Cost allocation method and system for community-shared energy storage

Abstract

A cost allocation method and system for community-shared energy storage. The method comprises: acquiring a charging power of prosumers, a discharging power of prosumers, and a shared power of community-shared energy storage (S11); constructing a shared contribution quantification algorithm on the basis of the charging power of prosumers, the discharging power of prosumers, and the shared power of community-shared energy storage (S12); on the basis of the shared contribution quantification algorithm, quantifying the shared contribution degrees of different prosumers to an alliance (S13); and on the basis of the shared contribution degrees, constructing a cost allocation algorithm based on a generalized Nash bargaining theory, and determining allocation costs for different prosumers on the basis of the cost allocation algorithm (S14).

Description

Cost allocation method and system for community shared energy storage

[0001] The present application claims priority to the Chinese patent application No. 202410453361.5, filed on April 16, 2024, to the Chinese Patent Office, the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the technical field of community shared energy storage, for example, to a cost allocation method and system for community shared energy storage. BACKGROUND

[0003] Due to the natural uncertainty of distributed energy, the value of distributed renewable energy cannot be fully utilized. Energy storage is considered an effective way to solve these problems. With the emergence of more and more small-scale producers and consumers, economies of scale will inevitably lead to large-scale cooperation of small-scale producers and consumers to configure community shared energy storage.

[0004] With the development of technology, community groups are gradually formed in a small range. The life of the community group is concentrated in the community. At this time, the community is the life carrier of the community group and there is a cost of energy storage. At this time, the cost of energy storage is superimposed by the individual cost of each person in the community. However, the allocation of the cost of energy storage by each person in the community is not ideal. The cost is divided by using a single contribution level, which leads to an unreasonable allocation of the cost of community shared energy storage. SUMMARY

[0005] The present application provides a cost allocation method and system for community shared energy storage, which is compatible with the shared contribution level of different producers and consumers to the alliance and quantifies the shared contribution level of different producers and consumers to the alliance, so as to determine the allocation cost of different producers and consumers according to the cost allocation algorithm, ensuring the reasonable allocation of the cost of different producers and consumers, realizing the reasonable allocation of the cost of community shared energy storage, and avoiding the cost division by using a single contribution level.

[0006] The present application provides a cost allocation method for community shared energy storage, which is applied to a community shared energy storage scenario. The cost allocation method for community shared energy storage comprises the following steps.

[0007] Obtaining the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage;

[0008] Constructing a shared contribution quantification algorithm based on the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage;

[0009] Quantifying the shared contribution level of different producers and consumers to the alliance according to the shared contribution quantification algorithm;

[0010] A cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the degree of each shared contribution, and the allocation costs of different prosumers are determined according to the cost allocation algorithm.

[0011] Optionally, obtaining the prosumer charging power, the prosumer discharging power, and the community shared energy storage shared power includes:

[0012] Collect the charging and discharging status of all prosumers at each moment, and determine whether there are complementary charging and discharging demands among all prosumers at each moment.

[0013] Optionally, obtaining the prosumer charging power, the prosumer discharging power, and the community shared energy storage shared power further includes:

[0014] If there is no charging and discharging complementary behavior between prosumers at time τ, then the shared power of all prosumers at that time is 0, that is,

[0015] If there is complementary behavior between prosumers at time τ, calculate the overall charging power and overall discharging power of all prosumers at time τ;

[0016] If the overall charging power at time τ is greater than the overall discharging power, the total amount of shared power is equal to the overall discharging power, that is,

[0017] Optionally, the shared contribution quantification algorithm is constructed based on the prosumer charging power, the prosumer discharging power, and the community shared energy storage shared power, including:

[0018] Fixed-frame prosumer charging power, prosumer discharging power, and community shared energy storage sharing power;

[0019] The charging power of prosumers, the discharging power of prosumers, and the shared power of community shared energy storage are trained with the algorithm learning model, and a shared contribution quantification algorithm is constructed.

[0020] Optionally, the algorithm for constructing a shared contribution quantification based on the prosumer charging power, the prosumer discharging power, and the community shared energy storage shared power further includes:

[0021] Specific calculation of shared power among prosumers:

[0022] Where, represents the power shared by prosumer u at time τ on the nth typical operation scenario day in year y; and are the charging and discharging powers of prosumer u at time τ, respectively; Shared energy storage and power for the community, and The charging and discharging power of the community shared energy storage at τ time is respectively.

[0023] Optionally, the sharing contribution quantification algorithm comprises:

[0024] The sharing contribution quantification algorithm is fixed.

[0025] The sharing contribution quantification algorithm is associated with the different producers and consumers.

[0026] The sharing contribution quantification algorithm quantifies the sharing contribution of the different producers and consumers to the alliance.

[0027] Optionally, the sharing contribution quantification algorithm quantifies the sharing contribution of the different producers and consumers to the alliance, and further comprises:

[0028] The sharing contribution of each producer and consumer can be represented as:

[0029] In the formula, χ u is the sharing contribution of the producer and consumer u, and the value range is [0, 1]; w y,n is the probability of the typical operation day n appearing in the yth year; N y is the total number of years contained in the planning period; N d is the number of typical scenarios; N t is the number of time periods.

[0030] Optionally, the cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the sharing contribution, and the allocation cost of the different producers and consumers is determined according to the cost allocation algorithm, and the cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the sharing contribution, and the allocation cost of the different producers and consumers is determined according to the cost allocation algorithm.

[0031] The sharing contribution is fixed.

[0032] The cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the sharing contribution.

[0033] The allocation cost of the different producers and consumers is determined according to the cost allocation algorithm.

[0034] Optionally, the cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the sharing contribution, and the allocation cost of the different producers and consumers is determined according to the cost allocation algorithm, and the cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the sharing contribution, and the allocation cost of the different producers and consumers is determined according to the cost allocation algorithm.

[0035] The cost allocation algorithm based on the generalized Nash bargaining theory is as follows:

[0036] In the formula, represents the total cost of the producer and consumer u independently configuring the energy storage, which is the negotiation breaking point; χ u is the sharing contribution of the producer and consumer u.

[0037] Optionally, the cost distribution system of community shared energy storage is applied to the cost distribution method of community shared energy storage, and the cost distribution system of community shared energy storage comprises:

[0038] The acquisition module is configured to acquire the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage.

[0039] The algorithm module is configured to construct a shared contribution quantification algorithm based on the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage.

[0040] The quantification module is configured to quantify the shared contribution degree of different producers and consumers to the alliance according to the shared contribution quantification algorithm.

[0041] The cost distribution module is configured to construct a cost distribution algorithm based on the generalized Nash bargaining theory based on the shared contribution degrees, and determine the distribution cost of different producers and consumers according to the cost distribution algorithm.

[0042] In the embodiments of the present application, the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage are acquired, the shared contribution quantification algorithm is constructed based on the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage, the shared contribution degree of different producers and consumers to the alliance is quantified according to the shared contribution quantification algorithm, the cost distribution algorithm based on the generalized Nash bargaining theory is constructed based on the shared contribution degrees, and the distribution cost of different producers and consumers is determined according to the cost distribution algorithm. At this time, the shared contribution degrees of different producers and consumers to the alliance are compatible, and the shared contribution degrees of different producers and consumers to the alliance are quantified, so as to determine the distribution cost of different producers and consumers according to the cost distribution algorithm, to ensure the reasonable distribution of the cost of different producers and consumers, to realize the reasonable distribution of the cost of community shared energy storage, and to avoid the cost division by using a single contribution degree. BRIEF DESCRIPTION OF DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technical solutions, the following will briefly introduce the drawings needed to be used in the embodiments or related technical solution descriptions. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0044] FIG. 1 is a flow diagram of the cost distribution method of community shared energy storage in the embodiments of the present application;

[0045] FIG. 2 is a flow diagram of S12 in the cost distribution method of community shared energy storage in the embodiments of the present application;

[0046] FIG. 3 is a flowchart of S13 in the cost allocation method of community shared energy storage according to an embodiment of the present application;

[0047] FIG. 4 is a flowchart of S14 in the cost allocation method of community shared energy storage according to an embodiment of the present application;

[0048] FIG. 5 is a schematic diagram of the CSES scheduling strategy of each type of producer and consumer in the cost allocation method of community shared energy storage according to an embodiment of the present application;

[0049] FIG. 6 is a schematic diagram of the structure of the cost allocation system of community shared energy storage according to an embodiment of the present application;

[0050] FIG. 7 is a hardware diagram of an electronic device according to an example embodiment. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of the present application.

[0052] EMBODIMENT

[0053] Referring to FIGS. 1 to 7, a cost allocation method of community shared energy storage is applied to a magnetic induction sensor. The cost allocation method of community shared energy storage comprises the following steps.

[0054] S11: Obtain the charging power of a producer and consumer, the discharging power of the producer and consumer, and the shared power of community shared energy storage.

[0055] S12: Construct a shared contribution quantification algorithm based on the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of community shared energy storage.

[0056] S13: Quantify the shared contribution degree of different producers and consumers to the alliance according to the shared contribution quantification algorithm.

[0057] S14: Construct a cost allocation algorithm based on the generalized Nash bargaining theory based on the shared contribution degrees, and determine the allocation cost of different producers and consumers according to the cost allocation algorithm.

[0058] In the embodiment of the present application, the producer-consumer charging power, the producer-consumer discharging power and the community shared energy storage sharing power are obtained by the method in the embodiment of the present application; the shared contribution quantification algorithm is constructed based on the producer-consumer charging power, the producer-consumer discharging power and the community shared energy storage sharing power; the shared contribution degree of different producer-consumers to the alliance is quantified according to the shared contribution quantification algorithm; the cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the shared contribution degrees, and the allocation cost of different producer-consumers is determined according to the cost allocation algorithm. At this time, the shared contribution degrees of different producer-consumers to the alliance are compatible and quantified, so as to determine the allocation cost of different producer-consumers according to the cost allocation algorithm, ensure the reasonable allocation of the cost of different producer-consumers, realize the reasonable allocation of the cost of community shared energy storage, and avoid using a single contribution degree to divide the cost.

[0059] In step S11, the producer-consumer charging power, the producer-consumer discharging power and the community shared energy storage sharing power are obtained;

[0060] In the embodiment of the present application, the charging and discharging states of all producer-consumers at each time are collected, and it is judged whether there is complementary charging and discharging demand between all producer-consumers at each time. At this time, the charging and discharging states of all producer-consumers at each time are controlled, so as to utilize the charging and discharging states of all producer-consumers at each time to judge whether there is complementary charging and discharging demand between all producer-consumers at each time, realize the confirmation of the complementary charging and discharging demand of all producer-consumers, and realize the interaction between producer-consumers.

[0061] Further, the charging and discharging demand of the producer-consumer in the community cooperation alliance has complementarity, and the community shared energy storage is configured for cooperation to obtain considerable benefits. When there is complementary charging and discharging demand, the producer-consumer contributes to the maximization of collective welfare whether charging the shared energy storage system or accepting the discharging of the shared energy storage system. Therefore, a producer-consumer shared contribution quantification method is constructed. First, the charging and discharging states of all producer-consumers at each time are determined. Then, it is judged whether there is complementary charging and discharging demand between all producer-consumers at each time.

[0062] At this time, if there is no complementary charging and discharging behavior between producer-consumers at time τ, the shared power of all producer-consumers at this time is 0, that is,

[0063] If there is complementary behavior between producer-consumers at time τ, the overall charging power and the overall discharging power of all producer-consumers at time τ are calculated;

[0064] If the overall charging power at time τ is greater than the overall discharging power, the total amount of shared power is equal to the overall discharging power, that is,

[0065] In step S12, a sharing contribution quantification algorithm is constructed based on the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power.

[0066] In the implementation of the present application, the specific steps can be:

[0067] S121: Determine the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power.

[0068] S122: Train the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power with an algorithm learning model, and construct a sharing contribution quantification algorithm.

[0069] In the embodiment of the present application, the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power are determined. At this time, the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power are introduced in order to control the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power, so as to construct a sharing contribution quantification algorithm based on the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power, and further process the sharing contribution quantification algorithm in order to quantify the sharing contribution degree and reasonably allocate the subsequent energy storage cost. Specifically, the producer-consumer charging power, the producer-consumer discharging power and the community shared energy sharing power are trained with an algorithm learning model, and a sharing contribution quantification algorithm is constructed.

[0070] Further, the sharing power of the producer-consumer is specifically calculated as follows:

[0071] In the formula, represents the sharing power of the producer-consumer u at time τ on the nth typical operation scenario day of the yth year; and are the charging and discharging power of the producer-consumer u at time τ, respectively; is the community shared energy sharing power, and are the charging and discharging power of the community shared energy at time τ, respectively.

[0072] In step S13, the sharing contribution degree of different producer-consumers to the alliance is quantified according to the sharing contribution quantification algorithm.

[0073] In the implementation of the present application, the specific steps can be:

[0074] S131: Determine the sharing contribution quantification algorithm;

[0075] S132: Associate the sharing contribution quantification algorithm with different producer-consumers;

[0076] S133: quantifying the sharing contribution degree of different producers and consumers to the alliance based on the sharing contribution quantification algorithm.

[0077] In the embodiment of the present application, the sharing contribution quantification algorithm is defined, and the sharing contribution quantification algorithm is controlled, so as to associate the sharing contribution quantification algorithm with different producers and consumers, so as to implement the sharing contribution degree of each producer and consumer, and then quantifying the sharing contribution degree of different producers and consumers to the alliance based on the sharing contribution quantification algorithm.

[0078] Further, the sharing contribution degree of each producer and consumer can be expressed as:

[0079] In the formula, χ u is the sharing contribution degree of the producer and consumer u, and the value range is [0, 1]; w y,n is the probability of the typical operation day n in the yth year; N y is the total number of years contained in the planning period; N d is the number of typical scenarios; N t is the number of time periods.

[0080] S14: constructing a cost allocation algorithm based on the generalized Nash bargaining theory based on the sharing contribution degree of each producer and consumer, and determining the allocation cost of different producers and consumers according to the cost allocation algorithm;

[0081] In the specific implementation process of the present application, the specific steps can be:

[0082] S141: defining the sharing contribution degree of each producer and consumer;

[0083] S142: constructing a cost allocation algorithm based on the generalized Nash bargaining theory based on the sharing contribution degree of each producer and consumer;

[0084] S143: determining the allocation cost of different producers and consumers according to the cost allocation algorithm;

[0085] In the embodiment of the present application, the sharing contribution degree of each producer and consumer is controlled, so as to determine the sharing contribution degree of each producer and consumer to the alliance, and then constructing a cost allocation algorithm based on the generalized Nash bargaining theory based on the sharing contribution degree of each producer and consumer, realizing the control of the cost allocation algorithm based on the generalized Nash bargaining theory, and determining the allocation cost of different producers and consumers according to the cost allocation algorithm, at this time, the sharing contribution degree of different producers and consumers to the alliance is compatible, and the sharing contribution degree of different producers and consumers to the alliance is quantified, so as to determine the allocation cost of different producers and consumers according to the cost allocation algorithm, ensuring the reasonable allocation of the cost of community shared energy storage, avoiding the use of single contribution degree for cost division.

[0086] Specifically, in the community shared energy storage optimization configuration, there is a constraint between the community producer and consumer cost and the community total cost as follows:

[0087] wherein formula (31) represents the total cost C of the CSES in the planning period CSES , including investment cost C INV and operation and maintenance cost In formula (32), C u represents the total electricity cost of the producer and consumer u in the planning period, is the daily electricity purchase cost of the producer and consumer u, is the daily electricity sale income of the producer and consumer u; in formula (33), indicates that the total cost of the CSES is jointly shared by each producer and consumer; in formula (34), is the total cost of the producer and consumer u in the planning period; formula (35) indicates that the community total cost C CES is jointly shared by each producer and consumer. The quantitative model of each cost will be described in detail in the planning sub-problem.

[0088] The premise for the producer and consumer to join the community cooperative investment is to further reduce their own cost, otherwise they will refuse to participate in the co-construction and sharing. Therefore, the cooperative planning model (P: CPP) based on generalized Nash bargaining can be represented as P: cooperative planning model (CPP), at this time, the cost allocation algorithm based on generalized Nash bargaining theory is as follows:

[0089] wherein, represents the total cost of the producer and consumer u to configure energy storage alone, and χ u is the shared contribution degree of the producer and consumer u. The cost allocation algorithm based on generalized Nash bargaining greatly reduces the computational complexity and is better used in engineering practice. In addition, this model can not only be used to solve the ex ante cost allocation problem, but also can be conveniently used for ex post cost allocation after obtaining actual operation data.

[0090] The product and exponential problem of the decision variable in the CPP belongs to a non-convex non-linear optimization problem, which is difficult to solve directly. Related research proves that the generalized Nash bargaining model can be transformed into a community welfare maximization sub-problem and a revenue allocation sub-problem, that is, by solving the planning operation problem (POP) and then solving the cost allocation problem (CAP) to solve the CPP, as follows:

[0091] (1) Planning operation problem (POP)

[0092] The planning operation of the community shared energy storage (CSES) is represented by a double-layer stochastic optimization problem, which includes an upper-layer community shared energy storage optimization investment model and a lower-layer community shared energy storage optimization operation model, as follows:

[0093] 1) Upper-level community shared energy storage optimization investment model

[0094] The objective function of the upper-level CSES investment model is to minimize the total cost of the community in the planning period under the construction sequence i , which can be expressed as:

[0095] In the formula, and are the total operating income and total investment cost of the community in the planning period under the construction sequence i, respectively. Among them, is the optimization objective of the lower-level CSES optimization operation model, which will be described in detail in the lower-level model. and are the total construction cost and equipment residual value of CSES under the construction sequence i, respectively. and are the decision variable sets of the upper-level model and the lower-level model, respectively.

[0096] The total construction cost of community shared energy storage equipment can be expressed as:

[0097] In the formula, Nc is the number of energy storage construction in the planning period; cces is the unit capacity construction cost of community shared energy storage; is the newly constructed capacity of community shared energy storage in the cth phase under the investment construction sequence i; y i,c is the starting year of the cth phase under the investment construction sequence i; r d and r i are the discount rate and inflation rate, respectively.

[0098] The residual value of community shared energy storage equipment can be expressed as:

[0099] In the formula, γ is the net residual value rate of community shared energy storage equipment; T i is the total number of years of operation of the cth phase of the energy storage equipment from construction to the end of the planning period; T dev is the life cycle of energy storage.

[0100] The constraint conditions of the upper-level CSES optimization investment model include the energy storage equipment construction capacity constraint and the energy storage energy multiplication factor constraint:

[0101] In the formula, is the upper limit of the CSES construction capacity; θ is the energy multiplication factor of community shared energy storage; For the construction of power. It should be noted that the decision variable of the upper optimization model is the set of community shared energy storage capacity configuration schemes

[0102] 2) Lower community shared energy optimization operation model

[0103] The objective function of the lower CSES operation model based on the stochastic programming method is to minimize the total operation and maintenance cost of community producers and consumers As shown in the following formula:

[0104] In the formula, represents the daily maintenance cost of scenario nCSES in year y; and represents the daily electricity purchase cost and daily electricity sales revenue of scenario n community producers and consumers in year y, respectively.

[0105] The daily electricity purchase cost of all producers and consumers Can be expressed as:

[0106] In the formula, is the electricity purchase price of period t; is the electricity purchase power of producer and consumer u in scenario n in year y period τ.

[0107] The daily electricity sales revenue of all producers and consumers Can be expressed as:

[0108] In the formula, is the electricity sales price of period t; is the electricity sales power of producer and consumer u in scenario n period τ.

[0109] The maintenance cost of CSES Can be expressed as:

[0110] In the formula, c mt represents the daily unit power maintenance cost of energy storage; is the rated power of CSES in year y.

[0111] All constraint conditions of the lower CSES optimization operation model are the constraint conditions of the n typical day operation scenario in year y of construction time sequence i. For the sake of simplicity, the subscripts i, y, n are omitted.

[0112] a. Power balance constraint

[0113] In the formula, is the load of producer and consumer u at time τ; Photovoltaic output of prosumer u at time τ; Discharge power of energy storage called by prosumer u at time τ; Charge power of energy storage called by prosumer u at time τ.

[0114] b. Charge / discharge direction / state constraints

[0115] where, and respectively represent the auxiliary binary variables of prosumer u using CSES for charging and discharging. The above constraints restrict the unidirectionality of prosumer using energy storage for charging and discharging.

[0116] c. Energy storage power constraints

[0117] d. Energy storage state of charge constraints

[0118] where, and respectively represent the minimum and maximum state of charge allowed by CSES; represents the remaining energy of CSES at time τ.

[0119] e. Energy storage state of charge continuity constraints

[0120] The remaining energy of CSES at time τ is determined by the remaining energy at time τ-1 and the energy change in period τ, which can be expressed as:

[0121] where, and are the remaining energy stored by CSES at time τ and τ-1, respectively; represents the energy change of CSES in period τ; α is the self-discharge rate of CSES; η ch and η dis are the charging efficiency and discharging efficiency of CSES, respectively.

[0122] f. Energy storage initial / final state consistency constraints

[0123] where, and respectively represent the remaining energy at the beginning and end of the scheduling period.

[0124] g. Photovoltaic actual output constraints

[0125] where, is the predicted value of photovoltaic output of prosumer u at time τ.

[0126] h. Equivalent load constraint

[0127] To prevent the aggravation of peak-valley difference, the equivalent load of the grid side after load scheduling should be less than a certain limit:

[0128] wherein, is the equivalent load of the grid side of producer-consumer u; is the maximum value of the typical daily load of producer-consumer u; and ξ is the equivalent load coefficient.

[0129] To verify the effectiveness and accuracy of the proposed community shared energy storage cost allocation algorithm based on shared contribution quantification algorithm and generalized Nash bargaining theory (hereinafter referred to as GNB), a photovoltaic community containing 800 producer-consumers is taken as an example. It is assumed that the independent installation capacity of each producer-consumer is 9 kW, and the load data of the producer-consumers is generated from the historical data of the intelligent electric meter of a single transformer area in Zhejiang Province, China. The collection time of the load data is 365 days, and the collection frequency is 15 minutes. The typical daily load curve of the producer-consumers can be clustered into four types: evening peak type (EP-U), flat peak type (NP-U), peak avoidance type (PA-U), and double peak type (DP-U).

[0130] Firstly, the rationality of the allocation strategy based on GNB is analyzed. Table 1 lists the comparison between independent energy storage operation (IES) and traditional Nash bargaining model (TNB).

[0131] Table 1 Comparison of community shared energy storage cost allocation strategies based on GNB and TNB

[0132] In Table 1, the independent operation cost of each producer-consumer under IES is the negotiation breakdown point. When the allocation cost after cooperation is higher than the negotiation breakdown point, cooperation cannot be achieved. It can be seen that the cost of each producer-consumer under GNB and TNB is lower than that under IES, and the cost reduction value of each producer-consumer under TNB is 57×10 4 4 Yuan. Obviously, when the contributions of the producer-consumers are different, this method is unfair. By comparing the results of TNB and GNB, it can be found that under the GNB scheme, the cost of EP-U is reduced by 16×10 4 4 Yuan, the cost of NP-U is reduced by 9×10 4 4 Yuan, and the costs of PA-U and DP-U are increased by 7×10 4 4 Yuan and 18×10 4 4 Yuan, respectively. The reason for this phenomenon is that the proposed GNB introduces the contribution degree to distinguish the bargaining power of the producer-consumers, and the obtained contribution degree matrix is χ u=[0.31890.29010.22000.1710]. The contribution rate evaluation results show that EP-U and NP-U have larger complementary energy contribution values, and therefore have higher contribution than PA-U and DP-U, showing stronger bargaining power. Referring to Figure 1, it can be more intuitively seen that DP-U has the lowest complementary charge and discharge power during the daily scheduling cycle, and therefore has the lowest contribution. However, due to its participation in the CSES cooperative configuration and operation, the net benefit still increased by 39×10 compared to the scenario of independently configuring energy storage. 4 Yuan.

[0133] To further verify the superiority of the proposed method, GNB is compared with other methods, including the Shapley value method (SVM), the minimum cost remaining savings (MCRS), and the nucleolus method (NM). Considering the significant differences in emphasis between GNB and other methods, only the overall benefit and computational time are compared and analyzed, as shown in Table 2.

[0134] Table 2 Comparison of cost sharing strategies under different cooperative game methods

[0135] In the comparison, the objective functions and constraints of the four models are the same to ensure fairness. It can be seen that the overall profit of the cooperative alliance under GNB is higher than that of SVN, MCRS, and NB. This is because GNB distributes profits according to the maximization of the interests of the cooperative alliance, while MCRS and SVM distribute profits by measuring the comprehensive marginal benefits of each participant; NM distributes profits by making the net profits of all cooperative sub-alliances as equal as possible. In addition, it can be seen that the solution time of GNB is shortened by 89.1%, 78.6% and 89.3% compared with SVM, MCRS and NM, respectively. To further explore the impact of member size on solution time, the computational costs of various methods at different scales (N=4, 8, 12, 16, 20) are compared, as shown in Table 3:

[0136] Table 3 Comparison of post-cost allocation solution time under different cooperative game methods

[0137] As can be seen from Table 3, when N = 8, the calculation time of SVM and NM is more than 1000 min, and when N = 20, the calculation time of SVM and NM has reached an impossible solution, which cannot be applied in practice. Unlike these methods, the solving time of the proposed GNB method is only 270.5 min when N = 20, which is completely acceptable and conducive to practical application. The reasons are as follows: GNB only needs to solve the planning model of the entire community and each independent producer and consumer, and the basic calculation complexity is O(N+1). MCRS needs to solve the planning model of the entire community and the maximum and minimum sub-alliances, and the basic calculation complexity is O(2N+1). SVM and NM both need to traverse all possible cooperative sub-alliances, so the basic calculation complexity of the two is O(2N-1). In summary, compared with other cooperative game methods, the solving efficiency of the proposed GNB is superior to that of the commonly used cooperative game method, and the practicability is stronger.

[0138] In the embodiment of the application, the producer and consumer charging power, the producer and consumer discharging power, and the community shared energy sharing power are obtained; a shared contribution quantification algorithm is constructed based on the producer and consumer charging power, the producer and consumer discharging power, and the community shared energy sharing power; the shared contribution degree of different producers and consumers to the alliance is quantified according to the shared contribution quantification algorithm; a cost allocation algorithm based on the generalized Nash bargaining theory is constructed based on the shared contribution degree, and the allocation cost of different producers and consumers is determined according to the cost allocation algorithm, at this time, the shared contribution degree of different producers and consumers to the alliance is compatible and quantified, so as to facilitate the determination of the allocation cost of different producers and consumers according to the cost allocation algorithm, to ensure the reasonable allocation of the cost of different producers and consumers, to realize the reasonable allocation of the cost of the community shared energy, and to avoid the use of a single contribution degree for cost division.

[0139] Embodiment

[0140] Please refer to FIG. 6, which is a structural composition schematic diagram of a community shared energy cost allocation system in the embodiment of the application.

[0141] As shown in FIG. 6, a community shared energy cost allocation system comprises:

[0142] The acquisition module 21 is configured to obtain the producer and consumer charging power, the producer and consumer discharging power, and the community shared energy sharing power;

[0143] The algorithm module 22 is configured to construct a shared contribution quantification algorithm based on the producer and consumer charging power, the producer and consumer discharging power, and the community shared energy sharing power;

[0144] The quantification module 23 is configured to quantify the shared contribution degree of different producers and consumers to the alliance according to the shared contribution quantification algorithm;

[0145] The allocation cost module 24 is configured to construct a cost allocation algorithm based on the generalized Nash bargaining theory based on the respective sharing contribution degrees, and determine the allocation cost of different producers and consumers according to the cost allocation algorithm.

[0146] Embodiments

[0147] Referring to FIG. 7, an electronic device 40 according to an embodiment of the present application will be described below with reference to FIG. 7. FIG. 7 shows the electronic device 40 as only one example, and should not be taken as limiting the functions and the use range of the embodiments of the present application.

[0148] As shown in FIG. 7, the electronic device 40 is in the form of a general computing device. The components of the electronic device 40 can include, but are not limited to, the at least one processing unit 41 described above, the at least one storage unit 42 described above, and a bus 43 connecting different system components, including the storage unit 42 and the processing unit 41.

[0149] The storage unit stores program codes which can be executed by the processing unit 41, so that the processing unit 41 performs the steps according to various exemplary embodiments of the present application described in the above "Embodiments Methods" section of the present specification.

[0150] The storage unit 42 can include a readable medium in the form of a volatile storage unit, such as a random access memory (RAM) 421 and / or a cache memory 422, and can further include a read-only memory (ROM) 423.

[0151] The storage unit 42 can further include program / utilities 424 having a set of (at least one) program modules 425, such as an operating system, one or more application programs, other program modules, and program data, each of which or some combination of which can include implementation of a network environment.

[0152] The bus 43 can be one or more of several types of bus structures, including a storage unit bus or storage unit controller, a peripheral bus, a graphics acceleration port, a processing unit bus, or a local bus using any of a variety of bus architectures.

[0153] The electronic device 40 can also communicate with one or more external devices such as a keyboard or pointing device, a Bluetooth device, or a device that enables a user to interact with the electronic device 40. Additionally, the electronic device 40 can communicate with one or more devices that enable the electronic device 40 to perform a function such as a printer or a plotter, with one or more devices that enable the electronic device 40 to communicate with one or more other computing devices. Such communication can occur via an input / output (I / O) interface 44. Still yet, the electronic device 40 can communicate with one or more networks such as a local area network (LAN), a general wide area network (WAN), or a public network such as the Internet, via a network adapter 45. As depicted, the network adapter 45 communicates with the other components of the electronic device 40 via the bus 43. It should be understood that although not shown, other hardware and / or software components could be used in conjunction with the electronic device 40. Such components include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data archival

[0154] Those skilled in the art will readily understand that the example embodiments described herein can be implemented by software and / or by hardware coupled with software, as described above. Thus, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product. The software product can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash disk, a mobile hard disk, or the like) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to perform the methods according to the embodiments of the present disclosure.

[0155] Those skilled in the art will readily understand that all or part of the steps of the various methods described above can be performed by a program instructing relevant hardware, and the program can be stored in a computer-readable storage medium, which can include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc. Moreover, the computer-readable storage medium stores computer program instructions, which, when executed by a computer, enable the computer to perform the methods described above.

Claims

1. A cost allocation method of community shared energy storage, applied to a community shared energy storage scenario. The cost allocation method of the community shared energy storage comprises the following steps: Obtain the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage; Based on the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage, a shared contribution quantification algorithm is constructed; According to the shared contribution quantification algorithm, the shared contribution degree of different producers and consumers to the alliance is quantified; Based on the shared contribution degree, a cost allocation algorithm based on the generalized Nash bargaining theory is constructed, and the allocation cost of different producers and consumers is determined according to the cost allocation algorithm.

2. The cost allocation method of community shared energy storage according to claim 1, wherein, The method comprises the following steps: Collect the charging and discharging states of all producers and consumers at each time, and determine whether there is complementary charging and discharging demand between all producers and consumers at each time.

3. The cost allocation method of community shared energy storage according to claim 2, wherein, The method further comprises the following steps: If there is no complementary charging and discharging behavior between producers and consumers at time τ, the shared power of all producers and consumers at this time is 0, i.e. If there is complementary behavior between the producers and consumers at τ time, the overall charging power and overall discharging power of all producers and consumers at τ time are calculated. If the overall charging power at time τ is greater than the overall discharging power, the total amount of shared power is equal to the overall discharging power, i.e.

4. The cost allocation method of community shared energy according to claim 3, wherein, The method further comprises the following steps: Quantify the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage; Train the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage with an algorithm learning model, and construct a shared contribution quantification algorithm.

5. The cost allocation method of community shared energy according to claim 4, wherein, The method further comprises the following steps: Producer-consumer shared power calculation: In the formulae, Pn,y,u(τ) represents the shared power of producer-consumer u at time τ on the nth typical operating scenario day in year y; and respectively the charging and discharging power of the producer-consumer u at time τ; Sharing energy and power for community, and Respectively for the charging and discharging power of the community shared energy storage at τ time.

6. The cost allocation method of community shared energy according to claim 5, wherein, The method further comprises the following steps: Quantify the shared contribution quantification algorithm; Correlate the shared contribution quantification algorithm with different producers and consumers; Quantify the shared contribution degree of different producers and consumers to the alliance based on the shared contribution quantification algorithm.

7. The cost allocation method of community shared energy according to claim 6, wherein, The method further comprises the following steps: The sharing contribution degree of each producer and consumer can be expressed as: In the formula, χ u is the sharing contribution degree of producer-consumer u, and the value range is [0, 1]; w y,n is the probability of the typical operation day n appearing in the yth year; N y is the total number of years contained in the planning period; N d is the number of typical scenarios; N t is the number of time periods.

8. The cost allocation method of community shared energy according to claim 7, wherein, The method further comprises the following steps: Quantify the shared contribution degree; Based on the shared contribution degree, a cost allocation algorithm based on the generalized Nash bargaining theory is constructed; Determine the allocation cost of different producers and consumers according to the cost allocation algorithm.

9. The cost allocation method of community shared energy according to claim 8, wherein, The method further comprises the following steps: The cost allocation algorithm based on generalized Nash bargaining theory is as follows: In the formulae, The total cost of the energy storage configured by the producer-consumer u alone is the negotiation breaking point; χ u is the sharing contribution of the producer-consumer u.

10. A community shared energy storage cost allocation system, which is applied to the community shared energy storage cost allocation method according to any one of claims 1-9, and comprises: An acquisition module configured to obtain the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage; An algorithm module configured to construct a shared contribution quantification algorithm based on the charging power of the producer and consumer, the discharging power of the producer and consumer, and the shared power of the community shared energy storage. a quantification module configured to quantify the sharing contribution degrees of the different producers and consumers to the alliance according to a sharing contribution quantification algorithm; a cost distribution module configured to construct a cost distribution algorithm based on the generalized Nash bargaining theory based on the sharing contribution degrees, and determine the distribution costs of the different producers and consumers according to the cost distribution algorithm.

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