CN105160490A - Cooperative game and DEA (Data Envelopment Analysis) based method for sharing fixed cost of power transmission system - Google Patents

Abstract

The invention discloses a cooperative game and DEA (Data Envelopment Analysis) based method for sharing the fixed cost of a power transmission system. According to the method, a coalitional game model in a DEA framework is established, a method for sharing the fixed cost of the power transmission system with a nucleolus method is proposed based on a cooperative game and DEA from the perspective of multi-attribute decisions, the DEA and coalitional game based sharing of the fixed cost of the power transmission system is calculated under the condition that area constraints are ensured, and an optimal and reasonable weight is calculated within a limited weight range, so that each user obtains a satisfied sharing result and benefit maximization of each user is satisfied.

Description

A Fixed Cost Allocation Method for Transmission System Based on Cooperative Game and DEA

technical field

The invention relates to a method for apportioning fixed costs of a power transmission system based on cooperative game and DEA, in particular to a method for apportioning fixed costs in the case of traditional power generation, and belongs to the field of cost apportionment.

Background technique

There is a mapping relationship between the fixed cost of a general transmission system and a single load (or power generation) electricity, which is called cost-energy mapping. Research shows that the topological structure of cost-electricity mapping is complex, showing strong nonlinearity, discontinuity, high dimensionality and multi-period characteristics. That is to say, the information flow between the use of expenses or benefits and the payment of expenses is uncertain and complicated. At the same time, for grid operators who do not aim at profit, their fixed costs must be allocated reasonably, fairly and completely to users (users of fixed costs, including generators and power loads).

The fixed cost of transmission system has the characteristic of non-decoupling, that is, there is no one-to-one correspondence between the generation of fixed cost and the specific load. It is impossible to pinpoint which load is responsible for which part of the fixed costs. This is mainly because the power network is a monopoly operation, and all loads and generators must use the same power network at the same time, and the complex interactions between them jointly generate fixed costs, and it is usually impossible to distinguish the actual interaction responsibility in reality. do it. Therefore, the allocation of the fixed cost of the transmission system is a difficult problem that must be solved.

At present, in the operation of transmission systems in countries all over the world, fixed costs are usually apportioned according to the proportion of load. However, the disadvantages of the proportional apportionment method are very obvious. Not only is it easy to cause cross subsidies between loads, which violates the market principle of economic fairness, but more importantly, it cannot provide correct economic incentive signals to promote load distribution in the entire network. Reasonable distribution to achieve the optimization goal of reducing fixed costs and saving social resources.

The opening of the power transmission system will provide a standardized and fair competition environment for the power generation market and users, which enables power transactions to use power transmission resources or equipment under fair and non-discriminatory conditions. In order to ensure the normal and orderly opening of the transmission system, how to formulate a transmission pricing system is very important.

The electric power industry is undergoing significant changes all over the world. Many countries in the world are carrying out or will carry out the reform of the electric power industry, that is, deregulation, breaking monopoly, restructuring, and building a competitive market mechanism. The goal of power industry reform is to improve power production efficiency, rationalize the electricity price mechanism, provide safe and high-quality power products, promote the healthy development of the power industry, and achieve better economic and social benefits. At present, the power market reforms in Chile, Argentina, the United Kingdom, the United States, Australia and other countries have injected new vitality into their power industries and stimulated the development of power markets in other countries around the world. The electricity market is essentially a process in which buyers and sellers of electricity interact to determine their electricity prices and quantities. Specifically speaking, it is the sum of the management mechanism and execution system that organizes the coordinated operation of power generation, transmission, distribution, and users in the power system by using economic means and in line with the principles of fair competition, voluntariness and mutual benefit. The overall goal of power market construction is to introduce a competitive mechanism, optimize resource allocation, provide high-quality services, promote the rationalization of electricity prices, and promote the sustainable development of the power industry. One of the most important aspects of power market reform is to implement the opening of the transmission system, and the opening of the transmission system What brings is the pricing problem of the transmission system. Before the establishment of the electricity market, the power generation, transmission, and distribution systems of the power system were not separated, and the cost of the transmission system did not need to be charged separately to the power plant or user using the transmission line, but in fact, each user who uses electric energy included it in the electricity fee This part of the transmission cost. After the establishment of the electricity market, the transmission company and the power generation company are accounted for separately, and the transmission fee and the power generation fee are also separately accounted for. At this time, the members who use the transmission system will include many power plants and users, and they are connected through an intricate grid. How reasonable? The calculation and allocation of transmission costs has become an urgent problem in the electricity market.

The transmission pricing system includes the calculation and apportionment of transmission costs. The process can be regarded as the allocation of transmission costs among power plants or users using transmission lines, taking into account the balance of payments and appropriate profitability of the transmission company. The transmission cost of the power system is generally composed of two parts: one part reflects the operating cost of the power transmission system, also known as variable cost, which mainly includes the loss cost of electric energy, the congestion cost and the fixed cost sharing cost of power transmission based on the cooperative game kernel solution The other part is to reflect the investment and construction costs of transmission lines, also known as fixed costs, including the construction of transmission lines, the cost of purchasing equipment, operation management and maintenance costs, depreciation costs, and the rate of return on investment costs, etc., due to the fixed costs of the transmission system Occupy a large proportion in power transmission costs, and the apportionment method of the fixed cost of power transmission is also applicable to the apportionment of variable costs (network losses, congestion costs) of the power transmission system. In the present invention, only the fixed cost of power transmission is taken as an example to discuss the apportionment of expenses method.

The specific allocation method of transmission costs is determined by the Electricity Law and the regulations on the operation of the electricity market. Different pricing models can be implemented on different occasions or to achieve different operational purposes. Correspondingly, different pricing models can also be adopted under different pricing models. distribution form. If the cost settlement needs to meet the problem of complete recovery of the investment cost of the transmission system, the comprehensive cost allocation method can be used; if in order to provide users and power plants with clear system operation status information and promote the healthy development of network resources, the marginal cost method can be used. However, no matter which method is adopted, it is necessary to ensure the annual balance of the transmission company's income and expenditure as much as possible, to provide long-term or short-term economic information for users and power plants, and to be feasible and transparent to the complex transmission network and trading network.

There are many methods for calculating and apportioning transmission costs at home and abroad. On the whole, all methods cannot fairly allocate the fixed costs of transmission to each power generation that uses the transmission network while taking into account the complete recovery of transmission costs and the provision of economic signals. Therefore, no mature theory has been formed on the transmission pricing system. The practices of various countries are far from each other, and there is still a large gap between theory and practice.

Contents of the invention

The technical problem to be solved by the present invention is to provide a fixed cost allocation method for power transmission system based on cooperative game and DEA, which satisfies the axioms of validity, additiveness, non-negativity and scale invariance, and is a relatively reasonable fixed cost allocation method method.

The present invention adopts the following technical solutions for solving the problems of the technologies described above:

A transmission system fixed cost allocation method based on cooperative game and DEA, comprising the following steps:

Step 1. Obtain the basic situation of each user in the transmission system, including: load season, working system, peak-valley power price period division, peak-valley average power price ratio, power quality and power consumption;

Step 2, normalize the basic situation of each user to obtain the standardized index of each user;

Step 3, use the standardized index data of each user obtained in step 2, under the constraints of the guaranteed area, use the kernel solution of the DEA alliance game method to calculate the apportionment ratio of each user;

Step 4: Multiply the apportionment ratio of each user obtained in Step 3 by the fixed cost to obtain the cost to be apportioned by each user.

Preferably, the standardized indicators in step 2 include: direct power purchase indicators, power quality indicators, and time-of-use electricity price indicators.

Preferably, the calculation formula of the time-of-use electricity price index is: j=1,...,n, where D _j is the time-of-use electricity price index of the jth user, n is the total number of users, l is the number of typical days divided for each user, T _a is the number of days corresponding to the typical day a, α _a :1:β _a is the peak, average, and valley electricity price ratio of a typical day a, t _ja,f , t _ja,p , and t _ja,g are the peak, average, and valley utilization hours of user j on a typical day a, respectively.

Preferably, the formula for calculating the kernel solution of the DEA alliance game method in step 3 is: T _j /ΣT _j -y _j , wherein, T _j =D _j ω ₁ +Q _j ω ₂ +q _j ω ₃ , D _j , Q _j , and q _j are the time-of-use electricity price index, power quality index, and direct purchase electricity index of user j respectively, and ω ₁ , ω ₂ , and ω ₃ are the time-of-use electricity price index, power quality index, and direct purchase electricity index respectively. Weight value, y _j is the fixed cost ratio that user j can reduce after joining the alliance.

Preferably, the calculation method of y _j is the kernel allocation method.

Preferably, the calculation formulas of ω ₁ , ω ₂ , ω ₃ are:

$\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span>$

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; .</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; \&ForAll;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$

in, (i=1,...,m,j=1,...,n), S is the alliance formed by any subset of the user set N=(1,...,n), c(S) is the smallest alliance S Cost sharing, _Xij is the value of the i-th standardized indicator of the j-th user in the alliance S, m is the number of all standardized indicators, n is the number of all users, m=3.

Compared with the prior art, the present invention adopts the above technical scheme and has the following technical effects:

1. The present invention adopts a method based on the DEA alliance game, so that on the basis of satisfying the maximization of the interests of each user, by adding AR (guaranteed area) restrictions to the DEA alliance game, the optimal weight is calculated within the limited weight range. , Reasonable weight, so that all parties can get a satisfactory apportionment result.

2. All users of the present invention (i.e. users with fixed costs) use the entire power grid together, and the fixed costs of the power grid are generated by the joint action of all users, and the complex interactions between them jointly produce fixed costs, so it is necessary to distinguish the actual interaction Responsibility is often difficult to achieve in reality. But from the perspective of cooperative game, users constitute a de facto cooperative relationship. Using the method based on the DEA alliance game to invent the fixed cost allocation problem of the transmission system has the advantage of axiom.

3. The present invention uses the kernel solution as the distribution method of multi-person cooperative game, which has advantages that other methods do not have, and can ensure the stability of the alliance.

Description of drawings

FIG. 1 is an overall flow chart of the method for allocating fixed costs of a power transmission system based on cooperative game and DEA in the present invention.

Figure 2 is a graph of the allocation ratio of the fixed cost of the transmission system calculated by the Kernel method without AR constraints.

Fig. 3 is a distribution ratio diagram of the fixed cost of the power transmission system calculated by the Kernel method under AR constraints in the present invention.

Figure 4 is a comparison chart of the fixed cost allocation ratio of each user for the four methods (stamp method, Shapely value, unconstrained kernel method, and constrained kernel method).

Detailed ways

Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

Cooperative game theory is an important branch of microeconomics. Economic theory has proved that the fixed cost allocation method based on cooperative game theory satisfies the axioms of effectiveness, additiveness, non-negativity and scale invariance, and is a relatively reasonable fixed cost allocation method. In fact, economists have successfully applied this apportionment method on public utility network cost apportionment, such as water supply system cost apportionment and telecommunication network operating cost apportionment, etc., and achieved good apportionment results. The kernel method is one of the methods for solving cooperative game problems, and it is mainly used in the distribution of the common costs generated by the simultaneous use of a certain facility among the cooperative parties.

Data envelopment analysis (DEA) is a mathematical programming method and a widely recognized efficiency evaluation method. It uses multi-objective programming theory and non-parametric methods based on the relative performance of input and output to quantitatively evaluate the relative effectiveness of departments under the multi-input-multi-output model. The data envelopment analysis method is generally used to evaluate the relative efficiency among a group of multiple decision-making units (DecisionMakingUnit, DMU). A decision-making unit can be understood as an entity that invests certain elements in the social, economic and management fields to produce certain products. In this system, the same type of decision-making units with the same goal, the same external environment and the same input-output indicators can form a set of decision-making units. Using the input-output index data of decision-making units as the evaluation basis, the relative efficiency of each decision-making unit can be sorted, and ineffective decision-making units can be pointed out. Among them, the input index is used to represent the amount of resources consumed by the decision-making unit in related economic activities; the output index represents the economic output obtained by the decision-making unit on the premise of input factors.

For the fixed cost allocation of the transmission system, there are currently embedded cost methods (also known as comprehensive cost methods) and marginal cost methods. The embedded cost methods mainly include postage stamp method, contract path method, boundary flow method, MW-km method; marginal cost method is divided into short-term and long-term marginal cost method.

Aiming at the operation characteristics of my country's power grid, a comprehensive allocation method for the fixed cost of multi-factor large user transshipment costs, which considers time-of-use electricity price, power quality and purchased electricity, is proposed, that is, the modified stamp method, which solves this problem better. However, since the determination of its weight is determined by the interaction between the power grid and users, it increases the difficulty of transactions.

The method based on DEA coalition game is a new direction of DEA research, which is used to deal with the problem of fixed cost allocation and has good results. The present invention uses the DEA alliance game method, so that on the basis of maximizing the interests of each user, by adding the guarantee area (AR) restriction to the DEA alliance game, the optimal and reasonable weight is calculated within the limited weight range. Weights, so that all parties can get a satisfactory apportionment result.

Cooperative game means that several participants in the system combine with each other to form a coalition, and work together to obtain the maximum benefit in the coalition, and then distribute the common benefits in the coalition system. The concepts of cooperative game allocation solution mainly include core, Shapley value, nucleolus, etc. In the present invention, the nucleolus method is mainly used to solve the fixed cost allocation problem of the transmission system.

The process flow of the transmission system fixed cost allocation method based on cooperative game and DEA in the present invention is shown in FIG. 1 , and the data used in the embodiment based on the flow chart is shown in Table 1. For the sake of simplicity, this embodiment directly provides five power quality grades: A, B, C, D, and E, and the corresponding power quality indexes are 5, 4, 3, 2, and 1. First, we need to perform dimensionless normalization on the data to obtain Table 2.

Table 1 Basic information of each user

Table 2 Standardized indicators for each user

user name Direct power purchase indicator Power Quality Index Time-of-use electricity price index User A 0.4223 0.1818 0.5192 User B 0.4114 0.0909 0.2762 User C 0.0845 0.2727 0.1440 User D 0.0819 0.4545 0.0606

Data envelopment analysis: Let any subset S of user sets N=(1,...,n) in the power transmission system form an alliance. For example {1,2}, {1,2,4} etc. Define the value of alliance S as:

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; \&Element;</span>\mathrm{<span\; class="notranslate">\; the\; s</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; j</span>}}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; m</span>}<span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; j</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span><span\; class="notranslate">\; ...</span><span\; class="notranslate">\; ,</span>\mathrm{<span\; class="notranslate">\; no</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$

Wherein, X _ij is the value of the i-th standardized indicator of the j-th user in the alliance S, m is the number of all standardized indicators, and n is the number of all users. In the present invention, n is 4, and m is 3.

The purpose of forming an alliance S is to obtain the minimum alliance allocation cost c(S), which can be solved by solving the following linear programming:

$\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}{\mathrm{<span\; class="notranslate">\; min</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span>$

$\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; .</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; \&ForAll;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>$

Wherein, ω _i is the weight value corresponding to x _i (S).

Calculate the comprehensive index of each user according to the following formula: T _j = D _j ω ₁ + Q _j ω ₂ + q _j ω ₃ , where D _j , Q _j , q _j are time-of-use electricity price index, power quality index, direct Power purchase index.

The apportioned cost of each user can be obtained according to the cost apportionment formula: C′ _j =C×T _j /ΣT _j .

Kernel method: define the alliance revenue function as follows: where c(S) is the coalition feature function.

minz=y ₅

s.ty ₁ +y ₂ +y ₃ +y ₄ +y ₅ =1

y ₁ +y ₂ +y ₅ ≥c(A,B)

y ₁ +y ₃ +y ₅ ≥c(A,C)

y ₁ +y ₄ +y ₅ ≥c(A,D)

y ₂ +y ₃ +y ₅ ≥c(B,C)

y ₂ +y ₄ +y ₅ ≥c(B,D)

y ₃ +y ₄ +y ₅ ≥c(C,D)

y ₁ +y ₂ +y ₃ +y ₅ ≥c(A,B,C)

y ₁ +y ₂ +y ₄ +y ₅ ≥c(A,B,D)

y ₁ +y ₃ +y ₄ +y ₅ ≥c(A,C,D)

y ₂ +y ₃ +y ₄ +y ₅ ≥c(B,C,D)

y ₁ +y ₅ ≥c(A)

y ₂ +y ₅ ≥c(B)

y ₃ +y ₅ ≥c(C)

y ₄ +y ₅ ≥c(D)

Use matlab to solve the values of y ₁ , y ₂ , y ₃ , and y ₄ , which respectively represent the fixed cost ratio that each user can reduce after joining the alliance. The values of the alliance in the formula all adopt the alliance value under the AR constraint. It can be concluded that the fixed cost that each user can reduce after the alliance is:

y′ _j =y _j ×C

Therefore, the fixed cost that each user needs to share is:

According to the nucleolus apportionment method, the data in Table 3 and Table 5 are used for calculation, which are without AR constraints and AR constraints respectively. It can be seen that according to the information in Table 3, individual rationality, cooperative rationality, and overall rationality in the kernel may not be able to satisfy , so the kernel does not exist in the coalition game without AR constraints, see Table 4. The core exists in the coalition game with AR constraints. See Table 6 for the results of the coalition game under AR constraints obtained by the kernel apportionment method. Table 4 and Table 6 correspond to Figure 2 and Figure 3, respectively.

Table 3 The characteristic functions of each alliance under the condition of no AR constraint

Table 4 Values of nucleolus apportionment method without AR constraints

user name User A User B User C User D Shapley value 0.3455 0.2404 0.1478 0.2664

Table 5 has the characteristic functions of each alliance under AR constraints

Table 6 has the value of nucleolus apportionment method under AR constraints

user name User A User B User C User D Shapley value 0.3864 0.3299 0.0971 0.1867

As shown in Figure 4, it is a comparison chart of the fixed cost allocation ratio of each user for the four methods (stamp method, Shapely value, unconstrained kernel method, and constrained kernel method). Through the comparison of the four methods, the rationality of using the AR-DEA alliance game kernel method is further illustrated.

The above embodiments are only to illustrate the technical ideas of the present invention, and cannot limit the protection scope of the present invention with this. All technical ideas proposed according to the present invention, any changes made on the basis of technical solutions, all fall within the protection scope of the present invention. Inside.

Claims (6)

1. A transmission system fixed cost apportionment method based on cooperative game and DEA, is characterized in that: comprise the steps: Step 1. Obtain the basic situation of each user in the transmission system, including: load season, working system, peak-valley power price period division, peak-valley average power price ratio, power quality and power consumption; Step 2, normalize the basic situation of each user to obtain the standardized index of each user; Step 3, use the standardized index data of each user obtained in step 2, under the constraints of the guaranteed area, use the kernel solution of the DEA alliance game method to calculate the apportionment ratio of each user; Step 4: Multiply the apportionment ratio of each user obtained in Step 3 by the fixed cost to obtain the cost to be apportioned by each user. 2. The fixed cost allocation method for power transmission system based on cooperative game and DEA as claimed in claim 1, characterized in that: the standardized indicators in step 2 include: direct power purchase indicators, power quality indicators and time-of-use electricity price indicators. 3. The transmission system fixed cost allocation method based on cooperative game and DEA as claimed in claim 2, characterized in that: the calculation formula of the time-of-use electricity price index is: ${\mathrm{D.}}_j=\underset{a=1}{\overset{l}{\&Sigma;}}{T}_a({\mathrm{\&alpha;}}_a{t}_{ja,f}+t_{ja,p}+{\mathrm{\&beta;}}_a{t}_{ja,g}),j=1,...,\mathrm{no},$ Among them, D _j is the time-of-use electricity price index of the jth user, n is the total number of users, l is the typical number of days divided for each user, T _a is the number of days corresponding to the typical day a, α _a : 1: β _a is the typical day The peak, average, and valley electricity price ratios of a, t _ja,f , t _ja,p , and t _ja,g are the peak, average, and valley utilization hours of user j on a typical day, respectively. 4. The transmission system fixed cost allocation method based on cooperative game and DEA as claimed in claim 1, characterized in that: the calculation formula of the kernel solution of the DEA alliance game method described in step 3 is: T _j /ΣT _j -y _j , Among them, T _j ＝D _j ω ₁ +Q _j ω ₂ +q _j ω ₃ , D _j , Q _j , q _j are user j’s time-of-use electricity price index, power quality index, and direct purchase electricity index respectively, ω ₁ , ω ₂ and ω ₃ are the weight values corresponding to the time-of-use electricity price index, power quality index, and direct purchase electricity index respectively, and y _j is the fixed cost ratio that user j can reduce after joining the alliance. 5. The fixed cost allocation method for power transmission system based on cooperative game and DEA as claimed in claim 4, characterized in that: the calculation method of _yj is kernel allocation method. 6. The transmission system fixed cost allocation method based on cooperative game and DEA as claimed in claim 4, characterized in that: the calculation formulas of ω ₁ , ω ₂ , ω ₃ are: $\mathrm{<span\; class="notranslate">\; c</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\underset{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}{\mathrm{<span\; class="notranslate">\; m</span>}\mathrm{<span\; class="notranslate">\; i</span>}\mathrm{<span\; class="notranslate">\; no</span>}}\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; S</span>}<span\; class="notranslate">\; )</span>$ $\begin{array}{cc}\mathrm{<span\; class="notranslate">\; the\; s</span>}<span\; class="notranslate">\; .</span>\mathrm{<span\; class="notranslate">\; t</span>}<span\; class="notranslate">\; .</span>& \underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\overset{\mathrm{<span\; class="notranslate">\; m</span>}}{<span\; class="notranslate">\; \&Sigma;</span>}}{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; ,</span>{\mathrm{<span\; class="notranslate">\; \&omega;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}<span\; class="notranslate">\; \&Greater\; Equal;</span>\mathrm{<span\; class="notranslate">\; 0</span>}<span\; class="notranslate">\; (</span><span\; class="notranslate">\; \&ForAll;</span>\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; ,</span>\end{array}$ in, (i=1,...,m,j=1,...,n), S is the alliance formed by any subset of the user set N=(1,...,n), c(S) is the The minimum alliance cost sharing, _Xij is the value of the i-th standardized indicator of the j-th user in the alliance S, m is the number of all standardized indicators, n is the number of all users, m=3.