A method for optimizing the evaluation of the complementary capacity allocation of cascade water, wind and solar power in a river basin

Abstract

The present invention relates to the technical field of the capacity planning of complementary power generation of water, wind and light, and relates to a method for optimizing the evaluation of the capacity allocation of cascade water-wind-light complementary in a basin, including: 1) By evaluating the wind and light resource amounts, selecting typical wind and light power station sites, and determining the maximum total exploitable scale of the wind and light resources around the cascade hydropower in the basin; 2) Constructing a mathematical model of the optimal allocation ratio of wind farms and photovoltaic power stations with the objectives of the complementary coefficient of the combined output of wind and light, the source-load matching degree, and the minimum volatility, evaluating the results of each index under different wind-light ratio schemes, and selecting the allocation ratio with strong complementarity, small load deviation and good stability; 3) Constructing a mathematical model for evaluating the capacity allocation ratio and economy of the cascade water-wind-light complementary system in the basin considering the net present value of the whole life cycle of the wind farm and the photovoltaic power station; 4) Solving to obtain the optimal total installed capacity of wind and light. The present invention can better realize the multi-energy complementarity of water, wind and light.

Description

Technical Field

[0001] The present invention belongs to the technical field of water-wind-solar multi-energy complementary power generation capacity planning, and specifically relates to a basin cascade water-wind-solar complementary capacity loading optimization evaluation method. Background Art

[0002] With the continuous growth of the global economy and population, increasingly prominent environmental pollution and energy crisis have become global concerns. Against the background of carbon peak and carbon neutrality, the global energy structure is gradually becoming low-carbon. Renewable energy such as wind and solar can be obtained from nature, continuously used and recycled. Due to their rich and clean characteristics, they are currently the most promising alternative energy sources. However, wind and solar are affected by many natural factors such as wind speed, solar radiation, and temperature. Wind energy and light energy have obvious uneven characteristics in time and space, which makes them have significant randomness, volatility and intermittency. With a high proportion of wind power and photovoltaic grid connection, the anti-peaking nature of wind power indirectly increases the peak-to-valley difference of load, aggravates the peak-shaving burden of the power grid, increases the system operation cost, and poses great challenges to the safe operation of the power grid. At the same time, factors such as limited local power consumption capacity and insufficient external transmission channels make grid connection difficult, so that power systems containing wind power and photovoltaic power often have to abandon wind and light to ensure the smooth and safe operation of the power system. Coordinated operation with power sources with compensating regulation performance makes the combined output stable, providing an effective way to solve this problem. Proper integration of multiple energy sources can improve this phenomenon and achieve smooth total output power fluctuations and energy complementarity. By rationally configuring the capacity ratio of wind power and photovoltaic power stations, the volatility of wind and solar power combined output can be reduced, enabling them to better track load trends and reduce their demand for grid peak load regulation capabilities.

[0003] The ability to quickly adjust storable hydropower energy reduces the impact of fluctuations on the power grid. The combined transmission of water, wind and solar power solves the problem of absorption caused by large-scale grid connection of wind power and photovoltaic power, and solves the randomness, volatility and intermittency of wind and solar energy resources. Therefore, the coordinated operation of multi-energy complementation of water, wind and solar power can utilize the regulation performance of many hydropower stations in the basin, smooth the impact of unstable output of wind and solar power on the power grid, solve the absorption problem of large-scale centralized grid connection and long-distance transmission of wind and solar power, and improve the comprehensive utilization level of clean energy. It is an innovative and exploratory renewable energy development and utilization model. In order to avoid the newly planned wind and solar power stations from following the old path of "difficulty in grid connection and large-scale abandonment of wind and solar power" in the north, it is necessary to study the regulation and storage capacity of cascade hydropower stations in the basin and the optimal scale of wind and solar power station access that the power grid can absorb. At the same time, the study of large-scale wind, solar and water complementarity in the basin has only emerged in recent years. Affected by the uncertainty of regional runoff and the coupling of wind and solar power at multiple time scales, the problem is large in scale, complex in constraints and difficult to solve. There is little research on the optimal configuration of multi-energy complementary capacity of the three clean energy sources of water, wind and solar power considering economics. Summary of the invention

[0004] The present invention provides a method for optimizing the capacity allocation and evaluation of cascade water-wind-solar complementary in a basin to solve the above technical problems. This method can obtain a capacity planning scheme for new wind and solar energy that takes into account the spatio-temporal distribution characteristics of wind and solar resources and the economy of wind and solar power plants, which is of great significance for guiding the orderly development of water-wind-solar integration and improving the comprehensive economic benefits of cascade water-wind-solar multi-energy complementary systems.

[0005] A method for optimizing the capacity allocation and economic evaluation of water-wind-solar complementary in a basin according to the present invention includes the following steps:

[0006] 1) By evaluating the amount of wind and solar resources, select typical wind and solar power plant sites, and determine the maximum total exploitable scale of wind and solar resources around cascade hydropower in the basin;

[0007] 2) Construct a mathematical model for the optimal load ratio of wind farms and photovoltaic power plants with the goals of complementary coefficient of combined wind and solar output, source-load matching degree, and minimum volatility, evaluate the results of each index under different wind-solar ratio schemes, and select a load ratio with strong complementarity, small load deviation, and good stability;

[0008] 3) With the goal of maximizing the net present value of the whole life cycle of the cascade water-wind-solar multi-energy complementary system in the basin, construct a mathematical model for evaluating the capacity allocation ratio and economy of the cascade water-wind-solar complementary system considering the net present value of the whole life cycle of wind farms and photovoltaic power plants;

[0009] 4) Solve to obtain the optimal total installed capacity of wind and solar.

[0010] Preferably, in step 1), it specifically includes the following steps:

[0011] 1.1) Obtain data on the amount of wind and solar resources around cascade hydropower stations in the basin, and divide geographical grids according to the obtained data resolution;

[0012] 1.2) By evaluating the statistical probability distribution of wind speed, average wind power density, wind energy, global horizontal irradiance (GHI), direct normal irradiance (DNI), average sunshine duration, and available hours in each geographical grid, comprehensively evaluate the abundance of wind and solar resources in each geographical grid in the basin;

[0013] 1.3) Combining topography, engineering geology, transportation, and environmental protection, preliminarily select wind and solar power plant sites with conditions for wind and solar resource development;

[0014] 1.4) With the wind and solar power plant sites as constraints, select geographical grids with great potential for wind and solar resource development, and determine the maximum exploitable capacity of wind and solar.

[0015] Preferably, in step 2), the mathematical model for the optimal load ratio of wind farms and photovoltaic power plants is:

[0016]

[0017] Where: β 1 is the complementary coefficient reflecting the change rate of wind power output and photovoltaic power output; β 2 is the cumulative value of the daily deviation; n is the number of hours in a day; are the change rates of wind power output and photovoltaic power output at time t; are the wind power outputs at times t + 1 and t; are the photovoltaic power outputs at times t + 1 and t; is the load requirement at a certain time; is the sum of wind power output and photovoltaic power output at time t; is the total installed capacity of the wind farm and the photovoltaic power station; is the optimal installed capacity of the wind farm and the photovoltaic power station; is the output per unit installed capacity of the wind farm and the photovoltaic power station; μ is the optimal load ratio of the installed capacity of the wind farm; β 3 is the smoothness index, C v,i is the coefficient of variation of the combined wind and solar power output on the i-th day of the whole year, and k is the total number of days in a year; is the average output,

[0018] Preferably, in step 2), by proposing different evaluation index systems for the configuration of wind and solar capacities, and using the AHP-TOPSIS multi-criteria decision-making analysis method modified based on the entropy weight method for evaluation, a reasonable wind-solar capacity ratio is obtained.

[0019] Preferably, in step 3), the specific calculation process of the capacity load ratio and economic evaluation mathematical model of the cascade water-wind-solar complementary system considering the net present value of the whole life cycle of the wind farm and the photovoltaic power station is as follows:

[0020]

[0021] A. Initial investment cost C invest : Considering the geographical location and installed capacity of the wind farm and the photovoltaic power station respectively, analyzing the preliminary work cost, construction engineering cost, equipment purchase cost and other costs required for the design and construction period of the wind-solar power station, and calculating the total investment cost of the multi-energy complementary system. The calculation formula is as follows:

[0022]

[0023] B. Operation and maintenance cost Analyzing the operation and maintenance requirements of the wind-solar power station, and calculating the operation and maintenance cost of the system in the whole life cycle according to the operation life of the power station. The calculation formula is as follows:

[0024]

[0025] C, power generation revenue During the operation of the water-wind-solar system, based on the on-grid electricity price of the wind-solar power station and combined with the power generation of wind-solar-hydro at each time period, calculate the total power generation revenue of the multi-energy complementary system. The calculation formula is as follows:

[0026]

[0027] In the formula: NPV is the net present value of the full life cycle of the wind farm and the photovoltaic power station; C invest is the initial investment cost of the wind farm and the photovoltaic power station; is the power generation benefit of the wind farm and the photovoltaic power station in the y-th year; is the operation and maintenance cost of the wind farm and the photovoltaic power station in the y-th year; Y is the full life cycle years of the wind farm and the photovoltaic power station; J is the total number of time periods; Δt is the time step; r is the social discount rate; is the average output of the wind farm and the photovoltaic power station per unit installed capacity at the j-th time period on the d-th day in the y-th year; is the hydropower output at the j-th time period on the d-th day in the y-th year; are the installed capacities of the wind farm and the photovoltaic power station respectively; are the initial investment costs per unit installed capacity of the wind farm and the photovoltaic power station respectively; are the operation and maintenance costs of the wind farm and the photovoltaic power station respectively; are the land lease costs per unit area of the wind farm and the photovoltaic power station respectively; are the floor areas of the wind farm and the photovoltaic power station per unit installed capacity respectively; is the total installed capacity of the planned wind farm and the photovoltaic power station; is the optimal capacity load ratio of the wind power station; are the on-grid electricity prices of the wind farm and the photovoltaic power station respectively; is the hydropower electricity price; are the average annual power curtailment rates of wind and solar respectively; τ is the salvage rate of the wind farm and the photovoltaic power station; is the total number of days in the y-th year.

[0028] Preferably, in step 3), the model needs to meet the following constraint conditions:

[0029] a. Wind-solar access installed capacity constraint, various hydropower station output constraints:

[0030]

[0031] b. Water volume balance constraint:

[0032]

[0033] c. Flow balance constraint:

[0034]

[0035] d. Reservoir water storage capacity constraint:

[0036]

[0037] e. Reservoir water level constraint:

[0038]

[0039] f. Power generation flow constraint:

[0040]

[0041] g. Total installed capacity constraint of wind and solar

[0042]

[0043] h. Constraints on on-grid electricity prices of wind power and photovoltaic

[0044]

[0045] In the formula: Nm w , Nm pv is the theoretical installed capacity of wind power; is the output of the kth hydropower station in the ith period, are respectively the minimum output and the maximum output of the kth hydropower station in the ith period; are respectively the minimum output and the maximum output of the wind farm in the ith period; are respectively the minimum output and the maximum output of the photovoltaic power station in the ith period; are respectively the minimum and maximum values set for the power generation flow of the kth hydropower station in the ith period, is the average inflow of the kth hydropower station in the ith period, is the water discharge of the kth hydropower station in the ith period, q k,i is the sectional flow from the (k - 1)th hydropower station to the kth hydropower station in the ith period, is the average power generation flow of the kth hydropower station in the ith period; are respectively the minimum and maximum values allowed for the reservoir water storage of the kth hydropower station in the ith period, V k,i is the reservoir water storage of the kth hydropower station at the beginning of the ith period; are respectively the lowest and highest values allowed for the reservoir water level of the kth hydropower station in the ith period, Z k,i is the reservoir water level value of the kth hydropower station at the beginning of the ith period; is the on-grid guiding electricity price of the local photovoltaic power station; It is the on-grid guiding electricity price for the local wind farm.

[0046] Preferably, in step 4), a genetic algorithm is used to solve the mathematical model for the capacity load ratio and economic evaluation of the cascade water-wind-solar complementary system considering the full life cycle net present value of the wind farm and the photovoltaic power station, so as to obtain the optimal total installed capacity of wind and light.

[0047] The method for optimizing the capacity load and economic evaluation of cascade water-wind-solar complementary proposed by the present invention can comprehensively consider factors such as the complementary ability of hydropower, the on-grid electricity price of wind and light, land cost, social discount rate, component cost, etc., and solve for the reasonable installed capacity of various supporting power sources in the sending-end system to achieve multi-energy complementarity of water, wind and light. This method can obtain a capacity planning scheme for new wind and light energy that takes into account the spatio-temporal distribution characteristics of wind and light resources and the economy of wind and light power stations, which is of great significance for guiding the orderly development of water-wind-solar integration and improving the comprehensive economic benefits of the cascade water-wind-solar multi-energy complementary system. Brief Description of the Drawings

[0048] Figure 1 It is a flowchart of a method for optimizing the capacity load and evaluation of cascade water-wind-solar complementary in an embodiment. Detailed Embodiments

[0049] To further understand the content of the present invention, the present invention will be described in detail in combination with the drawings and embodiments. It should be understood that the embodiments are only for explaining the present invention rather than limiting it.

[0050] Embodiment

[0051] As Figure 1 shown, this embodiment provides a method for optimizing the capacity load and evaluation of cascade water-wind-solar complementary, which includes the following steps:

[0052] 1) By evaluating the wind and light resource amounts, select typical wind and light power station sites, and determine the maximum total exploitable scale of wind and light resources around the cascade hydropower;

[0053] 2) Construct a mathematical model for the best load ratio of wind farms and photovoltaic power stations with the goals of the complementary coefficient of wind-light combined output, source-load matching degree, and minimum volatility, evaluate the results of each index under different wind-light ratio schemes, and select a load ratio with strong complementarity, small load deviation, and good stability;

[0054] 3) Construct a mathematical model for the capacity load ratio and economic evaluation of the cascade water-wind-solar complementary system considering the full life cycle net present value of the wind farm and the photovoltaic power station; the model is constrained by the maximum exploitable scale of wind and light, the on-grid electricity price of wind and light, etc., and aims to maximize the full life cycle net present value of the cascade water-wind-solar multi-energy complementary system;

[0055] 4) Solve the model to obtain the optimal total installed capacity of wind and light.

[0056] In step 1), it specifically includes the following steps:

[0057] 1.1) Obtain the data of the wind and light resource amounts around the cascade hydropower stations in the basin, and divide the geographical grid according to the obtained data resolution;

[0058] 1.2) Evaluate indicators such as the statistical probability distribution of wind speed, average wind power density, wind energy, total solar radiation GHI, solar normal direct radiation DNI, average sunshine duration, available hours, etc. within each geographical grid, and comprehensively evaluate the abundance degree of the wind and light resources in each geographical grid within the basin;

[0059] 1.3) Combine the construction conditions such as topography, engineering geology, transportation, environmental protection, etc., and preliminarily select the wind and light power station sites with the conditions for wind and light resource development;

[0060] 1.4) With the wind and light power station sites as constraints, select the geographical grids with great potential for wind and light resource development, and determine the maximum wind and light developable capacity.

[0061] In step 2), the mathematical model of the optimal load ratio of the wind farm and the photovoltaic power station is:

[0062]

[0063] In the formula: β 1 reflects the complementary coefficient of the change rates of wind power output and photovoltaic power output; β 2 is the cumulative value of the daily deviation; n is the number of hours in a day; are the change rates of wind power output and photovoltaic power output at time t; are the wind power outputs at times t + 1 and t; are the photovoltaic power outputs at times t + 1 and t; is the load requirement at time ; is the sum of the wind power output and photovoltaic power output at time t; is the total installed capacity of the wind farm and the photovoltaic power station; is the optimal installed capacity of the wind farm and the photovoltaic power station; is the output per unit installed capacity of the wind farm and the photovoltaic power station; μ is the optimal load ratio of the wind farm installed capacity; β 3 is the smoothness index, C v,i is the coefficient of variation of the combined wind and light power output on the i-th day within a year, and k is the total number of days in a year; is the output mean value,

[0064] In step 2), by proposing different evaluation index systems for wind and light capacity configuration, and using the multi-criteria decision-making analysis method of AHP-TOPSIS modified based on the entropy weight method for evaluation, a reasonable wind and light capacity ratio is obtained.

[0065] The calculation steps of the entropy weight method modified AHP-TOPSIS multi-criteria decision analysis are as follows:

[0066] Step 1: Normalize the original data matrix X of the corresponding evaluation indicators;

[0067] Suppose there are p evaluation objects and q evaluation indicators for a decision-making problem. X ij is an index value in the original evaluation matrix, and the value after its standardization is denoted as X i ' j ;

[0068]

[0069] X max = max(x 1 , x 2 , …, x pj ), X min = min(x 1 x 2 , …, x pj ). When there are negative values in the data, the data is non-negativized;

[0070] Step 2: Calculate the index proportion S. Suppose S ij is the proportion of the value of the i-th scheme under the j-th index in that index;

[0071]

[0072] Step 3: Calculate the difference coefficient h. For the j-th index, the greater the difference in the index value X ij value, the greater the role in the evaluation of the scheme, and the smaller the entropy weight; Suppose h j is the difference coefficient of the j-th index;

[0073]

[0074] In the formula, k > 0; ln is the natural logarithm; the constant k is related to the number of schemes i to be evaluated, and let k = 1 / lni;

[0075] Step 4: Use the difference coefficient to adjust the weights obtained by the AHP method and calculate the index weights ω;

[0076] Step 5: Calculate the positive ideal solution as The negative ideal solution is

[0077] Step 6: Calculate the Euclidean distances of each scheme to the positive and negative ideal solutions as:

[0078] Step 7: Calculate the final evaluation value, and rank each plan according to the evaluation value as

[0079] In step 3), the specific calculation process of the capacity allocation ratio and economic evaluation mathematical model of the basin cascade water-wind-solar complementary system considering the net present value of the whole life cycle of the wind farm and the photovoltaic power station is as follows:

[0080]

[0081] A. Initial investment cost C invest : Considering the geographical location and installed capacity of the wind farm and the photovoltaic power station respectively, analyze the preliminary work cost, construction engineering cost, equipment purchase cost and other costs that need to be invested during the design and construction period of the wind-solar power station, and calculate the total investment cost of the multi-energy complementary system. The calculation formula is as follows:

[0082]

[0083] B. Operation and maintenance cost After the wind power and photovoltaic power stations are built and put into operation, in order to ensure the long-term normal and stable operation of the power stations, necessary maintenance and overhaul are required every year. Analyze the operation and maintenance requirements of the wind-solar power station, and calculate the operation and maintenance cost of the system during the whole life cycle according to the operation life of the power station. The calculation formula is as follows:

[0084]

[0085] C. Power generation income During the operation period of the water-wind-solar system, according to the on-grid electricity price of the wind-solar power station and combined with the power generation of wind-solar hydropower in each time period, calculate the total power generation income of the multi-energy complementary system. The calculation formula is as follows:

[0086]

[0087] In the formula: NPV is the net present value of the whole life cycle of the wind farm and the photovoltaic power station, (yuan); C invest is the initial investment cost of the wind farm and the photovoltaic power station, (yuan); is the power generation benefit of the wind farm and the photovoltaic power station in the yth year, (yuan); is the operation and maintenance cost of the wind farm and the photovoltaic power station in the yth year, (yuan); Y is the whole life cycle years of the wind farm and the photovoltaic power station, calculated as 20 years; J is the total number of time periods; Δt is the time step, (h), Δt = 24; r is the social discount rate; is the average output of the wind farm and the photovoltaic power station with unit installed capacity in the jth time period of the dth day in the yth year, (MW); is the hydropower output in the jth time period of the dth day in the yth year, (MW); The installed capacities of the wind farm and the PV power station, respectively, (MW); The initial investment costs per unit installed capacity of the wind farm and the PV power station, respectively, (yuan / MW); The operation and maintenance costs of the wind farm and the PV power station, respectively, (yuan / MWh); The land lease costs per unit area of the wind farm and the PV power station, respectively, (yuan / m 2 / year); The land occupation areas per unit installed capacity of the wind farm and the PV power station, respectively, (m 2 / MW); The total installed capacities of the planned wind farm and PV power station, (MW); The optimal capacity ratio of the wind farm; The on-grid electricity prices of the wind farm and the PV power station, respectively, (yuan / MWh); The electricity price of the hydropower station, (yuan / MWh); The average annual power curtailment rates of the wind and PV power, with a maximum of 5%; τ is the residual value rate of the wind farm and the PV power station, calculated at 8%; The total number of days in the yth year.

[0088] In step 3), the model needs to satisfy the following constraints:

[0089] a. Constraints on the installed capacities of the wind and PV power access and the output of various hydropower stations:

[0090]

[0091] b. Water volume balance constraint:

[0092]

[0093] c. Flow balance constraint:

[0094]

[0095] d. Reservoir water storage constraint:

[0096]

[0097] e. Reservoir water level constraint:

[0098]

[0099] f. Power generation flow constraint:

[0100]

[0101] g. Total installed capacity constraint of the wind and PV power

[0102]

[0103] h, Feed-in Tariff Constraints for Wind Power and Photovoltaic Power

[0104]

[0105] Where: Nm w and Nm pv are the theoretical installed capacities of wind power; is the output of the k-th hydropower station in the i-th period, are respectively the minimum output and the maximum output of the k-th hydropower station in the i-th period; are respectively the minimum output and the maximum output of the wind farm in the i-th period; are respectively the minimum output and the maximum output of the photovoltaic power station in the i-th period; are respectively the minimum and maximum values set for the power generation flow of the k-th hydropower station in the i-th period, is the average inflow of the k-th hydropower station in the i-th period, is the water discharge of the k-th hydropower station in the i-th period, q k,i is the sectional flow from the (k - 1)-th hydropower station to the k-th hydropower station in the i-th period, is the average power generation flow of the k-th hydropower station in the i-th period; are respectively the minimum and maximum values allowed for the reservoir water storage of the k-th hydropower station in the i-th period, V k,i is the reservoir water storage of the k-th hydropower station at the beginning of the i-th period; are respectively the lowest and highest values allowed for the reservoir water level of the k-th hydropower station in the i-th period, Z k,i is the reservoir water level value of the k-th hydropower station at the beginning of the i-th period; is the feed-in guiding price of the local photovoltaic power station; is the feed-in guiding price of the local wind farm.

[0106] In step 4), a genetic algorithm is used to solve the mathematical model for capacity allocation ratio and economic evaluation of the cascade water-wind-solar complementary system considering the whole life cycle net present value of the wind farm and the photovoltaic power station, and the optimal total installed capacity of wind and solar is obtained.

[0107] A method for cascade water-wind-solar complementary capacity allocation optimization and economic evaluation proposed in this embodiment can comprehensively consider factors such as the complementary ability of hydropower, feed-in tariffs for wind and solar, land cost, social discount rate, and component cost, and solve for the reasonable installed capacities of various supporting power sources in the sending-end system to achieve multi-energy complementarity of water, wind, and solar. This method can obtain a capacity planning scheme for wind and solar new energy that takes into account the spatio-temporal distribution characteristics of wind and solar resources and the economy of wind and solar power stations, which is of great significance for guiding the orderly development of water-wind-solar integration and improving the comprehensive economic benefits of the cascade water-wind-solar multi-energy complementary system.

[0108] The above has schematically described the present invention and its embodiments. This description is not restrictive. What is shown in the drawings is only one of the embodiments of the present invention, and the actual structure is not limited thereto. Therefore, if those of ordinary skill in the art are inspired by it and, without departing from the gist of the present invention, design similar structural modes and embodiments to this technical solution without creative efforts, they shall fall within the protection scope of the present invention.

Claims

1. A method for optimizing the capacity allocation and evaluation of cascade water-wind-solar complementary power generation in a river basin, characterized in that: It includes the following steps: 1) By evaluating the wind and solar energy resources, select typical wind and solar power plant sites, and determine the maximum total exploitable scale of wind and solar energy resources around the cascade hydropower stations in the river basin; 2) Construct a mathematical model of the optimal load ratio of wind farms and photovoltaic power plants with the goals of complementary coefficient of wind-solar combined output, source-load matching degree, and minimum volatility, evaluate the results of each index under different wind-solar ratio schemes, and select a load ratio with strong complementarity, small load deviation, and good stability; 3) With the goal of maximizing the net present value of the whole life cycle of the cascade water-wind-solar multi-energy complementary system in the river basin, construct a mathematical model for evaluating the capacity load ratio and economy of the cascade water-wind-solar complementary system considering the net present value of the whole life cycle of wind farms and photovoltaic power plants; 4) Solve to obtain the optimal total installed capacity of wind and solar energy; In step 1), it specifically includes the following steps: 1.1) Obtain the data of wind and solar energy resources around the cascade hydropower stations in the river basin, and divide the geographical grid according to the obtained data resolution; 1.2) Evaluate the statistical probability distribution of wind speed, average wind power density, wind energy, global horizontal irradiance (GHI), direct normal irradiance (DNI), average sunshine duration, and available hours in each geographical grid, and comprehensively evaluate the abundance of wind and solar energy resources in each geographical grid in the river basin; 1.3) Combining topography, engineering geology, transportation, and environmental protection, preliminarily select the wind and solar power plant sites with the conditions for developing wind and solar energy resources; 1.4) With the wind and solar power plant sites as constraints, select the geographical grids with great potential for developing wind and solar energy resources, and determine the maximum exploitable capacity of wind and solar energy; In step 2), the mathematical model of the optimal load ratio of wind farms and photovoltaic power plants is: where: β 1 is the complementary coefficient reflecting the change rate of wind power output and photovoltaic power output; β 2 is the cumulative value of the intraday deviation; n is the number of hours in a day; are the change rates of wind power output and photovoltaic power output at time t; are the wind power outputs at times t+1 and t; are the photovoltaic power outputs at times t+1 and t; is the load requirement at time ; is the sum of the wind power output and photovoltaic power output at time t; is the total installed capacity of the wind farm and the photovoltaic power station; is the optimal installed capacity of the wind farm and the photovoltaic power station; is the output per unit installed capacity of the wind farm and the photovoltaic power station; μ is the optimal load ratio of the wind farm installed capacity; β 3 is the smoothness index, C v,i is the coefficient of variation of the combined wind and solar power output on the i-th day of the whole year, and k is the total number of days in a year; is the output mean value, 2. A method for optimizing the capacity allocation and evaluation of cascade water-wind-solar complementary power generation in a river basin according to claim 1, characterized in that: In step 2), by proposing different evaluation index systems for wind and solar capacity allocation, use the multi-criteria decision-making analysis method of AHP-TOPSIS corrected by the entropy weight method for evaluation, and obtain a reasonable wind-solar capacity ratio.

3. A method for optimizing the capacity allocation and evaluation of cascade water-wind-solar complementary power generation in a river basin according to claim 2, characterized in that: In step 4), use the genetic algorithm to solve the mathematical model for evaluating the capacity load ratio and economy of the cascade water-wind-solar complementary system considering the net present value of the whole life cycle of wind farms and photovoltaic power plants, and obtain the optimal total installed capacity of wind and solar energy.

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