Multi-virtual power plant carbon sharing optimization method

Abstract

The invention relates to the technical field of micro-grids, and discloses a multi-virtual power plant carbon sharing optimization method. The method comprises the following steps: establishing a single virtual power plant optimization model, and considering carbon sharing between virtual power plants (VPP); establishing a multi-virtual power plant asymmetric Nash bargaining model based on the carbon sharing contribution degree: quantifying bargaining capability of each virtual power plant based on the carbon sharing contribution degree, and establishing a multi-virtual power plant (MVPP) asymmetric Nash bargaining model based on the carbon sharing contribution degree; and solving the MVPP asymmetric Nash bargaining model, and decomposing into two steps of solving: solving the cooperative alliance cost minimization model to obtain the carbon quota shared by the VPP, and solving the MVPP asymmetric Nash bargaining model to obtain the shared carbon price of the VPP. Compared with the prior art, the MVPP carbon sharing optimization method is established, and the carbon sharing strategy of the VPP is solved by adopting the asymmetric Nash bargaining game based on the carbon sharing contribution degree, so that the carbon cost of each VPP is reduced, the economic benefit of each VPP is improved, the benefit distributed by the VPP with the high carbon sharing contribution degree is larger, and the fairness of benefit distribution is ensured.

Description

Technical Field

[0001] The present application relates to the field of microgrid technology, and in particular to a carbon sharing optimization method for multiple virtual power plants. Background Art

[0002] This section is intended to provide a background or context for the embodiments of the present application as stated in the claims. The contents in this section are for reference only and do not constitute an admission or confirmation that they are prior art that has been disclosed.

[0003] At present, the emission reduction plan of the power system is mainly aimed at the power supply side, such as increasing the consumption rate of renewable energy, and power generation companies trading carbon quotas in the carbon market to promote the carbon reduction transformation of coal-fired power. The output of renewable energy fluctuates greatly, the load demand continues to grow, and the demand for deep peak regulation of thermal power increases, so that the power supply side is still unable to significantly reduce carbon emissions for the time being. In this context, exploring emission reduction strategies for users on the distribution network side and tapping the carbon emission reduction potential of producers and consumers on the distribution network side are powerful means to further reduce carbon emissions in the power system.

[0004] Some existing markets and systems have attempted to regulate carbon emissions from downstream consumer companies, but they are mainly aimed at large industrial and commercial users that meet the carbon market access threshold. There is still a lack of feasible carbon emission management rules for the massive number of small-volume users. The peer-to-peer (P2P) carbon sharing model of virtual power plants considers carbon trading, promotes clean power generation units to increase production capacity or encourages clean energy consumption, and can achieve carbon emission reduction while bringing benefits to producers and consumers.

[0005] However, there is little research in existing literature on carbon sharing among virtual power plants (VPPs). Since carbon sharing among VPPs can reduce the amount of carbon quotas purchased by VPPs and the parent carbon market, reduce the carbon trading costs of VPPs, and improve the economic benefits of VPPs, the carbon sharing strategy among VPPs needs to be studied in depth. Summary of the invention

[0006] The purpose of this application is to provide a carbon sharing optimization method for multiple virtual power plants, which can reduce the carbon cost of each virtual power plant, improve the economic benefits of each virtual power plant, and ensure the fairness of profit distribution.

[0007] The present application discloses a multi-virtual power plant carbon sharing optimization method, comprising:

[0008] Establish a single virtual power plant optimization model, taking into account carbon sharing among virtual power plants;

[0009] Establishing an asymmetric Nash bargaining model of multiple virtual power plants based on carbon sharing contribution, including: quantifying the bargaining power of each virtual power plant based on the carbon sharing contribution, and establishing an asymmetric Nash bargaining model of the multiple virtual power plants based on the carbon sharing contribution;

[0010] Solving the asymmetric Nash bargaining model of multiple virtual power plants includes: solving the cooperative alliance cost minimization model to obtain the carbon quota shared by the virtual power plants, and solving the asymmetric Nash bargaining model of multiple virtual power plants to obtain the shared carbon price of the virtual power plants.

[0011] In a preferred example, the model of the single virtual power plant considering carbon sharing between virtual power plants is:

[0012]

[0013] Among them, C i The total cost of carbon sharing for the i-th virtual power plant is: and represents the carbon cost, electricity transaction cost, combined heat and power operation cost, gas purchase cost, energy storage operation cost and demand response cost of the i-th virtual power plant in period t, G i (·) represents the equality constraint of the i-th virtual power plant, H i (·) represents the inequality constraint of the i-th virtual power plant.

[0014] In a preferred example, the calculation method for quantifying the bargaining power of each virtual power plant based on the carbon sharing contribution is:

[0015]

[0016] Among them, α i is the bargaining power of the i-th virtual power plant, δ sell is the indicator of the party selling carbon quotas, δ buy It is an indicator for buyers of carbon quotas. is the sum of the daily shared carbon quotas of the i-th virtual power plant, N sellers N is a collection of virtual power plants that sell carbon quotas. buyers A collection of virtual power plants for purchasing carbon allowances.

[0017] In a preferred example, the asymmetric Nash bargaining model of multiple virtual power plants based on the carbon sharing contribution is established as follows:

[0018]

[0019] in, is the total cost of the i-th virtual power plant without considering carbon sharing, and They are respectively the price at which the ith virtual power plant purchases carbon quotas from the upper carbon market and the price at which it sells carbon quotas in period t. The price at which the i-th virtual power plant sells carbon quotas to the j-th virtual power plant in period t.

[0020] In a preferred example, solving the asymmetric Nash bargaining model of multiple virtual power plants includes:

[0021] S31. Solve the cooperative alliance cost minimization model to obtain the carbon quota amount shared by the virtual power plant:

[0022]

[0023] Among them, Zi is an intermediate variable,

[0024] In MATLAB, CPLEX is called to solve the formula in S31 to obtain the carbon quota E shared by the virtual power plant when the cost of the multi-virtual power plant cooperative alliance is minimized. ij，t * , and Z i * and α i ;

[0025] S32. Solving the asymmetric Nash bargaining model of multiple virtual power plants according to the bargaining power to obtain the shared carbon price of the virtual power plant:

[0026] E ij，t * , Z i * and α i As a known quantity, it is substituted into formula (3). The objective function of formula (3) is a strictly monotonically increasing convex function. Taking the logarithm of the objective function, the optimization model is obtained.

[0027]

[0028] The shared carbon price of the virtual power plant is To optimize the variables, call MOSEK to solve.

[0029] The present invention has at least the following advantages:

[0030] By considering the carbon sharing mechanism among virtual power plants (VPPs), the carbon emission cost of each power plant is reduced and the overall economic benefits are improved. The asymmetric Nash bargaining game is used to solve the carbon trading strategy, and the bargaining power of each VPP is quantified according to its carbon sharing contribution, so that power plants with high contribution can obtain more benefits, achieving fairness and rationality in benefit distribution.

[0031] Furthermore, by optimizing various costs including electricity trading, cogeneration, natural gas purchase, energy storage operation and demand response, efficient utilization and allocation of resources are achieved. By decomposing and solving the cost minimization model and Nash bargaining model, the computational complexity is reduced and the solution efficiency is improved.

[0032] Each technical feature disclosed in the above invention content, each technical feature disclosed in each implementation mode and example below, and each technical feature disclosed in the accompanying drawings can be freely combined with each other to form various new technical solutions (these technical solutions should be deemed to have been recorded in this specification), unless such combination of technical features is technically infeasible. For example, in one example, feature A+B+C is disclosed, and in another example, feature A+B+D+E is disclosed, and features C and D are equivalent technical means that play the same role. Technically, only one of them can be used, and it is impossible to use them at the same time. Feature E can be combined with feature C technically. Then, the solution of A+B+C+D should not be deemed to have been recorded because it is technically infeasible, while the solution of A+B+C+E should be deemed to have been recorded. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a schematic diagram of a system framework according to an implementation of the present application;

[0034] Figure 2 is a flow chart of a multi-virtual power plant carbon sharing optimization method according to an embodiment of the present application;

[0035] Figure 3 It is a new energy prediction curve of each virtual power plant according to a multi-virtual power plant carbon sharing optimization method in accordance with an embodiment of the present application;

[0036] Figure 4 It is an electric load forecast curve of each virtual power plant according to a multi-virtual power plant carbon sharing optimization method in accordance with an embodiment of the present application;

[0037] Figure 5 is a heat load prediction curve of each virtual power plant according to a multi-virtual power plant carbon sharing optimization method according to an embodiment of the present application;

[0038] Figure 6 is a relationship diagram between price and time of an upper power grid and an upper carbon market in a multi-virtual power plant carbon sharing optimization method according to an embodiment of the present application;

[0039] Figure 7 is a situation of carbon quota sharing among virtual power plants according to an implementation mode of the present application;

[0040] Figure 8 is a shared carbon price for a virtual power plant according to one embodiment of the present application;

[0041] Figure 9a-9c The carbon cost comparison of VPP1-VPP3 in different modes according to one embodiment of the present application is shown in sequence;

[0042] Fig.10 This is a comparison of the benefits of various virtual power plants according to an implementation of the present application. DETAILED DESCRIPTION

[0043] In the following description, many technical details are provided to help readers better understand the present application. However, those skilled in the art can understand that the technical solution claimed in the present application can be implemented even without these technical details and various changes and modifications based on the following embodiments.

[0044] In order to make the objectives, technical solutions and advantages of the present application more clear, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0045] Figure 1 The carbon trading and sharing relationship between multiple virtual power plants (MVPPs) and the upper-level carbon market is shown. Multiple virtual power plants buy and sell carbon quotas with the upper-level carbon market, and virtual power plants also collaborate through the carbon sharing mechanism. Each virtual power plant includes multiple energy types such as wind power, photovoltaics, energy storage, electricity and industrial users. Through the carbon sharing mechanism, each virtual power plant can achieve flexible configuration and complementarity in carbon quota resources, thereby effectively reducing the overall carbon emission cost and improving economic benefits.

[0046] The first embodiment of the present application relates to a multi-virtual power plant carbon sharing optimization method, the process of which is as follows: Figure 2 As shown, the method comprises the following steps:

[0047] In S1, individual virtual power plant optimization models are established in turn considering carbon sharing among virtual power plants.

[0048] In S2, the bargaining power of each virtual power plant is quantified based on the carbon sharing contribution.

[0049] In S3, an asymmetric Nash bargaining model of multiple virtual power plants based on carbon sharing contribution is established.

[0050] In S4, the cooperative alliance cost minimization model is solved to obtain the carbon quota amount shared by the virtual power plant.

[0051] In S5, the asymmetric Nash bargaining model of multiple virtual power plants is solved to obtain the shared carbon price of virtual power plants.

[0052] In an optional embodiment, in S1, a single virtual power plant optimization model is established, including an objective function and constraints, as follows:

[0053] 1. Objective Function

[0054] The aggregated units of a virtual power plant include wind turbines, photovoltaics, combined heat and power (CHP) units with carbon capture systems (CCS) and power to gas (P2G) devices or conventional CHP units, gas boilers (GB), energy storage systems (ESS) and loads. The optimization model of a single VPP aims to minimize its own total cost, and the objective function is as follows:

[0055]

[0056] Among them, C i Considering the total cost of carbon sharing for the i-th virtual power plant VPP(i), and They represent the carbon cost, electricity trading cost, cogeneration operation cost, gas purchase cost, energy storage operation cost and demand response cost of the i-th virtual power plant in period t respectively.

[0057] The specific calculation formulas for each cost are as follows:

[0058] 【1】Carbon cost of the i-th virtual power plant in period t

[0059]

[0060] in, is the carbon cost of the ith virtual power plant in period t with the upper carbon market, is the carbon sharing cost of the ith virtual power plant in period t.

[0061]

[0062] in, are the amount of carbon quotas purchased and sold by the i-th virtual power plant to the upper carbon market in period t, are the prices at which the ith virtual power plant purchases and sells carbon quotas from the superior carbon market in period t.

[0063]

[0064] in, is the price at which the i-th virtual power plant sells carbon quotas to the j-th virtual power plant in period t, E ij,t is the amount of carbon quota sold by the i-th virtual power plant to the j-th virtual power plant in period t.

[0065] 【2】Electricity transaction cost of the i-th virtual power plant in period t

[0066]

[0067] in, are the prices at which the ith virtual power plant buys and sells electricity to the upper market in period t, are the amount of electricity purchased and sold by the ith virtual power plant to the upstream market during period t.

[0068] 【3】The cogeneration operation cost of the i-th virtual power plant in period t

[0069]

[0070] in, represents the power generated by CHP in period t, They represent the electric energy consumed by CCS and P2G equipment in CHP during period t, a and b are the operating cost coefficients of CHP units, a2 and a3 are the operating cost coefficients of CCS and CHP equipment respectively, and c is the operating cost constant.

[0071] 【4】Gas purchase cost of the i-th virtual power plant in period t

[0072]

[0073] Among them, λ gas is the purchase price of natural gas, They represent the amount of natural gas consumed by CHP and GB in period t respectively; It represents the amount of natural gas produced by P2G in period t.

[0074] 【5】Energy storage operation cost of the i-th virtual power plant in period t

[0075]

[0076] in, They represent the charging and discharging power of ESS in period t respectively; ζ is the degradation cost of unit energy of charging and discharging.

[0077] 【6】Demand response cost of the i-th virtual power plant in period t

[0078]

[0079] in, They represent the electrical load that can be reduced, the electrical load that can be shifted, and the thermal load that can be reduced of the i-th virtual power plant in period t, respectively. cut , tran denote the compensation unit price for load transfer and load reduction, respectively,cut,h Indicates the compensation unit price for heat load reduction.

[0080] 2. Constraints

[0081] 【1】Carbon emission constraints

[0082] The initial carbon quota of the i-th virtual power plant is a pre-allocated value, calculated as follows:

[0083]

[0084] Among them, D E,CHP , D H,CHP They represent the carbon quota per unit of electricity and heat supplied by CHP respectively; They represent the power generation and heating power of CHP in the i-th virtual power plant in period t respectively; D GB , Represent the unit carbon quota and heating power in GB respectively.

[0085] The actual carbon emissions within the i-th virtual power plant are as follows:

[0086]

[0087] in, represents the carbon dioxide emission coefficient of CHP and GB; h1 is the constant coefficient of CHP; is the amount of CO2 captured by CCS in the i-th virtual power plant during period t, see formula (20).

[0088] 【2】CHP

[0089] Fuel consumption of CHP in the i-th virtual power plant during period t and power generation The relationship is as follows:

[0090]

[0091] Among them, η CHP is the power generation efficiency of the unit, is the calorific value of natural gas.

[0092] The conventional CHP unit electrical and thermal coupling constraints are as follows:

[0093]

[0094] in, They are the upper and lower limits of CHP power generation respectively; It is the thermal power when the CHP unit generates the minimum power; represents the power supplied by CHP to the load during period t; h1, h2, h mare all constant coefficients of CHP.

[0095] The electric-thermal coupling constraints of the CHP unit with CCS and P2G are as follows:

[0096]

[0097] Other constraints for CHP units with CCS and P2G are as follows:

[0098]

[0099] in, They represent the power supplied by CHP to CCS and P2G in period t respectively; CCS , γ P2G , γ P2G，p are the correlation coefficients of CCS and P2G, respectively; represents the amount of natural gas produced by P2G in period t; are the upper and lower limits of the power required by CCS respectively; They are the upper and lower limits of the power required by P2G respectively.

[0100] 【3】GB

[0101] Fuel consumption of GB in the i-th virtual power plant during period t With heating capacity The relationship is as follows:

[0102]

[0103] Among them, η GB It is the heating efficiency of gas boiler.

[0104] 【4】New energy

[0105]

[0106] in, It is the maximum output of the new energy unit.

[0107] 【5】ESS

[0108]

[0109] in, are the maximum charging and discharging power of ESS respectively; is the charging state of ESS; is the charge state of ESS; η ch , η dis Respectively represent the charge and discharge coefficient of ESS; Soc i，t represents the capacity of ESS in period t; Respectively represent the minimum and maximum capacity of ESS; Soc i,t＝0 is the initial charge state of ESS.

[0110] 【6】Load

[0111] The power load of the i-th virtual power plant and heat load as follows:

[0112]

[0113] in, They represent the power of fixed electrical load and fixed thermal load in period t respectively. The constraints of shiftable and curtailable power are as follows:

[0114]

[0115] Among them, a tran is the transferable electrical power and a cut，h To reduce the thermal power threshold coefficient, Indicates the maximum value of the electric power that can be reduced.

[0116] 【7】Balance Constraint

[0117] The balancing constraints of the i-th virtual power plant include power, carbon emissions, and thermal energy constraints as follows:

[0118]

[0119]

[0120]

[0121] In an optional embodiment, an MVPP asymmetric Nash bargaining model based on carbon sharing contribution is constructed. The specific steps are as follows:

[0122] 1. Bargaining power modeling based on carbon sharing contribution.

[0123] The carbon sharing contribution meets the following characteristics: 1) When a VPP shares carbon quotas with other VPPs, both the sale and purchase of carbon quotas can be regarded as contributions, and the more carbon quotas sold or purchased, the greater the contribution and the higher the bargaining power; 2) Since the price of purchasing carbon quotas from the superior carbon market is usually higher than the price of selling carbon quotas, the carbon sharing contribution of VPPs that sell carbon quotas is greater than that of VPPs that purchase the same carbon quotas. Based on the above characteristics, according to the sum of VPPs' daily shared carbon quotas, VPPs are divided into buyers and sellers, and the bargaining power is quantified based on the total amount of shared carbon quotas and the identity indicators of purchasing / selling carbon quotas, as described below:

[0124] First, calculate the total VPP daily shared carbon quota:

[0125]

[0126] in, is the sum of daily shared carbon quotas of the i-th virtual power plant.

[0127] Then, based on the daily shared carbon quota The virtual power plant is divided into buyers and sellers, and the identity indicator v i To distinguish:

[0128]

[0129] Among them, v sell The indicator for the party selling carbon quotas; buy It is an indicator for the party that purchases carbon quotas. Since VPPs that sell carbon quotas contribute more than VPPs that purchase the same carbon quotas, and in order to meet the

[0130] (31) Normalization of valence capacity requires, δ sell and δ buy The following equation must be satisfied:

[0131]

[0132] Finally, we quantify the bargaining power of sellers and buyers respectively:

[0133]

[0134] Among them, α i is the bargaining power of the ith virtual power plant, N sellers N is a collection of virtual power plants that sell carbon quotas. buyers A collection of virtual power plants for purchasing carbon allowances.

[0135] 2. Establishment of MVPP asymmetric Nash bargaining model

[0136] In the asymmetric Nash bargaining model, each participant obtains the Pareto optimal benefit according to his bargaining power, and its objective function is to maximize the Nash product:

[0137]

[0138] in, is the total cost of VPP(i) without considering carbon sharing.

[0139] Since the bargaining of each VPP is rational, in order for the bargaining to proceed normally, the model must also meet the following two conditions: (1) A single VPP aims to minimize its own cost, and multiple VPPs aim to maximize the Nash product. In order to avoid conflicts between objective functions and enable the VPPs to jointly reach a transaction agreement, it is necessary to ensure that the total cost of the i-th virtual power plant when carbon sharing is not considered. Not less than the total cost C when carbon sharing is considered i , as shown in formula (34); (2) The shared carbon price of VPP must be within the acceptable range of both parties, as shown in formula (35).

[0140]

[0141] In summary, the MVPP asymmetric Nash bargaining model is as follows:

[0142]

[0143] 3. The steps for solving the MVPP asymmetric Nash bargaining model are as follows:

[0144] Since there is This continuous variable multiplies, and the bargaining power α i With E ij,t Therefore, the asymmetric Nash bargaining model (36) is difficult to solve directly. It can be proved that the solution of the asymmetric Nash bargaining model (36) can minimize the cost of the MVPP cooperative alliance model. Therefore, the solution of the MVPP asymmetric Nash bargaining model can be divided into two steps: Step 1 first solves the cooperative alliance cost minimization model to obtain the carbon quota shared by VPP, and then solves the MVPP asymmetric Nash bargaining model through step 2 to obtain the shared carbon price of VPP.

[0145] The steps for decomposing and solving formula (36) are as follows:

[0146] Step 1: Solve the cooperative alliance cost minimization model to obtain the carbon quota shared by the VPP.

[0147] Since the carbon sharing cost of VPP in the cooperative alliance cost minimization model They will cancel out when summed, so the cooperative alliance cost minimization model can be transformed as follows:

[0148]

[0149] Where: Z i is an intermediate variable.

[0150] In MATLAB, CPLEX can be called to solve equation (37) and obtain the carbon quota amount E shared by VPP when the cooperative alliance cost is minimized. ij,t * , and Zi * and α i In formula (37), since the shared carbon price of VPP is offset, it is necessary to solve the shared carbon price of VPP through step 2.

[0151] Step 2: Solve the MVPP asymmetric Nash bargaining model based on bargaining power to obtain the shared carbon price of VPP.

[0152] The E obtained in step 1 ij,t * , Z i * and α i Substitute it into formula (36) as a known quantity. The objective function of formula (36) is a strictly monotonically increasing convex function, so the logarithm of the objective function can be taken to obtain the optimization model of step 2 as shown in formula (38). The carbon price of VPP in formula (38) is To optimize the variables, (38) can be solved by calling MOSEK.

[0153]

[0154] In order to better understand the technical solution of the present application, a specific example is provided below for illustration. The details listed in the example are mainly for ease of understanding and are not intended to limit the scope of protection of the present application.

[0155] This embodiment uses three virtual power plants VPP. The first virtual power plant VPP1 includes wind turbines, energy storage, loads, GB and conventional CHP units. The second virtual power plant VPP2 includes photovoltaic, energy storage, loads, GB and CHP units including CCS and P2G. The third virtual power plant VPP3 includes photovoltaic, energy storage, loads, GB and conventional CHP units. The model parameters in VPP are shown in Table 1. The new energy output, fixed electrical load and fixed thermal load in each VPP are shown in Table 1. Figure 3-Figure 5 The electricity price with the upper grid and the carbon price with the upper carbon market are shown in Figure 6 shown.

[0156] Table 1

[0157]

[0158]

[0159] The specific application process of the method of the present invention in this embodiment is as follows:

[0160] To verify the effectiveness of the method of the present invention, a model that does not consider carbon sharing between VPPs is compared with the model of the present invention that considers carbon sharing between VPPs. In addition, to prove the fairness of the income distribution of each VPP in the present invention, the symmetric Nash bargaining game is used as a comparison method, which is divided into the following three modes:

[0161] Mode 1 (M1): Carbon sharing among VPPs is not considered, and each VPP operates independently;

[0162] Model 2 (M2): Considering carbon sharing among VPPs, the symmetric Nash bargaining game is used to solve the carbon quota trading strategy among VPPs;

[0163] Mode 3 (M3): Considering carbon sharing among VPPs, an asymmetric Nash bargaining game based on carbon sharing contribution is used to solve the carbon quota sharing strategy among VPPs;

[0164] The simulation results of M1-M3 are shown in Table 2 and Figure 7-Figure 10 As shown, the optimization effect of the present invention is analyzed from three aspects: cost, carbon quota sharing, and fairness of income distribution.

[0165] (1) Cost analysis. As can be seen from Table 2, the total cost and carbon cost of each VPP in M2 and M3, which consider carbon sharing among VPPs, are always less than that in M1, which does not consider carbon sharing among VPPs. It can be seen that after considering carbon sharing among VPPs, the economic efficiency of each VPP is improved.

[0166] Table 2

[0167]

[0168]

[0169] (2) Analysis of carbon quota sharing. Figure 7 The carbon quota sharing between VPPs in M3. Figure 8 is the shared carbon price of VPP in M3, Figure 9a Comparison of carbon costs between VPP1 and the parent carbon market under M1 and M3. Figure 9b Comparison of carbon costs between VPP2 and the parent carbon market under M1 and M3. Fig.9c Comparison of carbon costs between VPP3 and the parent carbon market under M1 and M3. Figure 7 It can be seen that VPP2 sells carbon quotas to VPP1 and VPP3. This is because VPP2 has CCS equipment and can sell carbon quotas. Figure 8 It can be seen that the shared carbon price between VPPs is higher than the price of selling carbon quotas to the superior carbon market, and lower than the price of purchasing carbon quotas from the superior carbon market. This shows the rationality of using asymmetric Nash bargaining game to determine the shared carbon price between VPPs. Figure 9a-9cIt can be seen that the carbon cost of each VPP and the parent carbon market in M3 is less than that in M1. After considering the carbon sharing among VPPs, the carbon quota of each VPP trading in the parent carbon market is reduced.

[0170] (3) Analysis of the fairness of income distribution. Table 3 shows the bargaining power of each VPP in M2 and M3. Fig.10 is the income of each VPP in M2 and M3, where the income is the difference between the total cost of considering carbon sharing between VPPs and the total cost of not considering carbon sharing between VPPs. Fig.10 It can be seen that VPP1 and VPP2 in M2 have the same bargaining power and the same benefits. Although VPP3 has the same bargaining power as VPP1 and VPP2, its benefits are different from those of VPP1 and VPP2. This is because the shared carbon price between VPPs must meet the constraints of being lower than the price of purchasing carbon quotas from the superior carbon market and higher than the price of selling carbon quotas to the superior carbon market. Compared with M2, VPP2 in M3, as the seller of carbon quotas between VPPs, has a greater contribution to carbon sharing, increased bargaining power, and increased allocated benefits, which meets the fairness requirements of carbon sharing between VPPs.

[0171] Table 3

[0172]

[0173] Accordingly, the embodiments of the present application also provide a computer-readable storage medium, in which computer executable instructions are stored, and when the computer executable instructions are executed by the processor, the various method embodiments of the present application are implemented. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be a computer-readable instruction, a data structure, a module of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable storage media does not include temporary computer-readable media (transitory media), such as modulated data signals and carriers.

[0174] In addition, an embodiment of the present application further provides a computer program product, which includes computer executable instructions, and when the computer executable instructions are executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0175] It should be noted that, in the present application, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of more restrictions, the elements defined by the sentence "include one" do not exclude the existence of other identical elements in the process, method, article or equipment including the elements. In the present application, if it is mentioned that a certain action is performed according to a certain element, it means at least the meaning of performing the action according to the element, which includes two situations: performing the action only according to the element and performing the action according to the element and other elements. Multiple, multiple, multiple, etc. expressions include 2, 2 times, 2 kinds and more than 2, more than 2 times, more than 2 kinds.

[0176] The serial numbers used in describing the steps of the method do not themselves constitute any limitation on the order of these steps. For example, the step with a larger serial number does not necessarily have to be executed after the step with a smaller serial number. The step with a larger serial number may be executed first and then the step with a smaller serial number. They may also be executed in parallel, as long as this execution order is reasonable for those skilled in the art. For another example, multiple steps with consecutive serial numbers (e.g., step 101, step 102, step 103, etc.) do not limit other steps that can be executed in between. For example, there may be other steps between step 101 and step 102.

[0177] This specification includes combinations of the various embodiments described herein. Individual references to embodiments (e.g., "one embodiment" or "some embodiments" or "preferred embodiments"); however, these embodiments are not mutually exclusive unless indicated as mutually exclusive or it is clear to a person skilled in the art that they are mutually exclusive. It should be noted that the word "or" is used in this specification in a non-exclusive sense unless the context clearly indicates or requires otherwise.

[0178] All documents mentioned in this specification are considered to be included in the disclosure of this application as a whole, so that they can be used as a basis for modification when necessary. In addition, it should be understood that the above is only a preferred embodiment of this specification and is not intended to limit the scope of protection of this specification. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of one or more embodiments of this specification should be included in the scope of protection of one or more embodiments of this specification.

[0179] In some cases, the actions or steps described in the claims may be performed in a different order than in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A multi-virtual power plant carbon sharing optimization method, characterized in that: include: Establish a single virtual power plant optimization model, taking into account carbon sharing among virtual power plants; Establishing an asymmetric Nash bargaining model of multiple virtual power plants based on carbon sharing contribution, including: quantifying the bargaining power of each virtual power plant based on the carbon sharing contribution; and establishing an asymmetric Nash bargaining model of multiple virtual power plants based on the carbon sharing contribution; Solving the asymmetric Nash bargaining model of multiple virtual power plants, including: solving the cooperative alliance cost minimization model to obtain the carbon quota shared by the virtual power plants; and solving the asymmetric Nash bargaining model of multiple virtual power plants to obtain the shared carbon price of the virtual power plants.

2. The multi-virtual power plant carbon sharing optimization method according to claim 1, characterized in that: The model of the single virtual power plant considering carbon sharing among virtual power plants is: Among them, C i The total cost of carbon sharing for the i-th virtual power plant is: and represents the carbon cost, electricity transaction cost, combined heat and power operation cost, gas purchase cost, energy storage operation cost and demand response cost of the i-th virtual power plant in period t, G i (·) represents the equality constraint of the i-th virtual power plant, H i (·) represents the inequality constraint of the i-th virtual power plant.

3. The multi-virtual power plant carbon sharing optimization method according to claim 1, characterized in that: The calculation method for quantifying the bargaining power of each virtual power plant based on the carbon sharing contribution is: Among them, α i is the bargaining power of the i-th virtual power plant, δ Sell is the indicator of the party selling carbon quotas, δ buy It is an indicator for buyers of carbon quotas. is the sum of the daily shared carbon quotas of the i-th virtual power plant, N sellers N is a collection of virtual power plants that sell carbon quotas. buyers A collection of virtual power plants for purchasing carbon allowances.

4. The multi-virtual power plant carbon sharing optimization method according to claim 1, characterized in that: The asymmetric Nash bargaining model of multiple virtual power plants based on the carbon sharing contribution is established as follows: in, is the total cost of the i-th virtual power plant without considering carbon sharing, and They are respectively the price at which the ith virtual power plant purchases carbon quotas from the upper carbon market and the price at which it sells carbon quotas in period t. The price at which the i-th virtual power plant sells carbon quotas to the j-th virtual power plant in period t.

5. The multi-virtual power plant carbon sharing optimization method according to claim 4, characterized in that: The method of solving the asymmetric Nash bargaining model of multiple virtual power plants includes: Solving the cooperative alliance cost minimization model obtains the carbon quota shared by the virtual power plant: Among them, Z i is the intermediate variable, In MATLAB, CPLEX is called to solve equation (4) to obtain the carbon quota E shared by the virtual power plants when the cost of the multi-virtual power plant cooperation alliance is minimized. ij,t * , and Z i * and α i ; The asymmetric Nash bargaining model of multiple virtual power plants is solved according to the bargaining power to obtain the shared carbon price of the virtual power plant: E ij,t * , Z i * and α i As a known quantity, it is substituted into formula (3). The objective function of formula (3) is a strictly monotonically increasing convex function. Taking the logarithm of the objective function, the optimization model is obtained. The shared carbon price of the virtual power plant is To optimize the variables, call MOSEK to solve.

6. The multi-virtual power plant carbon sharing optimization method according to claim 2, characterized in that: The carbon cost of the i-th virtual power plant in period t is calculated as follows: in, is the carbon cost of the ith virtual power plant in period t with the upper carbon market, is the carbon sharing cost of the i-th virtual power plant in period t; in, are the amount of carbon quotas purchased and sold by the i-th virtual power plant from the upper carbon market in period t, are the prices at which the i-th virtual power plant purchases and sells carbon quotas from the upper carbon market in period t, respectively; in, is the price at which the i-th virtual power plant sells carbon quotas to the j-th virtual power plant in period t, E ij,t The amount of carbon quota sold by the i-th virtual power plant to the j-th virtual power plant in period t.

7. The multi-virtual power plant carbon sharing optimization method according to claim 2, characterized in that: The calculation method of the electricity transaction cost of the i-th virtual power plant in period t is as follows: in, are the prices at which the i-th virtual power plant buys and sells electricity from the upper market in period t, are the amount of electricity purchased and sold by the i-th virtual power plant to the upstream market in period t.

8. The multi-virtual power plant carbon sharing optimization method according to claim 2, characterized in that: The calculation method of the cogeneration operation cost of the i-th virtual power plant in period t is as follows: in, represents the power generation of the cogeneration unit in period t, They represent the electric energy consumed by the carbon capture system and the power-to-gas equipment in the cogeneration unit during period t, a and b are the operating cost coefficients of the cogeneration unit, a2 and a3 are the operating cost coefficients of the carbon capture system and the power-to-gas equipment, respectively, and c is the operating cost constant.

9. The multi-virtual power plant carbon sharing optimization method according to claim 2, characterized in that: The calculation method of the gas purchase cost of the i-th virtual power plant in period t is as follows: Among them, λ gas is the purchase price of natural gas, They represent the amount of natural gas consumed by the cogeneration unit and the gas boiler in period t respectively; It represents the amount of natural gas produced by the power-to-gas equipment during period t.

10. The multi-virtual power plant carbon sharing optimization method according to claim 2, characterized in that: The calculation method of the energy storage operation cost of the i-th virtual power plant in period t is as follows: in, They represent the charging and discharging power of the energy storage system in period t respectively; ζ is the degradation cost of unit energy of charging and discharging.

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