CN117081080A - Hydropower station compensation allocation scheme evaluation method with maximum power generation benefit as target - Google Patents
Hydropower station compensation allocation scheme evaluation method with maximum power generation benefit as target Download PDFInfo
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Abstract
The invention discloses a hydropower station compensation allocation scheme evaluation method aiming at the maximum power generation benefit, which comprises the following steps: establishing a hydropower station power generation optimizing and scheduling model, and comparing the generated energy of each hydropower station in different alliance modes; performing compensation allocation of the cascade hydropower station by using different compensation allocation methods; carrying out stability evaluation on the allocation results of different compensation allocation methods; establishing an index system, constructing an evaluation index value matrix, and making a compensation allocation scheme of the cascade hydropower station; based on the remorse theory, an optimal compensation allocation scheme is calculated. According to the invention, a plurality of compensation allocation schemes are made for the cascade hydropower station, the stability is used as one of indexes, an index system is established, the compensation allocation schemes are comprehensively evaluated, the selected optimal compensation allocation scheme has stability, the overall optimization of the cascade hydropower station is realized, and the joint scheduling and mutual cooperation of the cascade hydropower station are promoted.
Description
Technical Field
The invention belongs to the field of hydropower station scheduling, and particularly relates to a hydropower station compensation allocation scheme evaluation method aiming at the maximum power generation benefit.
Background
Under the large-scale development of water energy resources in China, the cascade hydropower station groups in large watercourses are of initial scale, the hydropower station groups do not pursue the maximum power generation capacity of a single hydropower station on one side, but start from the integral cascade, limited water energy resources are reasonably utilized to generate comprehensive benefits as large as possible. However, in the development of the cascade in the river basin, each hydropower station at the upstream and downstream of the cascade may belong to different owners, and during the joint scheduling operation, the upstream tap hydropower station and other hydropower stations with larger runoff adjustment capability often need to sacrifice part of the interests of themselves to improve the power generation benefits of the downstream power stations, so that the whole cascade is optimized, and the problem of the compensation benefit sharing among the cascade hydropower stations of multiple owners is related to the promotion of the joint scheduling and the mutual cooperation of the cascade hydropower stations.
At present, the main method for compensating benefit allocation of the cascade hydropower station comprises the following steps: treaties, agreements or rules, single index methods, comprehensive index methods, proportional distribution methods, shapley methods, and the like. According to more example analysis, various allocation methods can be applied to compensation benefit allocation of the cascade hydropower station, and how to select an optimal scheme from the compensation benefit allocation is a real problem to be solved.
In view of the above, a hydropower station compensation allocation scheme evaluation method is researched, an index system of a three-lining-level, temple-level and transitional bay cascade hydropower station compensation benefit allocation scheme on a south river basin in Han river is established, and comprehensive evaluation is carried out on various cascade hydropower station compensation benefit allocation schemes based on a subjective and objective comprehensive weighting method and a regret theory.
Disclosure of Invention
The invention has the technical problems that the existing cascade hydropower station compensation allocation methods are multiple, the cascade hydropower station compensation allocation schemes established according to the methods have advantages and disadvantages, the existing method for evaluating the cascade hydropower station compensation allocation scheme is lacking, and the problem that how to establish a fair and reasonable compensation allocation scheme and select an optimal scheme from the established multiple compensation allocation schemes is still to be solved is still urgent.
The invention aims to solve the problems, and provides a hydropower station compensation allocation scheme evaluation method aiming at the maximum power generation benefit, which utilizes different compensation allocation methods to carry out cascade hydropower station compensation allocation and carries out stability evaluation on compensation allocation results, establishes the compensation allocation scheme of the hydropower station by establishing an index system, and selects an optimal compensation allocation scheme based on the remorse theory to promote joint scheduling and mutual cooperation of the cascade hydropower station so as to ensure that the integral cascade hydropower station is optimal.
The technical proposal of the invention is a hydropower station compensation allocation scheme evaluation method aiming at the maximum power generation benefit, which comprises the following steps,
step 1: establishing a hydropower station power generation optimizing and scheduling model, and comparing the generated energy of each hydropower station in different alliance modes;
step 1.1: respectively establishing power generation optimizing and scheduling models by taking the maximum power generation benefit of a single hydropower station or the maximum power generation benefit under different alliance modes as an objective function:
step 1.2: determining constraint equations, wherein the constraint equations mainly comprise water quantity balance equations, hydropower station water storage capacity constraint, reservoir water level constraint, hydropower station output constraint, reservoir lower drainage flow constraint and flow connection between an upstream hydropower station and a downstream hydropower station;
step 1.3: carrying out power generation dispatching optimization calculation by adopting a dynamic programming method to obtain the power generation amount and the power generation benefit of each hydropower station in different alliance modes;
step 2: performing compensation allocation of the cascade hydropower station by using different compensation allocation methods;
step 3: performing stability evaluation on the compensation allocation result in the step 2;
step 4: establishing an index system, constructing an evaluation index value matrix, and making a compensation allocation scheme of the cascade hydropower station;
the index system comprises an allocation proportion, a step increase power generation amount, a minimum output and a splitting tendency value;
step 5: based on the regret theory, calculating to obtain the optimal compensation allocation scheme according to the evaluation index values of the compensation allocation schemes in the step 4.
Preferably, in step 2, the different compensation allocation methods include a contribution degree method, a variation coefficient method, a shape value method, and a variation coefficient-shape value method.
Preferably, in step 3, the stability of the compensation allocation result in step 2 is evaluated by adopting a splitting tendency method.
Further, step 4 further includes calculating weights of the respective indexes of the index system by using an expert scoring method and an entropy weighting method.
Preferably, the index system of the step 4 comprises an allocation proportion, a step increase generating capacity, a minimum output and a splitting tendency value.
Further, in step 1.1, the power generation optimization scheduling model is as follows:
1) The annual power generation benefit of a single hydropower station is the largest:
2) The annual power generation benefit is the largest under different alliance modes:
b is the total power generation benefit of the allied hydropower station in the scheduling period; k is the total number of alliance hydropower stations; i is the hydropower station number, which indicates the ith hydropower station in the cascade; t and T are respectively the time interval numbers and the total time interval numbers of the scheduling periods; a is that i The comprehensive output coefficient of the hydropower station i; q (Q) i，t The flow is quoted for the power generation of the hydropower station i in a period t; h i，t Generating water head for hydropower station i in period t; Δt is the time period length; p is p i The electricity price of the hydropower station i is the internet.
Further, step 5 comprises the sub-steps of,
step 5.1: constructing an evaluation index value matrix of the compensation allocation scheme and carrying out standardization processing on the evaluation index value matrix;
step 5.2: taking the optimal value of the index evaluation value in the standardized matrix aiming at each index, and establishing an ideal scheme;
step 5.3: constructing a regret value matrix;
step 5.4: constructing a perception utility matrix;
step 5.5: calculating the comprehensive perception utility value of each compensation allocation scheme by combining the weight of each index;
step 5.6: and (5) comparing the comprehensive perception utility values of the compensation allocation schemes, and selecting an optimal compensation allocation scheme.
Compared with the prior art, the invention has the beneficial effects that:
1) According to the invention, a plurality of compensation allocation schemes are made for the cascade hydropower station, the stability of the compensation allocation result is used as one of indexes, an index system of the compensation allocation scheme is established, the compensation allocation scheme is comprehensively evaluated, the optimal compensation allocation scheme of the cascade hydropower station is conveniently selected, the selected optimal compensation allocation scheme has stability, the overall optimization of the cascade hydropower station is realized, and the joint scheduling and mutual cooperation of the cascade hydropower station are promoted;
2) The variation coefficient-shape method provided by the invention considers individual characteristics of the power station and marginal contribution of the power station, and promotes the downstream power stations at all levels to actively participate in cascade joint scheduling while fully determining the effect and value of the tap power station in the alliance;
3) The invention combines the remorse theory and the utility, truly reflects the decision-making behavior of the hydropower station owner, and increases the accuracy and the scientificity of the optimal compensation allocation scheme.
Drawings
The invention is further described below with reference to the drawings and examples.
FIG. 1 is a flow chart of a hydropower station compensation allocation scheme evaluation method aiming at the maximum power generation benefit.
Fig. 2 is a schematic diagram of an embodiment of a cascade hydropower station.
FIG. 3 is a comparison of different compensation apportionment methods of the embodiments.
Detailed Description
As shown in fig. 1, the hydropower station compensation allocation scheme evaluation method aiming at the maximum power generation benefit comprises the following steps,
step 1: establishing a hydropower station power generation optimizing and scheduling model, and calculating the power generation benefits of each hydropower station in different alliance modes;
step 1.1: respectively establishing power generation optimizing and scheduling models by taking the maximum power generation benefit of a single hydropower station or the maximum power generation benefit under different alliance modes as an objective function:
(1) the annual power generation benefit of a single hydropower station is the largest:
(2) the annual power generation benefit is the largest under different alliance modes:
b is the total power generation benefit of the allied hydropower station in the dispatching period; k is the total number of alliance hydropower stations; i is the hydropower station number, which indicates the ith hydropower station in the cascade; t and T are respectively the time interval numbers and the total time interval numbers of the scheduling periods; a is that i The comprehensive output coefficient of the hydropower station i; q (Q) i，t For hydropower station i in period tElectric reference flow; h i，t Generating water head for hydropower station i in period t; Δt is the time period length; p is p i The electricity price of the hydropower station i is the internet.
Step 1.2: the constraint equation is determined, and mainly comprises a water quantity balance equation, a hydropower station water storage capacity constraint, a reservoir water level constraint, a hydropower station output constraint, a reservoir lower drainage flow constraint, a flow connection between an upstream hydropower station and a downstream hydropower station and the like.
Step 1.3: and (3) carrying out power generation dispatching optimization calculation by adopting a dynamic programming method to obtain the power generation amount and the power generation benefit of each hydropower station in different alliance modes.
Step 2: the compensation benefit allocation is carried out by adopting a contribution degree method, a variation coefficient method, a shape value method and a variation coefficient-shape value method respectively;
the contribution degree method is that in the generation benefits of the cascade hydropower station joint optimization scheduling, the higher the efficiency of converting the unit hydropower station into electric energy and then into the generation benefits, the larger the contribution degree to the joint scheduling generation benefits is, and the calculation formula is as follows:
wherein x is i The apportionment proportion of the ith hydropower station; n is the total number of the cascade hydropower stations; p is p i k i The potential energy of the ith hydropower station is converted into a conversion coefficient of generating benefits; k (k) i The power generation efficiency coefficient represents the coefficient of converting potential energy into electric energy; p is p i And the online electricity price represents the coefficient of converting the electric energy into the power generation benefit.
The coefficient of variation method is an objective weighting method, and the method weights the individual characteristic parameters of the hydropower station according to the degree of variation of the observed values of all the evaluated individual characteristic parameters. Assuming n hydropower stations, each having m individual characteristic parameters, a parameter value matrix x= (X) is formed ij ) n×m The calculation process is as follows:
(1) each parameter value is normalized, and then the parameter value matrix is normalized, so that each parameter value is greater than 0, and in the [0.6,1] range, the forward parameters are as follows:
wherein Y is ij Is the standard value of the characteristic parameter j of the ith hydropower station, Y ij ∈[0.6，1]；X max j 、X min j The maximum and minimum feature values of the feature parameter j.
(2) Calculating the average value and the mean square error of the j-th characteristic parameter value:
(3) calculating a variation coefficient of the j-th characteristic parameter value:
(4) calculating the weight value of the j-th characteristic parameter:
(5) calculating the specific gravity of the j characteristic parameter value of the i hydropower station:
(6) calculating the comprehensive weight value of the ith hydropower station:
wherein v i The individual characteristic weight coefficient of the ith hydropower station, namely the apportionment proportion.
The Shapley method is a mathematical method for solving the problem of benefit allocation of multiparty cooperative countermeasures, and the method carries out benefit allocation according to the expected value of marginal cost of participators so as to ensure the effectiveness and fairness of allocation.
The basic axiom used by the Shapley value has symmetrical axiom, effective axiom and additive axiom. After meeting the basic axiom, the Shapley value of each hydropower station has a unique solution:
wherein s is the number of water power stations in the alliance; n is all possible alliance modes; s is a sub-alliance of N; (s-1) ++! (n-s) ++! /n-! The federation probability for federation S to occur; v (S) -v (S-i) is the marginal contribution of station i to the league S.
Combining the advantages of the coefficient of variation method and the Shapley method to provide a coefficient of variation-Shapley method, and obtaining individual characteristic weight coefficients upsilon of each hydropower station according to formulas (4) - (10) i Obtaining a Shapley value sigma of each hydropower station according to a formula (11) i The coefficient of variation-shape method formula is as follows:
θ i ＝υ i σ i (12)
wherein x is i The apportionment proportion of the ith hydropower station; upsilon (v) i The characteristic weight coefficient of the individual characteristic of the ith hydropower station; sigma (sigma) i Is the Shapley value of the ith hydropower station.
Step 3: performing stability evaluation on the allocation results of the 4 compensation allocation methods in the step 2 by using a splitting tendency (Propensity to disrupt, PTD) method;
the split tendency method is a common method for quantitatively evaluating the stability of a cooperative game solution, and is the ratio of the loss suffered by a large league losing a member i to the loss suffered by the member i leaving the large league under a certain allocation result:
wherein PTD i A split tendency of member i for a certain allocation result; c i Distributing the obtained benefits for the member i in the big alliance; v (i) is the benefit obtained when member i performs single library scheduling; v (N- { i }) is the large coalition total revenue for losing member i.
Step 4: establishing an index system by taking the allocation proportion, the step increase power generation amount, the minimum output and the PTD value as indexes, and establishing 4 compensation allocation schemes to construct an index evaluation value matrix;
step 5: and (4) evaluating the 4 allocation schemes formulated in the step (4) based on the regret theory to obtain an optimal allocation scheme.
The regret theory is a theory which considers two different psychological behaviors of regret and happiness simultaneously in decision making under the premise of giving up the independence axiom, and is specifically expressed as a perception utility function. This function is mainly divided into two parts: the utility function of the current selection scheme is firstly, and the remorse-euphoria function of the current selection scheme is secondly selected. Let a and B be the results obtained by selecting the a-scheme and the B-scheme, respectively, then the decision maker selects the perceptual utility function of scheme a as:
q(a,b)＝v(a)+R(v(a)-v(b)) (15)
the functions v (a) and v (B) are utility functions obtained by selecting the A scheme and the B scheme respectively, the functions R (v (a) -v (B)) are remorse-euphoric functions, and when the remorse-euphoric function value is larger than 0, the functions are expressed as that the A scheme and the B scheme are selected to feel happy; when the regret-euphoria function value is less than 0, the regret is expressed as a choice of a scheme and a non-choice of a scheme.
For a number of different schemes, the decision maker's perceptual utility function is as follows
q i ＝v(a i )+R(v(a i )-v(a*)) (16)
Where a=max { a } i ，i＝1，2，…，m}；R(v(a i )-v(a*))<And 0, namely that the regret-euphoria function value is a negative number, and represents the regret degree of a decision maker.
The evaluation process of the allocation scheme comprises the following steps:
assume that F compensation benefit allocation schemes form a decision scheme set M= (M) 1 ，M 2 ，…，M F ) L decision indexes form index set I= (I) 1 ，I 2 ，…，I L ) Wherein the splitting tendency (PTD) is one of the indexes, and the index weight is W= (W) 1 ，w 2 ，…，w L )。
(1) Constructing an evaluation index value matrix and a normalization process thereof
The evaluation index value matrix of the evaluation value of the scheme set M to the index set I is as follows:
because of the differences in nature or magnitude between the various decision metrics, the sample matrix needs to be normalized first:
in order for each parameter value to be greater than 0, and within the range of [0.6,1], for the benefit-type index:
for the cost index:
wherein x is ij Representing the decision maker at I j Index lower scheme M i Is a value of (1); x is x maxj Representing the decision maker at I j Index lower scheme M i The largest value among the evaluation values of (a); x is x minj Representing the decision maker at I j Index lower scheme M i The smallest value among the evaluation values of (2); y is ij Is I j Scheme under index M i Standard value, y ij ∈[0.6，1]，(i＝1，2，…，F；j＝1，2，…，L)。
(2) Establishing an ideal scheme
Let x be j + ＝max(x ij ) (i=1, 2, …, F; j=1, 2, …, L), called
x j + ＝(x 1 + ，x 2 + ，…，x L + ) (20)
Is an ideal scheme for decision making;
(3) construction of regret matrix
Calculating different index values x ij The value v of the functional effect of (2) ij It is necessary to construct the utility function v (x) first. In view of the fact that when risk decision is made in real life, a decision maker avoids risks as much as possible, so that the utility function v (x) is a concave function which is monotonically increased, and v '(x) > 0 and v' (x) are satisfied<0. The utility function is represented by a power function, and the calculation formula is as follows
v(x)＝x α (21)
Where 1 > α > 0, the smaller α indicates the more risk is circumvented by the decision maker.
(4) Construction of a perceptual utility matrix
And respectively calculating the remorse value of each scheme, and constructing a remorse-happiness function R (.). In view of the risk avoidance of the decision maker, the remorse-euphoric function R (·) is a monotonically increasing concave function, i.e., the remorse-euphoric function satisfies: r' (. Cndot.) is > 0 and R "(. Cndot.) is <0. The calculation formula of the regret-euphoria function value of the decision maker is as follows
Wherein epsilon is the remorse avoidance coefficient of a decision maker, and the larger epsilon is, and the larger remorse avoidance degree is; v ab Is the difference in utility values for 2 different schemes.
Then the utility perception function matrix of the decision maker is constructed by the formulas (8) and (9) as
q ij ＝v ij +R ij (23)
(5) And determining subjective and objective comprehensive weights by an expert scoring method and an entropy weight method:
the expert scoring method is a qualitative description quantification method, which comprises the steps of firstly selecting a plurality of evaluation indexes according to specific requirements of evaluation objects, then preparing an evaluation standard according to the evaluation indexes, adopting a plurality of representative experts to give evaluation scores of the indexes according to the evaluation standard by virtue of own experience, and then integrating the evaluation scores. The weight of the index j calculated by expert scoring is denoted as w zj 。
The entropy weight method is one of the comprehensive index methods. Information is a measure of the degree of order in the system, entropy is a measure of the degree of disorder in the system, the sign of the two is opposite, and the absolute values are equal. The entropy can be used for measuring and evaluating the information content of index data, and meanwhile, the weight value of each index can be determined.
The entropy weight method comprises the following steps of:
a. information entropy of each index is calculated
Wherein e j Information entropy indicating evaluation index j, U ij The ratio of the jth evaluation index value of the ith scheme is expressed,y ij the standard value of the evaluation index j of the ith scheme;
b. determining weights of various indexes
Wherein w is kj Weight g representing evaluation index j calculated by entropy weight method j Representation ofThe j-th characteristic index difference coefficient g j ＝1-e j 。
Comprehensive subjective and objective weights:
w j to evaluate the comprehensive subjective and objective weight and parameter of index jAnd determining according to the preference information of the decision maker.
(6) Calculation scheme M i The comprehensive perception utility value under different indexes is calculated as follows:
in the embodiment, a cascade hydropower station consisting of a three-lining-level hydropower station A, a temple-level hydropower station B and a transitional bay hydropower station C on a downstream main stream in a south river is selected as an implementation object, and the annual runoff process of 50% of the annual runoff of the three-lining-level water is taken as an annual runoff process, so that compensation and allocation calculation is carried out. The positional relationship of the 3 power stations is shown in fig. 2.
The implementation results are as follows:
(1) Solving the power generation optimizing dispatching model in the step 1 by adopting a dynamic programming method, the power generation amount and the power generation benefit of the three-lining-level, temple-level and transition bay 3 hydropower stations under different alliance modes are obtained, and are shown in table 1.
TABLE 1 generating capacity and generating benefit table of each hydropower station under different alliance modes
The total power generation amount of the steps of the combined operation of the three-lining-level, the temple-level and the transition bay 3 hydropower stations is increased by 0.738 hundred million kwh compared with the total power generation amount of the independent operation of the 3 hydropower stations, the total power generation benefit is increased by 0.290 hundred million yuan, and the compensation allocation proportion calculation is carried out according to the 4 compensation allocation methods in the step 2, so that the results are shown in fig. 3 and table 2.
Table 2 Compensation and sharing proportion table for each hydropower station
As can be seen from table 2, the three-lawn hydropower station is used as a tap power station, and has the compensation adjustment capability, so that the overall power generation benefit of the steps is greatly improved, and the highest compensation benefit is obtained when the compensation benefit is shared, so that the compensation adjustment effect of the tap power station is fully ensured; the temple and the transition bay hydropower stations have large allocation difference when obtaining compensation benefits higher than those of each power station when independently operating, so that individual differences among secondary power stations can be seen, and the effective allocation method is favorable for promoting the downstream power stations at all levels to actively participate in joint scheduling.
(2) The tendency to split was calculated and the results are shown in Table 3. The greater the PTD value of hydropower station i, the less revenue it receives compared to its contribution to the federation, the more prone it tends to leave the federation; conversely, the smaller the PTD value, the more prone hydropower station i will stay in the large federation. If the PTD values of each hydropower station are both closer and smaller, this indicates that the negotiating capabilities of each station under the apportionment scheme are close and all tend to remain in the large consortium, i.e., the scheme is a better-stable, more acceptable apportionment scheme.
TABLE 3 Split tendency value Table for each hydropower station under different apportionment methods
(3) An evaluation index value matrix was constructed, and the evaluation index values of the 4 schemes are shown in table 4, with the power generation amount, the minimum output, and the PTD value, which were increased in proportion to the individual scheduling steps in the different coalition manners, as evaluation indexes.
TABLE 4 evaluation index value Table
(4) Subjective and objective comprehensive weights are determined by expert scoring and entropy weighting, and the results are shown in table 5.
TABLE 5 subjective and objective comprehensive weight table for evaluation index values
(5) Carrying out scheme evaluation through the regret theory, wherein the regret value matrix is as follows:
the regret-euphoria function matrix is:
the perceptual utility matrix is:
the overall perceived utility values for each protocol and the protocol evaluation results are shown in table 6.
Table 6 comprehensive perceptual utility value table for each scheme
Through the above evaluation procedure, the following conclusion is drawn:
(1) the three-apron hydropower station is used as a tap hydropower station to obtain the highest compensation, the compensation obtained by a variation coefficient-shape value method is increased to different degrees relative to the allocation results of other methods, and the temple hydropower station and the transition bay hydropower station also obtain higher compensation benefits than the hydropower station which operates independently and have larger allocation differences. The method fully confirms the role and the value of the tap power station in alliance, has fairness, and also highlights the individual difference of the secondary power station while promoting the downstream power stations at all levels to actively participate in cascade joint scheduling.
(2) The PTD value comparison analysis shows that the variation coefficient-Shapley value method is the most stable and well accepted allocation method, wherein the PTD values of the three-lining-level hydropower station and the temple-level hydropower station are the smallest, the compensation adjustment capability of the three-lining-level hydropower station and the temple-level hydropower station serving as the upstream power station is fully ensured, the PTD value of the transition bay hydropower station is larger, the contribution rate of each hydropower station is fully considered in allocation, and the upstream power station with larger sacrifice of the contribution rate is compensated greatly.
(3) Of the 4 evaluation protocols, protocol M 1 The comprehensive perception utility value of (1) is 0.822, scheme M 2 The comprehensive perception utility value of (1) is 0.832, scheme M 3 Is 0.877, scheme M 4 The comprehensive perception utility value of (1) is 0.948, scheme M 4 Scheme M 3 Scheme M 2 Scheme M 1 , > represents better than scheme M 4 Optimally, scheme M 1 Worst.
Claims (7)
1. The hydropower station compensation allocation scheme evaluation method with the maximum power generation benefit as the target is characterized by comprising the following steps of sequentially executing,
step 1: establishing a hydropower station power generation optimizing and scheduling model, and comparing the generated energy of each hydropower station in different alliance modes;
step 1.1: respectively establishing power generation optimizing and scheduling models by taking the maximum power generation benefit of a single hydropower station or the maximum power generation benefit under different alliance modes as an objective function:
step 1.2: determining constraint equations, including water balance equations, hydropower station water storage capacity constraints, reservoir water level constraints, hydropower station output constraints, reservoir lower drainage flow constraints and flow connection between an upstream hydropower station and a downstream hydropower station;
step 1.3: carrying out power generation dispatching optimization calculation by adopting a dynamic programming method to obtain the power generation amount and the power generation benefit of each hydropower station in different alliance modes;
step 2: performing compensation allocation of the cascade hydropower station by using different compensation allocation methods;
step 3: performing stability evaluation on the compensation allocation result in the step 2;
step 4: establishing an index system, constructing an evaluation index value matrix, and making a compensation allocation scheme of the cascade hydropower station;
the index system comprises an allocation proportion, a step increase power generation amount, a minimum output and a splitting tendency value;
step 5: based on the regret theory, calculating to obtain the optimal compensation allocation scheme according to the evaluation index values of the compensation allocation schemes in the step 4.
2. The hydropower station compensation allocation scheme evaluation method according to claim 1, wherein in step 1.1, the objective function is:
1) The annual power generation benefit of a single hydropower station is the largest:
2) The annual power generation benefit is the largest under different alliance modes:
b is the total power generation benefit of the allied hydropower station in the scheduling period; k is the total number of alliance hydropower stations; i is the hydropower station number, which indicates the ith hydropower station in the cascade; t and T are respectively the time interval numbers and the total time interval numbers of the scheduling periods; a is that i The comprehensive output coefficient of the hydropower station i; q (Q) i,t The flow is quoted for the power generation of the hydropower station i in a period t; h i,t Generating water head for hydropower station i in period t; Δt is the time period length; p is p i The electricity price of the hydropower station i is the internet.
3. The hydropower station compensation allocation scheme evaluation method according to claim 2, wherein in step 2, the different compensation allocation methods include a contribution degree method, a coefficient of variation method, a shape value method, a coefficient of variation-shape value method.
4. The method for evaluating a compensation allocation scheme for a hydropower station according to claim 2, wherein in the step 3, stability evaluation is performed on the compensation allocation result in the step 2, and a split tendency method is adopted.
5. The hydropower station compensation allocation scheme evaluation method according to claim 2, wherein the step 4 further comprises calculating weights of the respective indexes of the index system by using an expert scoring method and an entropy weight method.
6. The method for evaluating a hydropower station compensation allocation scheme according to claim 5, wherein the step 5 comprises the sub-steps of,
step 5.1: constructing an evaluation index value matrix of the compensation allocation scheme and carrying out standardization processing on the evaluation index value matrix;
step 5.2: taking the optimal value of the index evaluation value in the standardized matrix aiming at each index, and establishing an ideal scheme;
step 5.3: constructing a regret value matrix;
step 5.4: constructing a perception utility matrix;
step 5.5: calculating the comprehensive perception utility value of each compensation allocation scheme by combining the weight of each index;
step 5.6: and (5) comparing the comprehensive perception utility values of the compensation allocation schemes, and selecting an optimal compensation allocation scheme.
7. The hydropower station compensation allocation scheme evaluation method according to claim 6, wherein the contribution degree method is characterized in that in the generation benefits of the cascade hydropower station joint optimization scheduling, the higher the efficiency of converting unit hydropower station water into electric energy and then into the generation benefits, the higher the contribution degree to the joint scheduling generation benefits;
the contribution degree method is calculated as follows:
wherein x is i The apportionment proportion of the ith hydropower station; n is the total number of the cascade hydropower stations; p is p i k i The potential energy of the ith hydropower station is converted into a conversion coefficient of generating benefits; k (k) i The power generation efficiency coefficient represents the coefficient of converting potential energy into electric energy; p is p i For the online electricity price, representing the coefficient of converting electric energy into power generation benefit;
the variation coefficient method weights the individual characteristic parameters of the hydropower station according to the variation degree of the observed values of all the individual characteristic parameters to be evaluated, and n hydropower stations are assumed, each hydropower station has m individual characteristic parameters, so that a parameter value matrix X= (X) ij ) n×m The calculation process is as follows:
(1) each parameter value is normalized, and then the parameter value matrix is normalized, so that each parameter value is greater than 0, and in the [0.6,1] range, the forward parameters are as follows:
wherein Y is ij Is the standard value of the characteristic parameter j of the ith hydropower station, Y ij ∈[0.6,1]；X max j 、X min j The maximum and minimum characteristic values of the characteristic parameter j are respectively; x is X ij Elements representing the ith row and jth column of the parameter value matrix X;
(2) calculating the average value and the mean square error of the j-th characteristic parameter value:
means for representing the value of the j-th feature parameter; d (D) j Mean square error representing the j-th feature parameter value;
(3) calculating a variation coefficient of the j-th characteristic parameter value:
(4) calculating the weight value of the j-th characteristic parameter:
(5) calculating the specific gravity of the j characteristic parameter value of the i hydropower station:
(6) calculating the comprehensive weight value of the ith hydropower station:
wherein v i The individual characteristic weight coefficient of the ith hydropower station, namely the apportionment proportion;
the Shapley value method carries out benefit allocation according to the expected value of the marginal cost of the participators so as to ensure the effectiveness and fairness of the allocation, and after the symmetrical axiom, the effective axiom and the additively axiom are satisfied, the Shapley value of each hydropower station has a unique solution:
wherein s is the number of water and power stations in the alliance; n is all possible alliance modes; s is a sub-alliance of N; (s-1) ++! (n-s) ++! /n-! The federation probability for federation S to occur; v (S) -v (S-i) is the marginal contribution value of power station i to alliance S;
combining the advantages of the coefficient of variation method and the Shapley method to provide a coefficient of variation-Shapley method, and obtaining individual characteristic weight coefficients upsilon of each hydropower station according to formulas (4) to (10) i Obtaining a Shapley value sigma of each hydropower station according to a formula (11) i The coefficient of variation-shape method is calculated as follows:
θ i ＝υ i σ i (12)
wherein x is i The apportionment proportion of the ith hydropower station; upsilon (v) i The characteristic weight coefficient of the individual characteristic of the ith hydropower station; sigma (sigma) i Is the Shapley value of the ith hydropower station.
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