Cascade hydropower station group dispatching benefit benchmarking evaluation method considering hydropower station characteristics

Abstract

The invention provides a cascade hydropower station group dispatching benefit benchmarking evaluation method considering hydropower station characteristics, which comprises the following steps: firstly, collecting and sorting basic indexes and benefit indexes related to hydropower station dispatching benefits, so as to formulate a scientific and objective hydropower station dispatching benefit benchmarking evaluation system, and standardizing the indexes in the evaluation system; secondly, the difference of hardware facilities of different hydropower stations is considered, and the benefit index data of different hydropower stations and the drainage basin main body are quantified into strength values according to the complexity theory, so that different evaluation objects can be compared and analyzed in the same dimension; according to the strength value of the benefit index, calculating a combined weight of the benefit index through an entropy weight method and a CRITIC method, and obtaining an index weight considering data disorder and conflict; and finally, solving the scheduling benefit level fitting progress of the different hydropower stations and the drainage basin main body through an improved TOPSIS method, and analyzing the benefit level change conditions of the different hydropower stations and the drainage basin main body from the time dimension.

Description

Technical Field

[0001] The invention belongs to the field of benchmarking and evaluation of hydropower stations, and in particular relates to a benchmarking and evaluation method for dispatching benefits of a cascade hydropower station group taking into account the characteristics of the hydropower stations. Background Art

[0002] Due to factors such as development difficulty and environmental pressure, it is becoming increasingly challenging for hydropower developers to obtain new projects. In order to obtain more profits, hydropower developers are shifting their focus from developing new power plants to meticulous management of existing assets. An effective way to improve management efficiency is to conduct benchmarking assessments. It can identify gaps between different enterprises, discover their weaknesses, and improve and enhance their operational efficiency. However, it is not easy to evaluate directly based on a single or multiple indicators. Because there are significant differences in the distribution areas, social services, operating environment, hydraulic structures, mechanical equipment, and electrical equipment parameters between different hydropower stations. Therefore, how to establish a standardized evaluation system for different hydropower station groups and improve the operational efficiency and management level of hydropower stations is a theoretical and practical problem that needs to be solved urgently. Summary of the invention

[0003] Aiming at the complexity of benchmarking evaluation of the dispatching benefit level of hydropower stations, the present invention first collects and organizes the basic indicators and benefit indicators related to the dispatching benefit of hydropower stations, thereby formulating a scientific and objective benchmarking evaluation system for the dispatching benefit of hydropower stations, and standardizing the indicators in the evaluation system; secondly, considering the differences in hardware facilities of different hydropower stations, the benefit indicator data of different hydropower stations and basin entities are quantified into intensity values ​​according to complexity theory, so that different evaluation objects can be compared and analyzed in the same dimension; again, according to the intensity value of the benefit indicator, the combined weight of the benefit indicator is calculated by the entropy weight method and the CRITIC method, and the indicator weight that takes into account the disorder and conflict of data is obtained; finally, the dispatching benefit level of different hydropower stations and basin entities is obtained by the improved TOPSIS method, and the change of the benefit level of different hydropower stations and basin entities is analyzed from the time dimension. The present invention can identify hydropower stations with low benefits and put forward improvement suggestions, which has certain reference significance for promoting the level of hydropower operation and management in my country.

[0004] In order to realize the above technical features, the object of the present invention is achieved as follows: a method for benchmarking and evaluating the dispatching benefits of a cascade hydropower station group considering the characteristics of the hydropower station comprises the following steps:

[0005] Step 1: Establish a benchmarking and evaluation system for hydropower station dispatching benefits:

[0006] Collect and organize basic indicators and benefit indicators related to the dispatching benefits of hydropower stations, build a benchmarking evaluation system for the dispatching benefits of hydropower stations, and standardize the indicators in the evaluation system;

[0007] Step 2: Quantify the hydropower station dispatching benefit indicators:

[0008] Considering the differences in hardware facilities of different hydropower stations, the benefit index data of hydropower stations and river basin entities are quantified into intensity values ​​through complexity theory;

[0009] Step 3: Determine the combined weight of the hydropower station dispatching benefit indicators:

[0010] According to the strength value of benefit index, the weight of benefit index is calculated by entropy weight method and CRITIC method, and then the combined weight of benefit index is obtained by taking the minimum sum of squares of the weight results of the two methods as the criterion;

[0011] Step 4: Calculate the hydropower station dispatching benefit level and progress:

[0012] The grey correlation method is combined with the Euclidean distance method to improve the distance measurement of the traditional TOPSIS method, and the scheduling benefit level of hydropower stations and river basin entities in different months is calculated.

[0013] The detailed steps of constructing the benchmarking evaluation system for hydropower station dispatching benefits in step 1 are as follows:

[0014] Step 1.1, construct an evaluation index system that can reflect the comprehensive dispatching benefit level of hydropower stations. The index system is divided into two categories, including basic indicators and benefit indicators; basic indicators reflect the differences in hydraulic structures, mechanical equipment and electrical equipment of different hydropower stations, including rated head, rated power generation flow, number of units, regulating reservoir capacity, inflow water, installed capacity and guaranteed output; benefit indicators reflect the dispatching benefit level of hydropower stations according to power generation and water utilization, including water-saving power generation, water energy utilization improvement rate, power generation water consumption rate, power generation, abandoned water power, installed capacity utilization hours, and water utilization rate; among them, the specific data of basic indicators are obtained from the technical parameter table of the hydropower plant, and the specific data of benefit indicators are calculated through the historical dispatching data of the hydropower station. The specific calculation method is as follows:

[0015] ①Power generation:

[0016]

[0017] In the formula, represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the daily average reservoir water level of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η irepresents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h;

[0018] ② Save water and increase power generation:

[0019]

[0020] In the formula, It represents the water-saving and increased power generation of the i-th hydropower station at the t-th time, in 10,000 kW·h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the water level of the assessment reservoir of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h;

[0021] ③Increase rate of water energy utilization:

[0022]

[0023] In the formula, It represents the water energy utilization improvement rate of the ith hydropower station at the tth moment, in %; It represents the water-saving and increased power generation of the i-th hydropower station at the t-th time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the water level of the assessment reservoir of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h;

[0024] ④Water consumption rate for power generation:

[0025]

[0026] Where: It represents the water consumption rate of the i-th hydropower station at the t-th time, in m 3 / kW·h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the average daily power generation flow of the i-th hydropower station, unit: m 3 / s; T represents the calculation period, unit is h;

[0027] ⑤ Abandoned hydropower:

[0028]

[0029] In the formula, It represents the abandoned power of the ith hydropower station at the tth time, in 10,000 kW·h; represents the daily average water discharge of the ith hydropower station, in m 3 / s; It represents the water consumption rate of the i-th hydropower station at the t-th time, in m 3 / kW·h;

[0030] ⑥Installation utilization hours:

[0031]

[0032] Where: It represents the installed capacity utilization hours of the i-th hydropower station at the t-th time, in h; represents the power generation of the ith hydropower station at the tth moment, in 10,000 kW·h; N i represents the installed capacity of the i-th hydropower station, in MW;

[0033] ⑦ Water utilization rate:

[0034]

[0035] In the formula, Indicates water utilization rate, unit: %; represents the daily average inflow of the ith hydropower station, in m 3 / s; represents the daily average water discharge of the ith hydropower station, in m 3 / s;

[0036] Step 1.2: Use the efficacy coefficient method to make the indicators dimensionless and eliminate the impact of differences in units, amplitudes, and trends between indicators on the evaluation results. The efficacy coefficient method is calculated as follows:

[0037] For positive indicators:

[0038]

[0039] In the formula, represents the jth index of the i-th hydropower station at the t-th moment after dimensionless conversion; u j,maxand s represent the maximum and minimum values ​​of the jth index respectively; c and d are constants, c = d = 1, c is used to translate the dimensionless value of the index, and d is used to scale the dimensionless value of the index;

[0040] For contrarian indicators:

[0041]

[0042] In the formula, represents the jth index of the i-th hydropower station at the t-th moment after dimensionless conversion; u j,max and u j,min They represent the maximum and minimum values ​​of the j-th indicator respectively; c and d are constants, c=d=1, the function of c is to translate the dimensionless value of the indicator, and the function of d is to scale the dimensionless value of the indicator.

[0043] The detailed steps for quantifying the hydropower station dispatching benefit index in step 2 are as follows:

[0044] Step 2.1, according to the constructed index system, the basic indicators of rated head, rated power generation flow, number of units, regulating reservoir capacity, water inflow, installed capacity and guaranteed output are used as independent variables, and the benefit indicators of water-saving and increased power generation, water energy utilization improvement rate, power generation water consumption rate, power generation, abandoned water power, installed capacity utilization hours, and water utilization rate are used as dependent variables in turn; first, select the jth benefit index and each basic index to construct a univariate regression equation, the equation is as follows:

[0045] y j =β0+β q s q ,(q=1,2,···,K)(10);

[0046] In the formula, y j represents the jth benefit index; s q represents the qth basic indicator; β0 represents the intercept; β q represents the regression coefficient of the qth basic indicator; K represents the number of basic indicators;

[0047] Step 2.2, calculate the deviation F of the basic indicators in each regression equation, and select the basic indicator with the largest deviation F. max >F 0.05 , then introduce the basic indicator into the model and test the deviation F value of each basic indicator in the model after introducing the indicator. If F q <F 0.1 , then remove the qth basic indicator until there is no indicator that needs to be introduced into the equation and no indicator that needs to be removed from the equation; after screening, the regression equation of the jth benefit indicator and the basic indicator is as follows:

[0048] yj =β0+β1s1+···+β Q s Q (11);

[0049] In the formula, y j represents the jth benefit index; β0 represents the intercept; β Q represents the regression coefficient of the Qth basic indicator; Q represents the number of basic indicators remaining after screening;

[0050] Step 2.3, calculate the weight of each basic indicator according to the size of the basic indicator regression coefficient in the regression equation. The calculation method is as follows:

[0051]

[0052] In the formula, w Q is the weight of the Qth basic indicator; β Q represents the regression coefficient of the Qth basic indicator; β sum represents the sum of the absolute values ​​of the regression coefficients of the basic indicators; Q represents the number of basic indicators remaining after screening;

[0053] Step 2.4, introduce the variance inflation factor to test whether the indicator passes the collinearity test. The calculation method is as follows:

[0054]

[0055] Where V q represents the variance inflation factor of the qth basic indicator; Represents the correlation coefficient between the qth basic index and other basic indexes; when V q ≤10 means that there is no multicollinearity in the qth basic indicator;

[0056] Step 2.5, considering the differences in hardware facilities between different hydropower stations and the temporal and spatial connections between different hydropower stations in the same basin, two types of intensity values ​​are constructed through complexity theory to standardize the benefit indicators of hydropower stations and basin entities. The two types of intensity values ​​are specifically introduced as follows:

[0057] Evaluation of the intensity value of single benefit index of different hydropower stations:

[0058]

[0059] In the formula, represents the intensity value of the jth benefit indicator of the ith hydropower station at the tth moment; represents the value of the jth benefit index of the ith hydropower station at the tth moment; represents the value of the qth basic indicator of the ith hydropower station at the tth moment; w qrepresents the weight of the qth basic indicator; f q It is a univariate function that takes the benefit index as the dependent variable and the basic index as the independent variable. Q represents the number of basic indicators remaining after screening.

[0060] Evaluate the intensity value of single benefit index of different basin entities:

[0061]

[0062] In the formula, It represents the intensity value of the jth benefit index of the gth watershed entity at the tth moment; represents the value of the jth benefit index of the ith hydropower station at the tth moment; represents the value of the qth basic indicator of the ith hydropower station at the tth moment; w q represents the weight of the qth basic indicator; f q It is a univariate function fitted with the benefit index as the dependent variable and the basic index as the independent variable; p represents the total number of hydropower stations in the basin body g; Q represents the number of basic indicators remaining after screening.

[0063] The detailed steps for determining the combined weight of the hydropower station dispatching benefit index in step 3 are as follows:

[0064] Step 3.1, according to the benefit indicator strength value, obtain the amount of useful information carried and transmitted by each benefit indicator, and then use the entropy weight method to obtain the weight of each benefit indicator. The calculation method is as follows:

[0065]

[0066] In the formula, α ej represents the weight of the jth benefit indicator obtained based on the entropy weight method; e j represents the entropy value of the jth benefit indicator; J represents the total number of benefit indicators;

[0067] Step 3.2, according to the benefit indicator strength value, obtain the conflict degree and fluctuation degree of each benefit indicator data, and then use the CRITIC method to obtain the weight of each benefit indicator. The calculation method is as follows:

[0068]

[0069] In the formula, α cj represents the weight of the jth benefit indicator obtained based on the CRITIC method; σ j Indicates the fluctuation degree of the jth benefit indicator; R j Indicates the conflict degree of the jth benefit indicator; S j represents the information content of the jth benefit indicator; J represents the total number of benefit indicators;

[0070] Step 3.3, minimize the heterogeneity of the weight results of the entropy weight method and the CRITIC method, and obtain the combined weight that fully considers the disorder and conflict of the indicator data. The calculation method is as follows:

[0071]

[0072] In the formula, α j represents the combined weight of the jth benefit index; α ej represents the weight of the jth benefit indicator obtained based on the entropy weight method; α cj represents the weight of the jth benefit indicator based on the CRITIC method; J represents the total number of benefit indicators.

[0073] The detailed steps for calculating the hydropower station dispatching benefit level and progress in step 4 are as follows:

[0074] Step 4.1, select J indicators, I hydropower stations or basin entities and T time periods to construct the original evaluation matrix:

[0075]

[0076] In the formula, R represents the original evaluation matrix; represents the intensity value of the jth benefit index of the i-th hydropower enterprise at the t-th time; J represents the number of benefit indexes; I represents the total number of hydropower enterprises; T represents the calculation period;

[0077] Step 4.2: The original evaluation matrix is ​​dimensionless processed to obtain the standardized evaluation matrix R * , the standardized evaluation matrix is ​​combined with the benefit index combination weight to obtain the weighted evaluation matrix, as shown below:

[0078]

[0079] Where Z represents the weighted evaluation matrix; express The value after dimensionless processing; α j represents the weight of the jth benefit indicator; represents the value of the jth benefit index of the i-th hydropower enterprise at the t-th time in the weighted evaluation matrix; J represents the number of benefit indexes; I represents the total number of hydropower enterprises; T represents the calculation period;

[0080] Step 4.3, obtain the positive ideal solution and the negative ideal solution according to the maximum and minimum values ​​corresponding to each indicator in the weighted evaluation matrix:

[0081]

[0082] In the formula, Z + and Z- denote positive ideal solution and negative ideal solution respectively; It represents the value of the jth benefit index of the ith hydropower enterprise at the tth moment in the weighted evaluation matrix; represents the maximum value of the jth benefit index; represents the minimum value of the jth benefit index; J represents the number of benefit indexes;

[0083] Step 4.4, calculate the Euclidean distance and grey relational degree; the calculation method of the Euclidean distance is as follows:

[0084]

[0085] In the formula, and are the Euclidean distances between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment, respectively; represents the value of the jth benefit index of the i-th hydropower enterprise at the t-th moment in the weighted evaluation matrix; represents the maximum value of the jth benefit index; represents the minimum value of the jth benefit index; J represents the number of benefit indexes;

[0086] The calculation method of grey relational degree is as follows:

[0087]

[0088] In the formula, and are the grey correlation between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment; and is the grey correlation coefficient; J represents the number of benefit indicators;

[0089] Step 4.5, construct an improved distance metric through grey relational degree and Euclidean distance, and the calculation method is as follows:

[0090]

[0091] In the formula, and are the new distance measures of the ith hydropower enterprise relative to the positive and negative ideal solutions at the tth moment, respectively; and are the Euclidean distances between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment, respectively; and are the grey correlation between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment; λ is the degree of emphasis on the two distances;

[0092] Step 4.6, calculate the relative progress by using the new distance metric. The larger the relative progress value, the closer the benefit of the evaluation object i at time t is to the positive ideal solution, and the better the benefit at this time. The relative progress is calculated as follows:

[0093]

[0094] Where D i,t It represents the relative progress value of the ith hydropower enterprise at the tth moment; and are the new distance measures of the i-th hydropower enterprise relative to the positive and negative ideal solutions at the t-th moment, respectively.

[0095] Beneficial effects of the present invention:

[0096] 1. Collect and organize the basic indicators and benefit indicators related to the dispatching benefits of hydropower stations, and build a scientific, objective and reasonable benchmarking and evaluation system for the dispatching benefits of hydropower stations to provide a reference for the dispatching work of hydropower stations in my country.

[0097] 2. Considering the differences in hardware facilities of different hydropower stations, the benefit index data of different hydropower stations and river basin entities are quantified into intensity values ​​according to complexity theory, so that different evaluation objects can be compared and analyzed in the same dimension.

[0098] 3. According to the strength value of the benefit indicators, the combined weights of the benefit indicators are calculated by the entropy weight method and the CRITIC method to obtain the indicator weights that take into account the disorder and conflict of the data.

[0099] 4. The improved TOPSIS method is used to obtain the dispatching benefit levels and progress of different hydropower stations and river basin entities, and the changes in the benefit levels of different hydropower stations and river basin entities are analyzed from the time dimension. BRIEF DESCRIPTION OF THE DRAWINGS

[0100] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0101] Figure 1 It is a flow chart for benchmarking and evaluation of dispatching benefits.

[0102] Figure 2 It is a diagram of the dispatching efficiency benchmarking evaluation index system.

[0103] Figure 3 It is a topological diagram of a hydropower station.

[0104] Figure 4 It is the effectiveness test chart of the intensity value of benefit indicators.

[0105] Figure 5 It is the result diagram of the combined weights of benefit indicators.

[0106] Figure 6It is a progress result chart of the dispatching efficiency level of hydropower stations and river basin entities. DETAILED DESCRIPTION

[0107] In order to make the purpose, technical solution and advantages of the present invention more clear, the technical solution in the embodiment of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0108] Embodiment 1:

[0109] like Figure 1-5 As shown in the figure, a benchmarking evaluation method for the dispatching benefit of a cascade hydropower station group considering the characteristics of hydropower stations is proposed. First, the basic indicators and benefit indicators related to the dispatching benefit of hydropower stations are collected and sorted, so as to formulate a scientific and objective benchmarking evaluation system for the dispatching benefit of hydropower stations, and the indicators in the evaluation system are standardized; secondly, considering the differences in hardware facilities of different hydropower stations, the benefit indicator data of different hydropower stations and river basin entities are quantified into intensity values ​​according to the complexity theory, so that different evaluation objects can be compared and analyzed in the same dimension; thirdly, according to the intensity value of the benefit indicator, the combined weight of the benefit indicator is calculated by the entropy weight method and the CRITIC method, and the indicator weight that takes into account the disorder and conflict of data is obtained; finally, the dispatching benefit level of different hydropower stations and river basin entities is obtained by the improved TOPSIS method, and the change of the benefit level of different hydropower stations and river basin entities is analyzed from the time dimension.

[0110] Embodiment 2:

[0111] A method for benchmarking and evaluating the dispatching benefits of a cascade hydropower station group considering the characteristics of the hydropower station comprises the following steps:

[0112] Step 1: Establish a benchmarking and evaluation system for hydropower station dispatching benefits:

[0113] Collect and organize basic indicators and benefit indicators related to the dispatching benefits of hydropower stations, build a benchmarking evaluation system for the dispatching benefits of hydropower stations, and standardize the indicators in the evaluation system;

[0114] Step 2: Quantify the hydropower station dispatching benefit indicators:

[0115] Considering the differences in hardware facilities of different hydropower stations, the benefit index data of hydropower stations and river basin entities are quantified into intensity values ​​through complexity theory;

[0116] Step 3: Determine the combined weight of the hydropower station dispatching benefit indicators:

[0117] According to the strength value of benefit index, the weight of benefit index is calculated by entropy weight method and CRITIC method, and then the combined weight of benefit index is obtained by taking the minimum sum of squares of the weight results of the two methods as the criterion;

[0118] Step 4: Calculate the hydropower station dispatching benefit level and progress:

[0119] The grey correlation method is combined with the Euclidean distance method to improve the distance measurement of the traditional TOPSIS method, and the scheduling benefit level of hydropower stations and river basin entities in different months is calculated.

[0120] Furthermore, the detailed steps of constructing the benchmarking evaluation system for hydropower station dispatching benefits in step 1 are as follows:

[0121] Step 1.1, construct an evaluation index system that can reflect the comprehensive dispatching benefit level of hydropower stations. The index system is divided into two categories, including basic indicators and benefit indicators; basic indicators reflect the differences in hydraulic structures, mechanical equipment and electrical equipment of different hydropower stations, including rated head, rated power generation flow, number of units, regulating reservoir capacity, inflow water, installed capacity and guaranteed output; benefit indicators reflect the dispatching benefit level of hydropower stations according to power generation and water utilization, including water-saving power generation, water energy utilization improvement rate, power generation water consumption rate, power generation, abandoned water power, installed capacity utilization hours, and water utilization rate; among them, the specific data of basic indicators are obtained from the technical parameter table of the hydropower plant, and the specific data of benefit indicators are calculated through the historical dispatching data of the hydropower station. The specific calculation method is as follows:

[0122] ①Power generation:

[0123]

[0124] In the formula, represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the daily average reservoir water level of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h;

[0125] ② Save water and increase power generation:

[0126]

[0127] In the formula, It represents the water-saving and increased power generation of the i-th hydropower station at the t-th time, in 10,000 kW·h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the water level of the assessment reservoir of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h;

[0128] ③Increase rate of water energy utilization:

[0129]

[0130] In the formula, It represents the water energy utilization improvement rate of the ith hydropower station at the tth moment, in %; It represents the water-saving and increased power generation of the i-th hydropower station at the t-th time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the water level of the assessment reservoir of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h;

[0131] ④Water consumption rate for power generation:

[0132]

[0133] Where: It represents the water consumption rate of the i-th hydropower station at the t-th time, in m 3 / kW·h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the average daily power generation flow of the i-th hydropower station, unit: m 3 / s; T represents the calculation period, unit is h;

[0134] ⑤ Abandoned hydropower:

[0135]

[0136] In the formula, It represents the abandoned power of the ith hydropower station at the tth time, in 10,000 kW·h; represents the daily average water discharge of the ith hydropower station, in m 3 / s; It represents the water consumption rate of the i-th hydropower station at the t-th time, in m 3 / kW·h;

[0137] ⑥Installation utilization hours:

[0138]

[0139] Where: It represents the installed capacity utilization hours of the i-th hydropower station at the t-th time, in h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; N i represents the installed capacity of the i-th hydropower station, in MW;

[0140] ⑦ Water utilization rate:

[0141]

[0142] In the formula, Indicates water utilization rate, unit: %; represents the daily average inflow of the ith hydropower station, in m 3 / s; represents the daily average water discharge of the ith hydropower station, in m 3 / s;

[0143] Step 1.2: Use the efficacy coefficient method to make the indicators dimensionless and eliminate the impact of differences in units, amplitudes, and trends between indicators on the evaluation results. The efficacy coefficient method is calculated as follows:

[0144] For positive indicators:

[0145]

[0146] In the formula, represents the jth index of the i-th hydropower station at the t-th moment after dimensionless conversion; u j,max and s represent the maximum and minimum values ​​of the jth index respectively; c and d are constants, c = d = 1, c is used to translate the dimensionless value of the index, and d is used to scale the dimensionless value of the index;

[0147] For contrarian indicators:

[0148]

[0149] In the formula, represents the jth index of the i-th hydropower station at the t-th moment after dimensionless conversion; u j,max and u j,min They represent the maximum and minimum values ​​of the j-th indicator respectively; c and d are constants, c=d=1, the function of c is to translate the dimensionless value of the indicator, and the function of d is to scale the dimensionless value of the indicator.

[0150] Furthermore, the detailed steps for quantifying the hydropower station dispatching benefit index in step 2 are as follows:

[0151] Step 2.1, according to the constructed index system, the basic indicators of rated head, rated power generation flow, number of units, regulating reservoir capacity, water inflow, installed capacity and guaranteed output are used as independent variables, and the benefit indicators of water-saving and increased power generation, water energy utilization improvement rate, power generation water consumption rate, power generation, abandoned water power, installed capacity utilization hours, and water utilization rate are used as dependent variables in turn; first, select the jth benefit index and each basic index to construct a univariate regression equation, the equation is as follows:

[0152] y j =β0+β q s q ,(q=1,2,···,K)(10);

[0153] In the formula, y j represents the jth benefit index; s q represents the qth basic indicator; β0 represents the intercept; β q represents the regression coefficient of the qth basic indicator; K represents the number of basic indicators;

[0154] Step 2.2, calculate the deviation F of the basic indicators in each regression equation, and select the basic indicator with the largest deviation F. max >F 0.05 , then introduce the basic indicator into the model and test the deviation F value of each basic indicator in the model after introducing the indicator. If F q <F 0.1 , then remove the qth basic indicator until there is no indicator that needs to be introduced into the equation and no indicator that needs to be removed from the equation; after screening, the regression equation of the jth benefit indicator and the basic indicator is as follows:

[0155] y j =β0+β1s1+···+β Q s Q (11);

[0156] In the formula, y j represents the jth benefit index; β0 represents the intercept; β Q represents the regression coefficient of the Qth basic indicator; Q represents the number of basic indicators remaining after screening;

[0157] Step 2.3, calculate the weight of each basic indicator according to the size of the basic indicator regression coefficient in the regression equation. The calculation method is as follows:

[0158]

[0159] In the formula, w Q is the weight of the Qth basic indicator; β Q represents the regression coefficient of the Qth basic indicator; β sum represents the sum of the absolute values ​​of the regression coefficients of the basic indicators; Q represents the number of basic indicators remaining after screening;

[0160] Step 2.4, introduce the variance inflation factor to test whether the indicator passes the collinearity test. The calculation method is as follows:

[0161]

[0162] Where V q represents the variance inflation factor of the qth basic indicator; Represents the correlation coefficient between the qth basic index and other basic indexes; when V q ≤10 means that there is no multicollinearity in the qth basic indicator;

[0163] Step 2.5, considering the differences in hardware facilities between different hydropower stations and the temporal and spatial connections between different hydropower stations in the same basin, two types of intensity values ​​are constructed through complexity theory to standardize the benefit indicators of hydropower stations and basin entities. The two types of intensity values ​​are specifically introduced as follows:

[0164] Evaluation of the intensity value of single benefit index of different hydropower stations:

[0165]

[0166] In the formula, represents the intensity value of the jth benefit indicator of the ith hydropower station at the tth moment; represents the value of the jth benefit index of the ith hydropower station at the tth moment; represents the value of the qth basic indicator of the ith hydropower station at the tth moment; w q represents the weight of the qth basic indicator; f q It is a univariate function that takes the benefit index as the dependent variable and the basic index as the independent variable. Q represents the number of basic indicators remaining after screening.

[0167] Evaluate the intensity value of single benefit index of different basin entities:

[0168]

[0169] In the formula, It represents the intensity value of the jth benefit index of the gth watershed entity at the tth moment; represents the value of the jth benefit index of the ith hydropower station at the tth moment; represents the value of the qth basic indicator of the ith hydropower station at the tth moment; w q represents the weight of the qth basic indicator; f q It is a univariate function fitted with the benefit index as the dependent variable and the basic index as the independent variable; p represents the total number of hydropower stations in the basin body g; Q represents the number of basic indicators remaining after screening.

[0170] Furthermore, the detailed steps for determining the combined weight of the hydropower station dispatching benefit index in step 3 are as follows:

[0171] Step 3.1, according to the benefit indicator strength value, obtain the amount of useful information carried and transmitted by each benefit indicator, and then use the entropy weight method to obtain the weight of each benefit indicator. The calculation method is as follows:

[0172]

[0173] In the formula, α ej represents the weight of the jth benefit indicator obtained based on the entropy weight method; e j represents the entropy value of the jth benefit indicator; J represents the total number of benefit indicators;

[0174] Step 3.2, according to the benefit indicator strength value, obtain the conflict degree and fluctuation degree of each benefit indicator data, and then use the CRITIC method to obtain the weight of each benefit indicator. The calculation method is as follows:

[0175]

[0176] In the formula, α cj represents the weight of the jth benefit indicator obtained based on the CRITIC method; σ j Indicates the fluctuation degree of the jth benefit indicator; R j Indicates the conflict degree of the jth benefit indicator; S j represents the information content of the jth benefit indicator; J represents the total number of benefit indicators;

[0177] Step 3.3, minimize the heterogeneity of the weight results of the entropy weight method and the CRITIC method, and obtain the combined weight that fully considers the disorder and conflict of the indicator data. The calculation method is as follows:

[0178]

[0179] In the formula, α j represents the combined weight of the jth benefit index; α ejrepresents the weight of the jth benefit indicator obtained based on the entropy weight method; α cj represents the weight of the jth benefit indicator based on the CRITIC method; J represents the total number of benefit indicators.

[0180] Furthermore, the detailed steps for calculating the hydropower station dispatching benefit level and progress in step 4 are as follows:

[0181] Step 4.1, select J indicators, I hydropower stations or basin entities and T time periods to construct the original evaluation matrix:

[0182]

[0183] In the formula, R represents the original evaluation matrix; represents the intensity value of the jth benefit index of the i-th hydropower enterprise at the t-th time; J represents the number of benefit indexes; I represents the total number of hydropower enterprises; T represents the calculation period;

[0184] Step 4.2: The original evaluation matrix is ​​dimensionless processed to obtain the standardized evaluation matrix R * , the standardized evaluation matrix is ​​combined with the benefit index combination weight to obtain the weighted evaluation matrix, as shown below:

[0185]

[0186] Where Z represents the weighted evaluation matrix; express The value after dimensionless processing; α j represents the weight of the jth benefit indicator; represents the value of the jth benefit index of the i-th hydropower enterprise at the t-th time in the weighted evaluation matrix; J represents the number of benefit indexes; I represents the total number of hydropower enterprises; T represents the calculation period;

[0187] Step 4.3, obtain the positive ideal solution and the negative ideal solution according to the maximum and minimum values ​​corresponding to each indicator in the weighted evaluation matrix:

[0188]

[0189] In the formula, Z + and Z - denote positive ideal solution and negative ideal solution respectively; It represents the value of the jth benefit index of the ith hydropower enterprise at the tth moment in the weighted evaluation matrix; represents the maximum value of the jth benefit index; represents the minimum value of the jth benefit index; J represents the number of benefit indexes;

[0190] Step 4.4, calculate the Euclidean distance and grey relational degree; the calculation method of the Euclidean distance is as follows:

[0191]

[0192] In the formula, and are the Euclidean distances between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment, respectively; represents the value of the jth benefit index of the i-th hydropower enterprise at the t-th moment in the weighted evaluation matrix; represents the maximum value of the jth benefit index; represents the minimum value of the jth benefit index; J represents the number of benefit indexes;

[0193] The calculation method of grey relational degree is as follows:

[0194]

[0195] In the formula, and are the grey correlation between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment; and is the grey correlation coefficient; J represents the number of benefit indicators;

[0196] Step 4.5, construct an improved distance metric through grey relational degree and Euclidean distance, and the calculation method is as follows:

[0197]

[0198] In the formula, and are the new distance measures of the ith hydropower enterprise relative to the positive and negative ideal solutions at the tth moment, respectively; and are the Euclidean distances between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment, respectively; and are the grey correlation between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment; λ is the degree of emphasis on the two distances, which is set to 0.5;

[0199] Step 4.6, calculate the relative progress by using the new distance metric. The larger the relative progress value, the closer the benefit of the evaluation object i at time t is to the positive ideal solution, and the better the benefit at this time. The relative progress is calculated as follows:

[0200]

[0201] Where D i,t It represents the relative progress value of the ith hydropower enterprise at the tth moment; and are the new distance measures of the i-th hydropower enterprise relative to the positive and negative ideal solutions at the t-th moment, respectively.

[0202] Embodiment 3:

[0203] Taking 37 hydropower stations in different river basins of two provinces in southwest my country as the research objects, the dispatching efficiency levels of different hydropower stations and river basin entities in 12 months of a year were analyzed. The topological structure and specific parameters of the hydropower stations were analyzed. Figure 3 As shown in the figure, 37 hydropower stations are distributed in the AF basin, and the hardware facilities of different hydropower stations are quite different.

[0204] Figure 4 The difference between the original data and intensity values ​​of the benefit indicators is shown. It can be seen that compared with the original data, the standard deviation of the intensity value of each benefit indicator has decreased by more than 0.01, indicating that quantifying the benefit indicators into intensity values ​​through complexity theory effectively eliminates the impact of data fluctuations caused by differences in basic indicators of different power stations on the evaluation results. Figure 5 The difference between the combined weight results of benefit indicators and the weight results of the entropy weight method and the CRITIC method is shown. It can be seen that the average value of the difference between the combined weight results and the weight results of the entropy weight method and the CRITIC method is smaller than the difference between the weight results of the entropy weight method and the CRITIC method. In particular, the weights of indicators CHU, HUR and SH are reduced by 0.036, 0.029 and 0.031 respectively, indicating that the combined weight balances the importance of indicators obtained by the entropy weight method and the CRITIC method, and effectively prevents the influence of the extreme weight of a single method on the evaluation results. Figure 6 The changes in the dispatching efficiency levels of different hydropower stations and different river basin entities in 12 months of the year are shown. It can be seen that the efficiency level of the hydropower stations is distributed between 0.387 and 0.619. The median of the efficiency level of the hydropower stations from June to December is generally higher than that from January to May, indicating that the efficiency level of most hydropower stations from June to December is higher than that from January to May. The efficiency level of the No. 14 hydropower station ranks in the top 25% every month, indicating that the efficiency level of the No. 14 hydropower station is higher than that of most hydropower stations. Figure 6 It can also be seen that the benefit level of the main body of the basin is distributed between 0.434 and 0.595. According to the median of the benefit level and progress value, it can be seen that the main body of the basin also shows a pattern in which the benefit level from June to December is higher than that from January to May. Among them, the benefit level of Basin C ranks in the top two in all 12 months, showing a higher level of scheduling benefit.

Claims

1. A benchmarking evaluation method for dispatching benefits of cascade hydropower stations considering the characteristics of hydropower stations, characterized in that: The following steps are involved: Step 1: Establish a benchmarking and evaluation system for hydropower station dispatching benefits: Collect and organize basic indicators and benefit indicators related to the dispatching benefits of hydropower stations, build a benchmarking evaluation system for the dispatching benefits of hydropower stations, and standardize the indicators in the evaluation system; Step 2: Quantify the hydropower station dispatching benefit indicators: Considering the differences in hardware facilities of different hydropower stations, the benefit index data of hydropower stations and river basin entities are quantified into intensity values ​​through complexity theory; Step 3: Determine the combined weight of the hydropower station dispatching benefit indicators: According to the strength value of benefit index, the weight of benefit index is calculated by entropy weight method and CRITIC method, and then the combined weight of benefit index is obtained by taking the minimum sum of squares of the weight results of the two methods as the criterion; Step 4: Calculate the hydropower station dispatching benefit level and progress: The grey correlation method is combined with the Euclidean distance method to improve the distance measurement of the traditional TOPSIS method, and the scheduling benefit level of hydropower stations and river basin entities in different months is calculated.

2. According to claim 1, a method for benchmarking and evaluating the dispatching benefits of a cascade hydropower station group taking into account the characteristics of the hydropower station is characterized in that: The detailed steps of constructing the benchmarking evaluation system for hydropower station dispatching benefits in step 1 are as follows: Step 1.1, construct an evaluation index system that can reflect the comprehensive dispatching benefit level of hydropower stations. The index system is divided into two categories, including basic indicators and benefit indicators; basic indicators reflect the differences in hydraulic structures, mechanical equipment and electrical equipment of different hydropower stations, including rated head, rated power generation flow, number of units, regulating reservoir capacity, inflow water, installed capacity and guaranteed output; benefit indicators reflect the dispatching benefit level of hydropower stations according to power generation and water utilization, including water-saving power generation, water energy utilization improvement rate, power generation water consumption rate, power generation, abandoned water power, installed capacity utilization hours, and water utilization rate; among them, the specific data of basic indicators are obtained from the technical parameter table of the hydropower plant, and the specific data of benefit indicators are calculated through the historical dispatching data of the hydropower station. The specific calculation method is as follows: ①Power generation: In the formula, represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the daily average reservoir water level of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h; ② Save water and increase power generation: In the formula, It represents the water-saving and increased power generation of the i-th hydropower station at the t-th time, in 10,000 kW·h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the water level of the assessment reservoir of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h; ③Increase rate of water energy utilization: In the formula, It represents the water energy utilization improvement rate of the ith hydropower station at the tth moment, in %; It represents the water-saving and increased power generation of the i-th hydropower station at the t-th time, in 10,000 kW·h; Represents the daily average power generation flow of the i-th hydropower station, unit: m 3 / s; represents the water level of the assessment reservoir of the i-th hydropower station, in m; Z i represents the daily average downstream water level of the ith hydropower station, in m; h i represents the head loss of the i-th hydropower station, in m; η i represents the comprehensive efficiency of the i-th hydropower station generator set; T represents the calculation period, unit is h; ④Water consumption rate for power generation: Where: It represents the water consumption rate of the i-th hydropower station at the t-th time, in m 3 / kW·h; represents the power generation of the ith hydropower station at the tth time, in 10,000 kW·h; Represents the average daily power generation flow of the i-th hydropower station, unit: m 3 / s; T represents the calculation period, unit is h; ⑤ Abandoned hydropower: In the formula, It represents the abandoned power of the ith hydropower station at the tth time, in 10,000 kW·h; represents the daily average water discharge of the ith hydropower station, in m 3 / s; It represents the water consumption rate of the i-th hydropower station at the t-th time, in m 3 / kW·h; ⑥Installation utilization hours: Where: It represents the installed capacity utilization hours of the i-th hydropower station at the t-th time, in h; represents the power generation of the ith hydropower station at the tth moment, in 10,000 kW·h; N i represents the installed capacity of the i-th hydropower station, in MW; ⑦Water utilization rate: In the formula, Indicates water utilization rate, unit: %; represents the daily average inflow of the ith hydropower station, in m 3 / s; represents the daily average water discharge of the ith hydropower station, in m 3 / s; Step 1.2: Use the efficacy coefficient method to make the indicators dimensionless and eliminate the impact of differences in units, amplitudes, and trends between indicators on the evaluation results. The efficacy coefficient method is calculated as follows: For positive indicators: In the formula, represents the jth index of the i-th hydropower station at the t-th moment after dimensionless conversion; u j,max and s represent the maximum and minimum values ​​of the jth index respectively; c and d are constants, c = d = 1, c is used to translate the dimensionless value of the index, and d is used to scale the dimensionless value of the index; For contrarian indicators: In the formula, represents the jth index of the i-th hydropower station at the t-th moment after dimensionless conversion; u j,max and u j,min They represent the maximum and minimum values ​​of the j-th indicator respectively; c and d are constants, c=d=1, the function of c is to translate the dimensionless value of the indicator, and the function of d is to scale the dimensionless value of the indicator.

3. According to claim 2, a method for benchmarking and evaluating the dispatching benefits of a cascade hydropower station group taking into account the characteristics of the hydropower station is characterized in that: The detailed steps for quantifying the hydropower station dispatching benefit index in step 2 are as follows: Step 2.1, according to the constructed index system, the basic indicators of rated head, rated power generation flow, number of units, regulating reservoir capacity, water inflow, installed capacity and guaranteed output are used as independent variables, and the benefit indicators of water-saving and increased power generation, water energy utilization improvement rate, power generation water consumption rate, power generation, abandoned water power, installed capacity utilization hours, and water utilization rate are used as dependent variables in turn; first, select the jth benefit index and each basic index to construct a univariate regression equation, the equation is as follows: y j =β0+β q s q ,(q=1,2,···,K)(10); In the formula, y j represents the jth benefit index; s q represents the qth basic indicator; β0 represents the intercept; β q represents the regression coefficient of the qth basic indicator; K represents the number of basic indicators; Step 2.2, calculate the deviation F of the basic indicators in each regression equation, and select the basic indicator with the largest deviation F. max >F 0.05 , then introduce the basic indicator into the model and test the deviation F value of each basic indicator in the model after introducing the indicator. If F q <F 0.1 , then remove the qth basic indicator until there is no indicator that needs to be introduced into the equation and no indicator that needs to be removed from the equation; after screening, the regression equation of the jth benefit indicator and the basic indicator is as follows: y j =β0+β1s1+···+β Q s Q (11); In the formula, y j represents the jth benefit index; β0 represents the intercept; β Q represents the regression coefficient of the Qth basic indicator; Q represents the number of basic indicators remaining after screening; Step 2.3, calculate the weight of each basic indicator according to the size of the basic indicator regression coefficient in the regression equation. The calculation method is as follows: In the formula, w Q is the weight of the Qth basic indicator; β Q represents the regression coefficient of the Qth basic indicator; β sum represents the sum of the absolute values ​​of the regression coefficients of the basic indicators; Q represents the number of basic indicators remaining after screening; Step 2.4, introduce the variance inflation factor to test whether the indicator passes the collinearity test. The calculation method is as follows: Where V q represents the variance inflation factor of the qth basic indicator; Represents the correlation coefficient between the qth basic index and other basic indexes; when V q ≤10 means that there is no multicollinearity in the qth basic indicator; Step 2.5, considering the differences in hardware facilities between different hydropower stations and the temporal and spatial connections between different hydropower stations in the same basin, two types of intensity values ​​are constructed through complexity theory to standardize the benefit indicators of hydropower stations and basin entities. The two types of intensity values ​​are specifically introduced as follows: Evaluation of the intensity value of single benefit index of different hydropower stations: In the formula, represents the intensity value of the jth benefit indicator of the ith hydropower station at the tth moment; represents the value of the jth benefit index of the ith hydropower station at the tth moment; represents the value of the qth basic indicator of the ith hydropower station at the tth moment; w q represents the weight of the qth basic indicator; f q It is a univariate function that takes the benefit index as the dependent variable and the basic index as the independent variable. Q represents the number of basic indicators remaining after screening. Evaluation of the intensity value of single benefit indicators of different basin entities: In the formula, It represents the intensity value of the jth benefit index of the gth watershed entity at the tth moment; represents the value of the jth benefit index of the ith hydropower station at the tth moment; represents the value of the qth basic indicator of the ith hydropower station at the tth moment; w q represents the weight of the qth basic indicator; f q It is a univariate function fitted with the benefit index as the dependent variable and the basic index as the independent variable; p represents the total number of hydropower stations in the basin body g; Q represents the number of basic indicators remaining after screening.

4. According to claim 3, a method for benchmarking and evaluating the dispatching benefits of a cascade hydropower station group considering the characteristics of the hydropower station is characterized in that: The detailed steps for determining the combined weight of the hydropower station dispatching benefit index in step 3 are as follows: Step 3.1, according to the benefit indicator strength value, obtain the amount of useful information carried and transmitted by each benefit indicator, and then use the entropy weight method to obtain the weight of each benefit indicator. The calculation method is as follows: In the formula, α ej represents the weight of the jth benefit indicator obtained based on the entropy weight method; e j represents the entropy value of the jth benefit indicator; J represents the total number of benefit indicators; Step 3.2, according to the benefit indicator strength value, obtain the conflict degree and fluctuation degree of each benefit indicator data, and then use the CRITIC method to obtain the weight of each benefit indicator. The calculation method is as follows: In the formula, α cj represents the weight of the jth benefit indicator obtained based on the CRITIC method; σ j Indicates the fluctuation degree of the jth benefit indicator; R j Indicates the conflict degree of the jth benefit indicator; S j represents the information content of the jth benefit indicator; J represents the total number of benefit indicators; Step 3.3, minimize the heterogeneity of the weight results of the entropy weight method and the CRITIC method, and obtain the combined weight that fully considers the disorder and conflict of the indicator data. The calculation method is as follows: In the formula, α j represents the combined weight of the jth benefit index; α ej represents the weight of the jth benefit indicator obtained based on the entropy weight method; α cj represents the weight of the jth benefit indicator based on the CRITIC method; J represents the total number of benefit indicators.

5. According to claim 4, a method for benchmarking and evaluating the dispatching benefits of a cascade hydropower station group taking into account the characteristics of the hydropower station is characterized in that: The detailed steps for calculating the hydropower station dispatching benefit level and progress in step 4 are as follows: Step 4.1, select J indicators, I hydropower stations or basin entities and T time periods to construct the original evaluation matrix: In the formula, R represents the original evaluation matrix; represents the intensity value of the jth benefit index of the i-th hydropower enterprise at the t-th time; J represents the number of benefit indexes; I represents the total number of hydropower enterprises; T represents the calculation period; Step 4.2: The original evaluation matrix is ​​dimensionless processed to obtain the standardized evaluation matrix R * , the standardized evaluation matrix is ​​combined with the benefit index combination weight to obtain the weighted evaluation matrix, as shown below: Where Z represents the weighted evaluation matrix; express The value after dimensionless processing; α j represents the weight of the jth benefit indicator; represents the value of the jth benefit index of the i-th hydropower enterprise at the t-th time in the weighted evaluation matrix; J represents the number of benefit indexes; I represents the total number of hydropower enterprises; T represents the calculation period; Step 4.3, obtain the positive ideal solution and the negative ideal solution according to the maximum and minimum values ​​corresponding to each indicator in the weighted evaluation matrix: In the formula, Z + and Z - denote positive ideal solution and negative ideal solution respectively; It represents the value of the jth benefit index of the ith hydropower enterprise at the tth moment in the weighted evaluation matrix; represents the maximum value of the jth benefit index; represents the minimum value of the jth benefit index; J represents the number of benefit indexes; Step 4.4, calculate the Euclidean distance and grey relational degree; the calculation method of the Euclidean distance is as follows: In the formula, and are the Euclidean distances between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment, respectively; represents the value of the jth benefit index of the i-th hydropower enterprise at the t-th moment in the weighted evaluation matrix; represents the maximum value of the jth benefit index; represents the minimum value of the jth benefit index; J represents the number of benefit indexes; The calculation method of grey relational degree is as follows: In the formula, and are the grey correlation between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment; and is the grey correlation coefficient; J represents the number of benefit indicators; Step 4.5, construct an improved distance metric through grey relational degree and Euclidean distance, and the calculation method is as follows: In the formula, and are the new distance measures of the ith hydropower enterprise relative to the positive and negative ideal solutions at the tth moment, respectively; and are the Euclidean distances between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment, respectively; and are the grey correlation between the ith hydropower enterprise and the positive and negative ideal solutions at the tth moment; λ is the degree of emphasis on the two distances; Step 4.6, calculate the relative progress by using the new distance metric. The larger the relative progress value, the closer the benefit of the evaluation object i at time t is to the positive ideal solution, and the better the benefit at this time. The relative progress is calculated as follows: Where D i,t It represents the relative progress value of the ith hydropower enterprise at the tth moment; and are the new distance measures of the i-th hydropower enterprise relative to the positive and negative ideal solutions at the t-th moment, respectively.

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