 The penalty factors are respectively corresponding to consistency constraints (16) to (19);
based on the principle of the alternating direction multiplier algorithm, the model (22) can be further decomposed into two layers of subproblems: the lower layer corresponds to the self optimization problem of each virtual power plant operator; and the upper layer corresponds to the collaborative updating of the community trading variables of each virtual power plant by the community coordination layer. The upper layer can be regarded as a virtual coordination problem, except that the virtual coordinator does not control any energy facility inside the virtual power plant, and the optimal convergence of the cooperative interaction of the virtual power plants is realized only by updating and transmitting the common variables of the virtual power plants.
The self-optimization sub-problems of each virtual power plant are expressed as follows:
the sub-problems of the coordination layer are specifically as follows:
the foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (9)
1. The utility model provides a many virtual power plants collaborative optimization operation scheme based on Nash negotiation which characterized in that, includes a plurality of virtual power plants, a plurality of virtual power plants constitute a comprehensive energy cooperation community, the cooperation interaction between a plurality of virtual power plants is constructed for the cooperation interactive model based on Nash negotiation, the objective function of cooperation interactive model is:
in the formula: n is the number of virtual power plants;the cost of the virtual power plant i running independently in non-cooperation mode is the known input parameter, the virtual power plant i calculates independently, and the running transaction cost with other virtual power plants is not includedIn order to simulate the trading cost of the power plant i and the power grid,the electric quantity purchased from the main network and sold to the main network of the virtual power plant i in the period t are not changed along with the scene,the electricity purchasing cost and the electricity selling cost are corresponding units;in order to simulate the gas purchase cost of the power plant i,is the price of the gas sold by the natural gas company,the natural gas consumption of the in-i cogeneration unit and the gas boiler of the virtual power plant under the scene s of the t time period is respectively; user utility functionConsisting of two parts, i.e. the electric utility of the userLess discomfort cost to the userFor the electricity consumption and the heat abandonment k of the i users of the virtual power plant under the scene s of the t period i 、a i Is the corresponding preference coefficient;corresponding to the unit operation cost of the cogeneration unit, the gas boiler, the electricity energy storage and heat energy storage equipment in the sub-area;for the electric quantity purchased and sold by the virtual power plant i from other virtual power plants under the scene s of the t period,for the corresponding community transaction, the electricity price is bought and sold, for the t period, the quantity of heat purchased and sold by the virtual power plant i from other virtual power plants,trading prices for corresponding heat energy;
transaction costs and transaction amounts among the plurality of virtual power plants present a community equilibrium state within the integrated energy collaborative community: i.e. at any timeThen, the community transaction energy of all the buyer virtual power plants is equal to the community transaction energy of all the seller virtual power plants; and the community transaction cost of all the buyer virtual power plants is equal to the community transaction income of all the seller virtual power plants, as shown in formulas (2) to (5):
community transaction electric energyThe community transaction electric energy is positive representation virtual electricityThe plant i purchases electric energy from the comprehensive energy cooperation community, and if the community trading electric energy is negative, the virtual plant i sells the electric energy to the comprehensive energy cooperation community; heat energy for community transactionThe community transaction heat energy is positive, which means that the virtual power plant i purchases heat energy from the comprehensive energy cooperation community, and the community transaction heat energy is negative, which means that the virtual power plant i sells heat energy to the comprehensive energy cooperation community; formulae (2) and (3) can be converted to:
community electric energy transaction cost of virtual power plant iCommunity thermal energy trading cost of virtual power plant iFormulae (4) and (5) can be converted to:
the cooperation interaction model is as follows:
(6):(9)
solving the cooperative interaction model by adopting an alternative direction multiplier method;
the general form of the hypothetical criteria optimization problem is as follows:
in the formula: x is a local variable, z is a global variable, and the corresponding augmented Lagrangian function is as follows:
in the formula: lambda is Lagrange multiplier, rho is penalty factor;
the iterative process of the alternating direction multiplier method is expressed as follows:
λ [k+1] =λ [k] +ρ(Ax [k+1] +Bz [k+1] -c) (15)
in the iterative process, the local variable x and the global variable z are alternately solved;
introducing a consistency constraint as an auxiliary variable:
and (3) the community interaction variables of the virtual power plants are represented by an equation (6): (9) decoupling;
the cooperation interaction model is further converted into:
(6):(9)
converting the objective function into a minimized form, namely:
(6):(9)
in the formula (21), variablesLocal variable x, variable corresponding to the criteria optimization problem (equation 11)Corresponding to the global variable z in the criteria optimization problem (equation 11);
in the coupling constraintUnder the condition, a =1,B = -1, c =0 corresponding to Ax + Bz = c in the standard optimization problem (formula 11); the augmented lagrange function for equation (21) is:
in the formula:is Lagrange multiplier, p 1 、ρ 2 、ρ 3 、ρ 4 The penalty factors are respectively corresponding to the consistency constraints (16) to (19);
based on the principle of the alternating direction multiplier method, equation (22) can be further decomposed into two sub-problems: the lower layer corresponds to the self optimization problem of each virtual power plant; the upper layer corresponds to a coordination layer of the comprehensive energy cooperation community and is used for carrying out coordination updating on community transaction variables of each virtual power plant;
the self-optimization sub-problems of each virtual power plant are expressed as follows:
subject to: each virtual power plant constraint
The sub-problems of the coordination layer are specifically as follows:
2. the nash-negotiation based multi-virtual power plant collaborative optimization operation scheme of claim 1, wherein the virtual power plant maintains decision independence and information privacy.
3. The nash-negotiation-based multi-virtual power plant collaborative optimization operation scheme of claim 1, wherein the virtual power plant is provided with an independent energy management system.
4. The nash-negotiation-based multi-virtual power plant collaborative optimization operation scheme of claim 1, wherein the virtual power plant comprises controllable units, uncontrollable units, energy storage, loads; the controllable unit comprises a combined heat and power generation unit (CHP) and a gas boiler, the uncontrollable unit comprises a fan and a photovoltaic, the energy storage comprises electric energy storage and heat energy storage, and the load comprises an electric load and a heat load.
5. The nash-negotiation-based multi-virtual power plant collaborative optimization operation scheme of claim 4, wherein collaborative operation between the different virtual power plants is achieved only through common information transfer.
6. The nash-negotiation-based multi-virtual power plant collaborative optimization operation scheme of claim 4, wherein the electrical loads comprise significant electrical loads and transferable electrical loads.
7. The nash-negotiation based multi-virtual power plant cooperative optimization operation scheme of claim 4, wherein the thermal loads comprise critical thermal loads and interruptible thermal loads.
8. The nash negotiation-based multi-virtual power plant collaborative optimization operation scheme of claim 1, wherein inside the virtual power plant, the virtual power plant autonomously decides an operation scheme of its own distributed energy plant group according to internal user energy demand.
9. The nash-negotiation-based multi-virtual power plant collaborative optimization operation scheme of claim 1, wherein redundant energy can be interacted among different virtual power plants to form cooperative community type transactions, so that the purchase amount of the virtual power plants from power companies or natural gas companies independently is reduced, the uncertain influence of renewable energy sources is reduced, and the operation cost of the whole comprehensive energy source cooperative community is reduced.
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CN112001752A (en) * | 2020-08-18 | 2020-11-27 | 四川大学 | Multi-virtual power plant dynamic game transaction behavior analysis method based on limited rationality |
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CN112232603B (en) * | 2020-12-08 | 2021-03-16 | 华东交通大学 | Virtual power plant optimal scheduling method considering electricity-to-gas coordination |
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CN115207917A (en) * | 2022-08-17 | 2022-10-18 | 国网山东省电力公司青岛供电公司 | Layered-distributed multi-target tracking method and system for virtual power plant |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103903066A (en) * | 2014-04-04 | 2014-07-02 | 东南大学 | Virtual power plant stratified random optimized dispatching method |
CN107292456A (en) * | 2017-08-01 | 2017-10-24 | 重庆大学 | Electrical energy flow point cloth collaboration optimized calculation method based on alternating direction multiplier method |
CN107370802A (en) * | 2017-07-10 | 2017-11-21 | 中国人民解放军国防科学技术大学 | A kind of collaboration storage dispatching method based on alternating direction multiplier method |
CN107507078A (en) * | 2017-07-12 | 2017-12-22 | 天津大学 | A kind of distributed energy distribution of income strategy based on bargaining game |
CN107506851A (en) * | 2017-07-26 | 2017-12-22 | 河海大学 | A kind of multizone virtual plant comprehensive energy coordinated scheduling Optimized model |
CN107767033A (en) * | 2017-09-28 | 2018-03-06 | 上海交通大学 | The probabilistic virtual plant of one kind consideration is bidded and distribution of interests method and system |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7599866B2 (en) * | 2003-10-24 | 2009-10-06 | Southern California Edison Company | Simultaneous optimal auctions using augmented lagrangian and surrogate optimization |
US10103550B2 (en) * | 2016-01-19 | 2018-10-16 | Fujitsu Limited | Aggregated and optimized virtual power plant control |
-
2018
- 2018-10-23 CN CN201811235364.2A patent/CN110135613B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103903066A (en) * | 2014-04-04 | 2014-07-02 | 东南大学 | Virtual power plant stratified random optimized dispatching method |
CN107370802A (en) * | 2017-07-10 | 2017-11-21 | 中国人民解放军国防科学技术大学 | A kind of collaboration storage dispatching method based on alternating direction multiplier method |
CN107507078A (en) * | 2017-07-12 | 2017-12-22 | 天津大学 | A kind of distributed energy distribution of income strategy based on bargaining game |
CN107506851A (en) * | 2017-07-26 | 2017-12-22 | 河海大学 | A kind of multizone virtual plant comprehensive energy coordinated scheduling Optimized model |
CN107292456A (en) * | 2017-08-01 | 2017-10-24 | 重庆大学 | Electrical energy flow point cloth collaboration optimized calculation method based on alternating direction multiplier method |
CN107767033A (en) * | 2017-09-28 | 2018-03-06 | 上海交通大学 | The probabilistic virtual plant of one kind consideration is bidded and distribution of interests method and system |
Non-Patent Citations (4)
Title |
---|
基于主从博弈的含电动汽车虚拟电厂协调调度;张高等;《电力***自动化》;20171124(第11期);都48-55页 * |
基于主从博弈的虚拟电厂双层竞标策略;方燕琼等;《电力***自动化》;20170725(第14期);第61-69页 * |
基于交替方向乘子法的微电网群双层分布式调度方法;王皓等;《电网技术》;20180630;第1718-1725页 * |
多时间尺度的多虚拟电厂双层协调机制与运行策略;刘思源等;《中国电机工程学报》;20180205(第03期);第753-761页 * |
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