Water-wind-solar complementary power generation and flood control dispatching optimization method considering water energy storage

Abstract

The invention provides a water-wind-light complementary power generation and flood control scheduling optimization method considering water energy storage, and relates to the field of reservoir optimization scheduling, the method considers a pumped storage power station taking a built reservoir as a lower reservoir or a reversible unit taking the built reservoir as an upper reservoir and a lower reservoir, and constructs a water-wind-light complementary power generation and flood control scheduling optimization model; and solving the water-wind-light complementary power generation and flood control scheduling optimization model by using a reference point-based non-dominated solution sorting genetic algorithm to obtain a three-target Pareto curved surface and a compromise solution, and outputting corresponding water level, flow and power generation process to complete optimization of water-wind-light complementary power generation and flood control scheduling. According to the method, the hydropower dispatching decision problem faced by multi-power-supply cooperative operation and water safety guarantee in a water-energy coupling system under the background that wind-solar new energy high-proportion power generation of a novel electric power system tends to be strong and tends to be frequency of climatic change flood events is solved.

Description

Technical Field

[0001] This invention relates to the field of reservoir optimization scheduling, and in particular to an optimization method for water-wind-solar hybrid power generation and flood control scheduling that considers water storage. Background Technology

[0002] New energy sources such as photovoltaic (PV) and wind power have experienced rapid development, with their installed capacity and power generation accounting for an increasing proportion of the power system year by year. On the other hand, due to the randomness, intermittency, and volatility of PV and wind power output, large-scale grid connection negatively impacts the safe and stable operation of the power system. Therefore, large-scale peak-shaving and energy storage power sources are needed to form multi-energy complementary systems with PV and wind power to promote the consumption of new energy and reduce the curtailment of new energy. Hydropower, with its rapid response, flexible operation, wide output adjustment range, and economical and efficient energy storage, is an ideal energy storage power source in the power system. Typical "water energy storage" methods, such as pumped storage, reversible units, and energy storage pump stations, all use water as a medium, regulating water storage and release through reservoirs and units to play roles in peak shaving, load tracking, and power time shifting. In recent years, climate change, characterized by global warming, and human activities, characterized by urbanization, have intensified, leading to drastic changes in the global water cycle and frequent extreme meteorological and hydrological events such as floods and droughts. Reservoirs, as important water storage and regulation projects on rivers, reduce flood risks in downstream areas by impounding and regulating floods and mitigating peak flows. If torrential rains and floods happen to fall on a reservoir area, exceeding the flood discharge capacity and warning level of the downstream river section, exceeding the capacity of the downstream flood storage area, or even if the reservoir's flood control capacity cannot withstand the flood pressure and threatens the safety of the dam, then pumped-storage power stations can be used to pump water to the corresponding upstream reservoir, or reversible units can be used to pump water to the upstream reservoir to ensure the safety of the dam and downstream flood control.

[0003] Traditional flood control and power generation scheduling utilizes reservoirs to pre-emptively store floodwaters and mitigate peak flows. While ensuring the safety of the reservoir dam itself, it controls downstream discharge based on upstream flood inflow to guarantee flood safety for downstream urban clusters and key flood-protected areas, while maximizing power generation efficiency during the flood season. Against the backdrop of increasingly intense and frequent flood events due to climate change, significant breakthroughs have been achieved in exploring thresholds such as flood season phases, flood control levels, and water storage methods, as well as in establishing flood control scheduling models and multi-objective solution methods. However, under the new demands of high-proportion wind and solar renewable energy generation in new power systems, there is still room for improvement: First, traditional flood control scheduling does not consider the new situation of multi-energy complementarity and the synergy between power and water dispatch objectives; second, the development space for conventional hydropower is limited. To further tap the driving effect of hydropower on wind and solar power, pumped storage power stations and reversible units are the main future development methods for hydropower. New models and methods are needed to fully utilize their flexibility and adjustability to support multi-source coordinated operation and address hydropower scheduling decisions related to flood control safety. Summary of the Invention

[0004] To address the aforementioned shortcomings in existing technologies, this invention provides an optimization method for hydropower, wind, and solar complementary power generation and flood control scheduling that considers water storage. This method solves the hydropower scheduling decision-making problem faced by multi-power source coordinated operation and water security assurance in water-energy coupled systems under the background of high proportion of wind and solar renewable energy generation in new power systems and increasingly frequent and intense flood events due to climate change.

[0005] To achieve the above objectives, the technical solution adopted by this invention is as follows: a method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling that considers water energy storage, comprising the following steps: S1. Consider pumped storage power stations with existing reservoirs as the lower reservoir, or reversible units with existing reservoirs as the upper and lower reservoirs, and construct an optimization model for hydropower, wind and solar power generation and flood control scheduling. S2. The non-dominated solution sorting genetic algorithm based on reference points is used to solve the optimization model of hydro-wind-solar hybrid power generation and flood control scheduling. The three-objective Pareto surface and compromise solution are obtained, and the corresponding water level, flow rate and power generation process are output to complete the optimization of hydro-wind-solar hybrid power generation and flood control scheduling.

[0006] The beneficial effects of this invention are: This invention establishes an optimized method for hydro-wind-solar hybrid power generation and flood control scheduling that considers water energy storage. Compared with previous studies, the main differences of this invention are: First, it considers pumped-storage power stations using existing reservoirs as lower reservoirs, or reversible units using existing reservoirs as upper and lower reservoirs, to fully utilize wind and solar renewable energy curtailment. Water is pumped from the existing lower reservoir to a newly built upper reservoir for energy storage via pumped-storage power stations, or from the existing downstream reservoir to an existing upstream reservoir via reversible units. This utilizes existing conventional hydropower and newly built pumped-storage power stations or reversible units for power generation and peak shaving, fully leveraging the high-quality green electricity absorption role of water projects in "water storage" and "energy storage"; Second, this method... Based on the comprehensive adoption of measures such as "blocking, diverting, storing, delaying, and draining," the newly added pumped storage power stations or reversible units have enabled the reservoir to "pump up" and "discharge down" during the flood season, improving the regulation and flexibility of flood control scheduling of cascade reservoirs and giving full play to the flood control safety role of water projects in "protecting the dam" and "protecting the downstream." Thirdly, it is considered to bundle multiple power sources and transmit power through a unified power transmission channel, using conventional hydropower and pumped storage power stations or reversible units for peak shaving and energy storage, forming a complementary output with photovoltaic and wind power, increasing the utilization rate of photovoltaic and wind power, and ensuring the safe and stable operation of the power system.

[0007] Further, S1 includes the following steps: S101. Considering pumped storage power stations or reversible units, construct a power calculation model for multiple power sources including hydropower, wind power, and solar power. S102, Construct the objective function of the optimization model for hydropower, wind and solar hybrid power generation and flood control scheduling; S103. Constraints for constructing an optimization model for hydropower, wind and solar power generation and flood control scheduling; S104. The upstream and inter-regional water inflow processes and the location information of wind power and photovoltaic power generation during the scheduling period are used as the input of the water-wind-solar complementary power generation and flood control scheduling optimization model, and the output and decision variables of the water-wind-solar complementary power generation and flood control scheduling optimization model are set. S105. Based on the processing of S101-S104, the optimization model for hydropower, wind and solar power generation and flood control scheduling is completed.

[0008] The beneficial effects of the above-mentioned further scheme are: for flood control scheduling during the flood season, a hydro-wind-solar complementary power generation and flood control scheduling model for short-term scale has been constructed, which fully considers the flexible adjustment brought by pumped storage power stations and reversible units, and can achieve multiple objectives such as flood control safety assurance, high-quality wind and solar power consumption, and coordinated operation of multiple power sources.

[0009] Furthermore, the power calculation model for the multiple power sources of water, wind, and solar includes: Conventional hydropower power calculation model: ; ; ; ; ; ; in, This indicates the time period for conventional hydropower. Power generation capacity, Indicates a reservoir index. Indicates the number of reservoirs. This indicates the density of water. Represents gravitational acceleration. Reservoir The power generation efficiency of the power plant , and Reservoirs During the period The discharge flow, power plant power generation flow, and wastewater discharge. , , and Reservoirs The power station during the period The average head, average water level upstream of the dam, average water level downstream of the dam, and average head loss. , , , and These represent the coefficients of the polynomial fitting. Reservoir During the period Average storage capacity and Reservoirs During the period The initial and final storage capacity, , , , and These represent the coefficients of each term fitted using a polynomial; Power calculation model for pumped storage power stations with existing reservoirs as the lower reservoirs: ; ; in, and These represent the time periods of the pumped storage power station. The power generation capacity and pumping capacity, and These represent pumped storage power stations. The power generation efficiency and pumping efficiency, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, Indicates pumped storage power station The upper reservoir during the period The average water level in front of the dam, Indicates pumped storage power station The lower reservoir during the period The average water level in front of the dam, and These represent pumped storage power stations. During the period Average head loss for power generation and pumping; Power calculation model for reversible generating units using existing reservoirs as upper and lower reservoirs: ; ; in, and These represent the time periods of the reversible unit. The power generation capacity and pumping capacity, and These represent reversible units. The power generation efficiency and pumping efficiency, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir During the period The average water level in front of the dam, and These represent reversible units. During the period Average head loss for power generation and pumping; Photovoltaic power generation calculation model: ; in, Indicates the time period of the photovoltaic power station Power generation capacity, Indicates an index of photovoltaic power plants. Indicates the number of photovoltaic power plants. Indicates photovoltaic power station Rated power, Indicates photovoltaic power station During the period The intensity of solar radiation, This represents the intensity of solar radiation under standard test conditions. This represents the temperature-to-power conversion factor of the solar panel. Indicates photovoltaic power station During the period The temperature of the solar panel, This indicates the temperature of the solar panel under standard test conditions. Wind power generation calculation model: ; in, Indicates the time period of the wind power station Power generation capacity, Indicates the index of wind power stations. Indicates the number of wind power stations. Indicates wind power station Rated power, Indicates wind power station During the period The average wind speed at the height of the wind turbine hub. , and They represent wind power stations Wind turbine cut-in, cut-out, and rated wind speed; Model of photovoltaic and wind power generation power composition: ; ; in, and These represent the time periods for photovoltaic and wind power, respectively. Internet power, and These represent the time periods for photovoltaic and wind power, respectively. energy storage capacity, and These represent the time periods for photovoltaic and wind power, respectively. The amount of abandoned electricity.

[0010] The beneficial effects of the aforementioned further scheme are as follows: Firstly, power models for conventional hydropower, pumped storage power stations, reversible turbines, photovoltaic power, and wind power are established separately. In particular, water energy storage is divided into two categories: pumped storage power stations with existing reservoirs as the lower reservoir and reversible turbines with existing reservoirs as both the upper and lower reservoirs. Power models are established separately for each category, taking into account different water level calculation methods. Secondly, addressing the need for high-quality utilization of wind and solar power as different transfer forms of traditional "waste electricity," wind and solar power generation is divided into three parts: grid connection, energy storage, and curtailment.

[0011] Furthermore, the objective function includes: Starting from meeting the power demand of power transmission channels, the optimization objective is to minimize the power supply-demand gap: ; or ; in, Let the objective function be 1. Indicates the total time period. Indicates the power transmission channel during the time period The load demand, This indicates that multiple power sources, including water, wind, and solar energy, are present during different time periods. Total power consumption for internet access This indicates the time period for conventional hydropower. Power generation capacity, and These represent the time periods for photovoltaic and wind power, respectively. Internet power, and These represent the pumped storage power station and the reversible unit during the time period, respectively. The power generation capacity; To ensure the flood control safety of the dam, the optimization goal is to establish the lowest possible water level upstream of the highest dam in the cascade reservoirs. ; ; in, Let objective function 2 be represented. Indicates the number of reservoirs. Reservoir At the highest water level in front of the dam during the study period Reservoir The flood season water level limit Reservoir During the period Average water level in front of the dam; To ensure flood control safety in downstream river sections, the optimization objective is to minimize the maximum outflow from cascade reservoirs. ; ; in, Let the objective function be 3. Reservoir The maximum discharge flow during the study period, Reservoir During the period The outflow rate.

[0012] The beneficial effects of the above-mentioned further scheme are: the three objectives of minimizing the power supply and demand gap, minimizing the highest water level in front of the cascade reservoirs, and minimizing the maximum outflow of the cascade reservoirs can achieve multiple benefits such as flood control safety (protecting the dam and downstream areas), high-quality wind and solar power consumption, and coordinated operation of multiple power sources.

[0013] Furthermore, the constraints include: Conventional hydropower constraints: When the water storage is a pumped storage power station, the water balance constraint is: ; When the water storage is a reversible unit, the water balance constraint is: ; Initial / Terminal Storage Capacity Constraints: ; ; Reservoir capacity constraints: ; Downflow constraint: ; Power generation flow constraints: ; Hydropower station output constraints: ; in, and Reservoirs During the period The initial and final storage capacity, Reservoir During the period Inbound traffic, Reservoir During the period The outflow rate, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, Indicates a long period of time. and Reservoirs during the scheduling period Initial and final storage capacity, Reservoir At the beginning of the scheduling period, the warehouse capacity Reservoir The target reservoir capacity at the end of the scheduling period needs to be determined based on the scheduling period. If the flood occurs in the middle of the flood season, flood control safety is the primary consideration; if the flood occurs at the end of the flood season, both flood control and water supply safety need to be considered. and Reservoirs During the period Minimum and maximum storage capacity, and Reservoirs During the period The discharge flow and the power plant's power generation flow, and Reservoirs During the period The minimum and maximum discharge flow rates, and Reservoirs The power station during the period The minimum and maximum power generation flow rates, For reservoir The power station during the period of effort, and Reservoirs The power station during the period The minimum and maximum output; Constraints of pumped storage power stations or reversible units: Power generation flow constraints: or ; Pumping flow rate constraint: or ; If the power generation and pumping operations of a pumped storage power station / reversible unit do not occur simultaneously, then: or ; Power generation constraints: or ; Pumping power constraints: or ; If the power consumption for pumping in a pumped-storage power station / reversible unit is provided by photovoltaic and wind power, then: or ; in, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and These represent pumped storage power stations. During the period Maximum power generation and pumping flow rate and These represent reversible units. During the period Maximum power generation and pumping flow rate and These represent pumped storage power stations. During the period Power generation and pumping capacity, and These represent reversible units. During the period Power generation and pumping capacity, and These represent pumped storage power stations. During the period Maximum power generation and pumping capacity, and These represent reversible units. During the period Maximum power generation and pumping capacity, and These represent the pumped storage power station and the reversible unit during the time period, respectively. Pumping power, and These represent the time periods for photovoltaic and wind power, respectively. Energy storage capacity; Flood evolution constraints: ; ; in, and Reservoirs Time period The initial and final inbound flow rates , and All indicate reservoir With reservoir Between the river sections The Muskingen evolution parameters, and Reservoirs Time period The initial and final discharge flow rates Indicates river section Time period The inflow rate within the interval.

[0014] The beneficial effects of the above-mentioned further scheme are: considering different forms of water energy storage (one is a pumped storage power station with an existing reservoir as the lower reservoir, and the other is a reversible unit with an existing reservoir as the upper and lower reservoirs), corresponding water balance equations are established respectively, and corresponding constraints are established for the different occurrence of power generation and pumping conditions and the fact that the power consumption of pumping comes from photovoltaic and wind power storage.

[0015] Furthermore, S2 includes the following steps: S201. Initialize the parameters of the reference point-based non-dominated sorting genetic algorithm; S202, Random initialization size is initial population ; S203, Dimensions Based on Target Space Equal fractions on each dimension of the objective ,generate Uniformly distributed inner and outer reference points on the 3D hyperplane; S204. Select real-number encoding to simulate binary crossover, and select polynomial mutation. After crossover and mutation, generate the offspring population. ; S205, Parental population With offspring population Merge into a population ; S206, The merged population Based on the objective function, a fast non-dominated sort is performed to obtain several non-dominated layers with Pareto levels from low to high. S207. Based on the order and reference point of the non-dominated layer, select the population. In Each individual generates a new parent population. ; S208. Determine whether the set number of evolutionary generations has been exceeded. If yes, proceed to S209; otherwise, return to step S204. S209. Obtain the Pareto order and summarize the three-objective Pareto surfaces; S210. Select a compromise solution based on the principle of shortest distance from the origin, and output the water level, flow rate, and power generation process corresponding to the compromise solution.

[0016] The beneficial effects of the above-mentioned further scheme are as follows: the non-dominated solution sorting genetic algorithm based on reference points (NSGA-III algorithm) can solve the reservoir three-objective optimization problem with high quality and efficiency. Its core advantages include: using structured reference points to guide the search, significantly improving the uniformity and breadth of the Pareto front in high-dimensional space, and fully revealing the complex trade-offs between objectives; combining elite strategies and genetic operators to ensure robustness and effectively handle system nonlinearity; outputting a uniformly distributed Pareto solution set to provide rich decision options and recommending compromise solutions, greatly enhancing the scientific nature and flexibility of the scheduling strategy.

[0017] Furthermore, step S203 includes the following steps: A1. Define the dimension of the target space as... ; A2. Dimensions based on the target space Generate a set all Combination of elements ; A3, Based on Combinatorial All outer reference points can be obtained using the following formula: ; ; in, The set of outer reference points represents the first... The first reference point The numerical value of the dimension. Indicate combination The Middle The first combination The value of each element. Indicate combination The Middle The first combination The value of each element. express Take from elements The number of combinations of elements; A4. Based on all outer reference points, the inner reference points are obtained using the following formula. : ; A5. Merge outer reference point sets With inner reference point set ,get The inner and outer reference points are uniformly distributed on the hyperplane.

[0018] The beneficial effects of the above-mentioned further scheme are: the hierarchical reference point design can significantly improve the NSGA-III algorithm's ability to simultaneously capture boundary solutions and trade-off solutions in complex target spaces of three dimensions and above, ensuring that the solution set is reasonably dense and fully covers the Pareto front.

[0019] Furthermore, step S207 includes the following steps: B1. According to the order of the non-dominated layers, put all individuals in the non-dominated layers into the population in sequence. until the critical layer After an individual is introduced into the population The number of individuals is greater than or equal to ; B2. Determining the population Is the number of individuals equal to If it equals, then proceed to B6; if the population... The number of individuals is greater than Enter B3; B3. Generate ideal points, use the ideal points as the origin to transform the objective function, calculate the extreme points and intercepts, and normalize the objective function. B4. Based on the normalized calculation results, the line connecting the origin and the reference point is used as the reference line to calculate the critical layer. The vertical distance from each individual to each reference line is calculated, and each individual is associated with its nearest reference line. B5. Based on the number of reference points associated, in the critical layer Select a number of individuals to add to the population so as to make the population The number of individuals equals ; B6. Setting the Evolutionary Generation for Generate a new parent population .

[0020] The beneficial effects of the above-mentioned further scheme are: ensuring the quality of the solution set through adaptive screening at the critical layer; ensuring the comparability of distances in high-dimensional space based on the accurate normalization of ideal points and intercepts; mapping individuals to the nearest reference direction through the vertical distance association of reference lines; and prioritizing the selection of individuals in sparse directions according to the association density of reference points. Under strict population size constraints, it breaks through the bottleneck of high-dimensional selection pressure imbalance and ensures the uniformity and boundary integrity of the solution set on the Pareto front.

[0021] Furthermore, B3 includes the following steps: C1. Calculate the minimum value in all target directions of the current generation population to generate the ideal point. ,in, , Representing dimension, Indicates the dimension of the target space; C2. Perform objective function transformation to make the objective value of all individuals... Subtract the ideal point from all The value is obtained. ,in, This represents the function after the objective function has been transformed. C3, according to Calculate the extreme points : ; in, This represents the function for calculating extreme points. Indicates the weighting coefficient. Represents the weight coefficients in the b-dimensional space; C4, by The extreme points form a linear hyperplane, from which the intercept is obtained. ; C5. Normalize the objective function using the following formula: ; in, This represents the normalized objective function.

[0022] The beneficial effects of the above-mentioned further scheme are: it constructs a mathematically rigorous normalization framework, provides a reliable basis for reference point association and population selection, and significantly improves the solution set quality of the NSGA-III algorithm in high-dimensional target space.

[0023] Furthermore, B5 includes the following steps: D1. Select the set of reference points with the fewest associated points. If the reference point set If there are multiple reference points, then any set of reference points can be chosen. A reference point and based on this reference point Solve for the critical layer A set of individuals that are related to each other ,like If it is an empty set, then a new reference point is selected; D2, if the critical layer No individual and reference point Correlation, and critical layer There is at least one individual and a reference point. If associated, then the critical layer will be... Center and reference point Individuals with the smallest vertical distance were selected for the population. If the critical layer At least one individual and reference point If associated, then randomly from the critical layer Select one individual to add to the population. ; D3. Repeat steps D1 to D2 until the population... The number of individuals equals until.

[0024] The beneficial effects of the above-mentioned further scheme are: under strict population size constraints, the mechanism simultaneously overcomes the problems of boundary solution loss and central solution aggregation in high-dimensional space, ensuring that the Pareto front maintains geometric integrity and global uniformity under complex morphology. Attached Figure Description

[0025] Figure 1 This is a flowchart of the method of the present invention.

[0026] Figure 2 This is a schematic diagram of a multi-energy complementary system of water, wind and solar power in this embodiment (with an existing reservoir as the lower reservoir of the pumped storage power station).

[0027] Figure 3This is a schematic diagram of a multi-energy complementary system of water, wind and solar power in this embodiment (with the existing reservoir as the upper and lower reservoirs for reversible generator units).

[0028] Figure 4 This is a schematic diagram of water volume evolution and water balance in this embodiment (using the existing reservoir as the lower reservoir of the pumped storage power station).

[0029] Figure 5 This is a schematic diagram of water volume evolution and water volume balance in this embodiment (using the existing reservoir as the upper and lower reversible units).

[0030] Figure 6 This is a flowchart of the NSGA-Ⅲ algorithm in this embodiment.

[0031] Figure 7 This is a schematic diagram of the Pareto surface and compromise solution for the three objectives in this embodiment.

[0032] Figure 8 This is a stacked diagram of the power generation process of the hydro-wind-solar multi-energy system in this embodiment. Detailed Implementation

[0033] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0034] Example This invention takes a system composed of multiple power sources, such as water, wind, and solar, as the research object (e.g. Figure 2 and Figure 3As shown in the figure, its main features are as follows: First, the system includes four main power sources: conventional hydropower (or "cascade hydropower" or "cascade reservoirs"), pumped storage power stations or reversible turbines, photovoltaic power, and wind power; second, pumped storage power stations with existing reservoirs as the lower reservoirs or reversible turbines with existing reservoirs as the upper and lower reservoirs can operate as both pumps and turbines, thereby realizing the "upward pumping" and "downward discharge" of cascade reservoirs, increasing the flexibility of cascade reservoir scheduling; third, multiple power sources can be bundled together. A unified power transmission channel transmits electricity externally, using conventional hydropower and pumped-storage power stations or reversible units for peak shaving and energy storage, complementing photovoltaic and wind power output, increasing the utilization rate of photovoltaic and wind power, and ensuring the safe and stable operation of the power system; fourth, cascade reservoirs and their respective river sections have flood control safety assurance tasks. By combining upstream and inter-regional water inflow forecasts, pumped-storage power stations or reversible units can be used for "upstream pumping" and "downstream discharge," effectively improving the adjustability of flood control scheduling, thereby reducing the flood control pressure on the dam itself and downstream river sections. This invention mainly includes two parts: first, the establishment of an optimization model for hydro-wind-solar complementary power generation and flood control scheduling; second, the solution of the optimization model for hydro-wind-solar complementary power generation and flood control scheduling. Figure 1 As shown, this invention provides an optimization method for hydro-wind-solar hybrid power generation and flood control scheduling that considers water energy storage. The implementation method is as follows: S1. Considering pumped storage power stations with existing reservoirs as the lower reservoir, or reversible generating units with existing reservoirs as the upper and lower reservoirs, construct an optimization model for hydro-wind-solar hybrid power generation and flood control scheduling. The implementation method is as follows: S101. Considering pumped storage power stations or reversible units, construct a power calculation model for multiple power sources including hydropower, wind power, and solar power. In this embodiment, the conventional hydropower calculation model is as follows: ; ; ; ; ; ; in, This indicates the time period for conventional hydropower. Power generation capacity, Indicates a reservoir index. Indicates the number of reservoirs. This indicates the density of water. Represents gravitational acceleration. Reservoir The power generation efficiency of the power plant , and Reservoirs During the period The discharge flow, power plant power generation flow, and wastewater discharge. , , and Reservoirs The power station during the period The average head, average water level upstream of the dam, average water level downstream of the dam, and average head loss. , , , and These represent the coefficients of the polynomial fitting. Reservoir During the period Average storage capacity and Reservoirs During the period The initial and final storage capacity, , , , and These represent the coefficients of the polynomial fitting. In this embodiment, the power calculation model for a pumped storage power station with an existing reservoir as the lower reservoir is as follows: The pumped storage power station operates under two modes: power generation and pumping. The power generation calculation model is as follows: ; The power consumption calculation model for water pumping is as follows: ; in, and These represent the time periods of the pumped storage power station. The power generation capacity and pumping capacity, and These represent pumped storage power stations. The power generation efficiency and pumping efficiency, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, Indicates pumped storage power station The upper reservoir during the period The average water level in front of the dam, Indicates pumped storage power station The lower reservoir during the period Average water level in front of the dam (i.e., the water level of the existing reservoir) The power station during the period (average water level in front of the dam) and These represent pumped storage power stations. During the period The average head loss for power generation and pumping.

[0035] In this embodiment, the power calculation model for the reversible unit is based on the existing reservoir as the upper and lower reservoirs: the reversible unit operates under two modes: power generation and pumping. The power generation calculation model is as follows: ; The power consumption calculation model for water pumping is as follows: ; in, and These represent the time periods of the reversible unit. The power generation capacity and pumping capacity, and These represent reversible units. The power generation efficiency and pumping efficiency, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir During the period The average water level in front of the dam, and These represent reversible units. During the period The average head loss for power generation and pumping.

[0036] In this embodiment, the photovoltaic power generation calculation model is as follows: ; in, Indicates the time period of the photovoltaic power station Power generation capacity, Indicates an index of photovoltaic power plants. Indicates the number of photovoltaic power plants. Indicates photovoltaic power station Rated power, Indicates photovoltaic power station During the period The intensity of solar radiation, This represents the intensity of solar radiation under standard test conditions. This represents the temperature-to-power conversion factor of the solar panel. Indicates photovoltaic power station During the period The temperature of the solar panel, This indicates the temperature of the solar panel under standard test conditions.

[0037] In this embodiment, the wind power generation calculation model is as follows: ; in, Indicates the time period of the wind power station Power generation capacity, Indicates the index of wind power stations. Indicates the number of wind power stations. Indicates wind power station Rated power, Indicates wind power station During the period The average wind speed at the height of the wind turbine hub. , and They represent wind power stations The wind turbine's cut-in, cut-out, and rated wind speed.

[0038] In this embodiment, the power composition model for photovoltaic and wind power generation includes three main components: grid connection, energy storage (providing electricity for pumped storage power stations or reversible turbines), and curtailment. The calculation model is as follows: ; ; in, and These represent the time periods for photovoltaic and wind power, respectively. Internet power, and These represent the time periods for photovoltaic and wind power, respectively. energy storage capacity, and These represent the time periods for photovoltaic and wind power, respectively. The amount of abandoned electricity.

[0039] S102, Construct the objective function of the optimization model for hydropower, wind and solar hybrid power generation and flood control scheduling; In this embodiment, from the perspectives of resource forecasting and regulation capabilities, the time scales of the two major tasks—hydro-wind-solar complementary power generation and flood control scheduling—are well-matched, as reflected in the following: First, under current technological levels, runoff and wind / solar energy have short-term (1-2 week) forecasting capabilities with relatively reliable accuracy; second, hydropower storage (pumped-storage power stations with existing reservoirs as the lower reservoir, or reversible units with existing reservoirs as the upper and lower reservoirs) generally has weekly / daily regulation capabilities; third, hydro-wind-solar complementary power generation planning and operation focus on the complementary characteristics of weekly and daily units; fourth, reservoir flood control scheduling generally focuses on flood events during the flood season, ranging from a few hours to tens of days. Therefore, the duration of each flood event is considered as the scheduling period, and the time step can be determined according to work needs and computing capabilities (e.g., 15 minutes, 1 hour, etc.). Hydro-wind-solar multi-energy system complementary power generation considers one objective: starting from meeting the power demand of the power transmission channel, minimizing the power supply-demand gap is the optimization objective. The reservoir flood control scheduling takes into account two objectives: firstly, to ensure the flood control safety of the dam body, the lowest possible water level in front of the dam is the optimal objective; secondly, to ensure the flood control safety of the downstream river section, the minimum possible maximum discharge flow is the optimal objective.

[0040] In this embodiment, objective 1 is to minimize the power supply-demand gap. ; in: or ; in, Let the objective function be 1. Indicates the total time period. Indicates the power transmission channel during the time period The load demand, This indicates that multiple power sources, including water, wind, and solar energy, are present during different time periods. Total power consumption for internet access This indicates the time period for conventional hydropower. Power generation capacity, and These represent the time periods for photovoltaic and wind power, respectively. Internet power, and These represent the pumped storage power station and the reversible unit during the time period, respectively. Power generation capacity.

[0041] In this embodiment, objective 2: the water level in front of the highest dam is the lowest. ; ; in, Let objective function 2 be represented. Indicates the number of reservoirs. Reservoir At the highest water level in front of the dam during the study period (flood season), Reservoir The flood season water level limit Reservoir The power station during the period Average water level in front of the dam.

[0042] In this embodiment, objective 3 is to minimize the maximum discharge flow rate. ; ; in, Let the objective function be 3. For reservoir The maximum discharge during the study period (flood season), Reservoir During the period The outflow rate.

[0043] S103. Constraints for constructing an optimization model for hydropower, wind and solar power generation and flood control scheduling; In this embodiment, the conventional water and electricity constraints are as follows: When the water storage is a pumped storage power station, the water balance constraint is: ; When the water storage is a reversible unit, the water balance constraint is: ; Initial / Terminal Storage Capacity Constraints: ; ; Reservoir capacity constraints: ; Downflow constraint: ; Power generation flow constraints: ; Hydropower station output constraints: ; in, and Reservoirs During the period The initial and final storage capacity, Reservoir During the period Inbound traffic, Reservoir During the period The outflow rate, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, Indicates a long period of time. and Reservoirs during the scheduling period Initial and final storage capacity, Reservoir At the beginning of the scheduling period (flood season), the reservoir capacity Reservoir The target reservoir capacity at the end of the scheduling period (flood season) is determined based on the specific scheduling period. If the flood season occurs in the middle of the flood season, flood control safety is the primary consideration; if the flood season occurs at the end of the flood season, both flood control and water supply safety must be considered. and Reservoirs During the period Minimum and maximum storage capacity, and Reservoirs During the period The discharge flow and the power plant's power generation flow, and Reservoirs During the period The minimum and maximum discharge flow rates, and Reservoirs The power station during the period The minimum and maximum power generation flow rates, For reservoir The power station during the period of effort, and Reservoirs The power station during the period The minimum and maximum output.

[0044] In this embodiment, the constraints for the pumped storage power station or reversible unit are as follows: Power generation flow constraints: or ; Pumping flow rate constraint: or ; Pumped storage power stations / reversible units cannot operate simultaneously in power generation and pumping modes; therefore: or ; Power generation constraints: or ; Pumping power constraints: or ; The pumping power consumption of pumped storage power stations / reversible units is provided by photovoltaic and wind power, therefore: or ; in, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and These represent pumped storage power stations. During the period Maximum power generation and pumping flow rate and These represent reversible units. During the period Maximum power generation and pumping flow rate and These represent pumped storage power stations. During the period Power generation and pumping capacity, and These represent reversible units. During the period Power generation and pumping capacity, and These represent pumped storage power stations. During the period Maximum power generation and pumping capacity, and These represent reversible units. During the period Maximum power generation and pumping capacity, and These represent the pumped storage power station and the reversible unit during the time period, respectively. Pumping power, and These represent the time periods for photovoltaic and wind power, respectively. Energy storage capacity.

[0045] In this embodiment, the flood evolution constraints are as follows: like Figure 4 and Figure 5 As shown, the Muskingan method is used to calculate the evolution of river floods, starting from the reservoir. The downstream floodwaters flowed through the river section Evolution to downstream reservoirs The flood evolution equation for the inflow section, considering the inflow of floodwater from the interval, is as follows: ; in: ; in, and Reservoirs Time period The initial and final inflows into the reservoir, i.e., the river section Downstream section period Initial and final flow rates, m 3 / s; and Reservoirs Time period The initial and final discharge volumes, i.e., the river section Upstream section time period Initial and final flow rates, m 3 / s; , , For river section The Muskingen evolution parameters; River section Time period The interval inflow rate, m 3 / s.

[0046] S104. The upstream and inter-regional water inflow processes forecasted during the scheduling period, as well as the location information of wind power and photovoltaic power generation, such as air temperature, surface shortwave radiation, and wind speed, are used as inputs to the water-wind-solar complementary power generation and flood control scheduling optimization model. The output and decision variables of the water-wind-solar complementary power generation and flood control scheduling optimization model are set.

[0047] S105. Based on the processing of S101-S104, the optimization model for hydropower, wind and solar power generation and flood control scheduling is completed.

[0048] In this embodiment, the input conditions for the model of hydro-wind-solar hybrid power generation and flood control scheduling optimization model include the upstream and inter-regional water inflow processes predicted during the scheduling period, as well as the air temperature, surface shortwave radiation, and wind speed of the wind power and photovoltaic locations.

[0049] In this embodiment, the decision variables of the hydro-wind-solar hybrid power generation and flood control scheduling optimization model include: Cascade reservoir discharge flow , ; Pumped storage power station pumping flow rate, , ; Pumped storage power station power generation flow rate , ; Reversible unit pumping flow rate , ; Reversible generator power generation flow rate, , .

[0050] S2. The non-dominated solution sorting genetic algorithm based on reference points is used to solve the optimization model of hydro-wind-solar hybrid power generation and flood control scheduling. The three-objective Pareto surface and compromise solution are obtained, and the corresponding water level, flow rate and power generation process are output to complete the optimization of hydro-wind-solar hybrid power generation and flood control scheduling.

[0051] In this embodiment, the non-dominated unordering genetic algorithm type III (NSGA-III) based on reference points is used to optimize the constructed scheduling model (the calculation process is as follows). Figure 6 As shown), the three-objective Pareto surface and compromise solution are obtained (e.g. Figure 7 As shown), and outputs the corresponding power generation (output) process (such as... Figure 8 (As shown).

[0052] The implementation method of S2 is as follows: S201. Initialize the parameters of the reference point-based non-dominated sorting genetic algorithm; In this embodiment, the algorithm parameters are initialized, including the total number of iterations, population size, crossover parameter, mutation parameter, crossover rate, mutation rate, etc., and the initial value of the evolution generation gen is set to 0.

[0053] S202, Random initialization size is initial population (Initial solution set); S203, Dimensions Based on Target Space Equal fractions on each dimension of the objective ,generate The uniform inner and outer reference points on the 3D hyperplane are implemented as follows: A1. Define the dimension of the target space as... ; A2. Dimensions based on the target space Generate a set all Combination of elements ; A3, Based on Combinatorial All outer reference points can be obtained using the following formula: ; ; in, The set of outer reference points represents the first... The first reference point The numerical value of the dimension. Indicate combination The Middle The first combination The value of each element. Indicate combination The Middle The first combination The value of each element. express Take from elements The number of combinations of elements; A4. Based on all outer reference points, the inner reference points are obtained using the following formula. : ; A5. Merge outer reference point sets With inner reference point set ,get Uniformly distributed inner and outer reference points on the 3D hyperplane; In this embodiment, based on the dimension of the target space Equal fractions on each dimension of the objective generate The inner and outer reference points are uniformly distributed on the hyperplane, as follows: ① Define the target dimension as Each target is divided into share, For the set of outer reference points, This is the set of inner reference points; ② Generate a set all Possible combinations of elements ; ③For all ( for The Middle The first combination The value of each element. , ), ; ④ For all and ( for The Middle The first reference point The numerical value of the dimension. , All outer reference points can be obtained; ⑤ Based on the obtained outer reference point, the inner reference point can be obtained. ; ⑥ Merge the outer reference point set With inner reference point set This yields the final set of reference points. .

[0054] S204. Select real-number encoding to simulate binary crossover, and select polynomial mutation. After crossover and mutation, generate the offspring population. ; In this embodiment, the crossover operation is as follows: The crossover algorithm uses real-number encoding to simulate binary crossover for two parent individuals. and Sub-individuals are generated according to the following formula. and : ; ; in: ; in, Indicates the cross parameter; Indicates uniform distribution within the interval Random numbers; This represents the cross-distribution index.

[0055] In this embodiment, the mutation operation is as follows: The mutation algorithm uses polynomial mutation, which is applied to a parent individual. Sub-individuals are generated according to the following formula. : ; in: ; in, Indicates the variation parameter; Indicates uniform distribution within the interval Random numbers; Indicates the distribution index of variation; and These represent the maximum and minimum values ​​of the current target individual, respectively.

[0056] S205, Parental population With offspring population Merge into a population ; S206, The merged population Based on the objective function, a fast non-dominated sort is performed to obtain several non-dominated layers with Pareto levels from low to high. In this embodiment, a offspring population is generated after crossover and mutation operations. ; the parent population (population size is) ) and offspring population (population size is) ) merged into a population (population size is) ); merged population Based on the objective function, a fast non-dominated sort is performed to obtain several non-dominated levels with Pareto ranks from low to high. .

[0057] S207. Based on the order and reference point of the non-dominated layer, select the population. In Each individual generates a new parent population. The implementation method is as follows: B1. According to the order of the non-dominated layers, put all individuals in the non-dominated layers into the population in sequence. until the critical layer After an individual is introduced into the population The number of individuals is greater than or equal to ; B2. Determining the population Is the number of individuals equal to If it equals, then proceed to B6; if the population... The number of individuals is greater than Enter B3; B3. Generate ideal points, use the ideal points as the origin to transform the objective function, calculate the extreme points and intercepts, and normalize the objective function. The implementation method is as follows: C1. Calculate the minimum value in all target directions of the current generation population to generate the ideal point. ,in, , Representing dimension, Indicates the dimension of the target space; C2. Perform objective function transformation to make the objective value of all individuals... Subtract the ideal point from all The value is obtained. ,in, This represents the function after the objective function has been transformed. C3, according to Calculate the extreme points : ; in, This represents the function for calculating extreme points. Indicates the weighting coefficient. Represents the weight coefficients in the b-dimensional space; C4, by The extreme points form a linear hyperplane, from which the intercept is obtained. ; C5. Normalize the objective function using the following formula: ; in, This represents the normalized objective function. B4. Using the line connecting the origin and the reference point as the reference line, calculate the critical layer. The vertical distance from each individual to each reference line is calculated, and each individual is associated with its nearest reference line. B5. Based on the number of reference points associated, in the critical layer Select a number of individuals to add to the population so as to make the population The number of individuals equals The implementation method is as follows: D1. Select the set of reference points with the fewest associated points. If the reference point set If there are multiple reference points, then any set of reference points can be chosen. A reference point and based on this reference point Solve for the critical layer A set of individuals that are related to each other ,like If it is an empty set, then a new reference point is selected; D2, if the critical layer No individual and reference point Correlation, and critical layer There is at least one individual and a reference point. If associated, then the critical layer will be... Center and reference point Individuals with the smallest vertical distance were selected for the population. If the critical layer At least one individual and reference point If associated, then randomly from the critical layer Select one individual to add to the population. ; D3. Repeat steps D1 to D2 until the population... The number of individuals equals until; B6. Setting the Evolutionary Generation for Generate a new parent population ; S208. Determine whether the set number of evolutionary generations has been exceeded. If yes, proceed to S209; otherwise, return to step S204. S209. Obtain the Pareto order and summarize the three-objective Pareto surfaces; S210. Select a compromise solution based on the principle of shortest distance from the origin, and output the water level, flow rate, and power generation process corresponding to the compromise solution.

[0058] In summary, this invention considers an optimization method for hydropower, wind-solar hybrid power generation, and flood control scheduling, taking into account pumped-storage power stations with existing reservoirs as the lower reservoirs or reversible units with existing reservoirs as both upper and lower reservoirs. It establishes a multi-objective optimization scheduling model that ensures flood control safety, high-quality wind and solar power absorption, and coordinated operation of multiple power sources. The method utilizes a non-dominated solution-sorting genetic algorithm type III (NSGA-III) based on reference points for optimization calculations, thereby outputting the scheduling results. This method has significant application value in flexible hydropower scheduling, multi-energy complementarity, power generation, and flood control. First, this method, based on existing cascade reservoirs, involves constructing new pumped-storage power stations or adding reversible turbine units. Since these units can operate as both pumps and turbines, they enable the "upstream pumping" and "downstream discharge" of water from the cascade reservoirs, effectively increasing the regulatory flexibility and controllability of the cascade reservoir scheduling. Second, considering that conventional hydropower, pumped-storage power stations or reversible turbine units, photovoltaic power, and wind power—four main power sources—can be bundled and transmitted through a unified power transmission channel, this method utilizes conventional hydropower and pumped-storage power... The power station or reversible unit can be used for peak shaving and energy storage, complementing photovoltaic and wind power generation, increasing the utilization rate of photovoltaic and wind power, promoting the consumption of clean energy, improving the power generation efficiency of the multi-energy complementary system of hydropower, wind power and photovoltaic power generation, and effectively reducing water and electricity curtailment; thirdly, for cascade reservoirs undertaking flood control tasks, this method can combine upstream and inter-regional water inflow forecasts, and effectively improve the adjustability of flood control scheduling through pumped storage power stations or reversible units to "pump up" and "release downstream", thereby reducing the flood control pressure on the dam itself and the downstream river section. The time step can be determined according to the work needs and computing power (e.g., 15min, 1h, etc.).

[0059] This invention considers pumped-storage power stations with existing reservoirs as the lower reservoir or reversible units with existing reservoirs as upper and lower reservoirs as energy storage facilities for cascade power stations. Those skilled in the art who consider large pumps with existing reservoirs as upper and lower reservoirs as energy storage facilities for cascade power stations are also within the scope of this invention. This invention does not explicitly specify the number of pumped-storage power stations and reversible units; those skilled in the art who consider any number of pumped-storage power stations and reversible units, as well as combinations thereof, are still within the scope of this invention. This invention does not specifically mention flood storage and detention areas; those skilled in the art who consider flood storage and detention areas for flood diversion are still within the scope of this invention. The solution method of this invention uses a non-dominated solution sorting genetic algorithm based on reference points (NSGA-Ⅲ); those skilled in the art who use other multi-objective optimization algorithms (other genetic algorithms, differential evolution algorithms, particle swarm optimization algorithms, ant colony optimization algorithms, cuckoo algorithm, etc.) to solve the problem are still within the scope of this invention. Those skilled in the art who make various other specific modifications and combinations based on these technical teachings disclosed in this invention, without departing from the essence of this invention, are still within the scope of this invention.

Claims

1. A method for optimizing hydro-wind-solar hybrid power generation and flood control dispatch considering water energy storage, characterized in that, Includes the following steps: S1. Consider pumped storage power stations with existing reservoirs as the lower reservoir, or reversible units with existing reservoirs as the upper and lower reservoirs, and construct an optimization model for hydropower, wind and solar power generation and flood control scheduling. S2. The non-dominated solution sorting genetic algorithm based on reference points is used to solve the optimization model of hydro-wind-solar hybrid power generation and flood control scheduling. The three-objective Pareto surface and compromise solution are obtained, and the corresponding water level, flow rate and power generation process are output to complete the optimization of hydro-wind-solar hybrid power generation and flood control scheduling.

2. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water storage as described in claim 1, characterized in that, S1 includes the following steps: S101. Considering pumped storage power stations or reversible units, construct a power calculation model for multiple power sources including hydropower, wind power, and solar power. S102, Construct the objective function of the optimization model for hydropower, wind and solar hybrid power generation and flood control scheduling; S103. Constraints for constructing an optimization model for hydropower, wind and solar power generation and flood control scheduling; S104. The upstream and inter-regional water inflow processes and the location information of wind power and photovoltaic power generation during the scheduling period are used as the input of the water-wind-solar complementary power generation and flood control scheduling optimization model, and the output and decision variables of the water-wind-solar complementary power generation and flood control scheduling optimization model are set. S105. Based on the processing of S101-S104, the optimization model for hydropower, wind and solar power generation and flood control scheduling is completed.

3. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage as described in claim 2, characterized in that, The power calculation model for the various power sources, including water, wind, and solar, includes: Conventional hydropower power calculation model: ； ； ； ； ； ； in, This indicates the time period for conventional hydropower. Power generation capacity, Indicates a reservoir index. Indicates the number of reservoirs. This indicates the density of water. Represents gravitational acceleration. Reservoir The power generation efficiency of the power plant , and Reservoirs During the period The discharge flow, power plant power generation flow, and wastewater discharge. , , and Reservoirs The power station during the period The average head, average water level upstream of the dam, average water level downstream of the dam, and average head loss. , , , and These represent the coefficients of the polynomial fitting. Reservoir During the period Average storage capacity and Reservoirs During the period The initial and final storage capacity, , , , and These represent the coefficients of each term fitted using a polynomial; Power calculation model for pumped storage power stations with existing reservoirs as the lower reservoirs: ； ； in, and These represent the time periods of the pumped storage power station. The power generation capacity and pumping capacity, and These represent pumped storage power stations. The power generation efficiency and pumping efficiency, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, Indicates pumped storage power station The upper reservoir during the period The average water level in front of the dam, Indicates pumped storage power station The lower reservoir during the period The average water level in front of the dam, and These represent pumped storage power stations. During the period Average head loss for power generation and pumping; Power calculation model for reversible generating units using existing reservoirs as upper and lower reservoirs: ； ； in, and These represent the time periods of the reversible unit. The power generation capacity and pumping capacity, and These represent reversible units. The power generation efficiency and pumping efficiency, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir During the period The average water level in front of the dam, and These represent reversible units. During the period Average head loss for power generation and pumping; Photovoltaic power generation calculation model: ； in, Indicates the time period of the photovoltaic power station Power generation capacity, Indicates an index of photovoltaic power plants. Indicates the number of photovoltaic power plants. Indicates photovoltaic power station Rated power, Indicates photovoltaic power station During the period The intensity of solar radiation, This represents the intensity of solar radiation under standard test conditions. This represents the temperature-to-power conversion factor of the solar panel. Indicates photovoltaic power station During the period The temperature of the solar panel, This indicates the temperature of the solar panel under standard test conditions. Wind power generation calculation model: ； in, Indicates the time period of the wind power station Power generation capacity, Indicates the index of wind power stations. Indicates the number of wind power stations. Indicates wind power station Rated power, Indicates wind power station During the period The average wind speed at the height of the wind turbine hub. , and They represent wind power stations Wind turbine cut-in, cut-out, and rated wind speed; Model of photovoltaic and wind power generation power composition: ； ； in, and These represent the time periods for photovoltaic and wind power, respectively. Internet power, and These represent the time periods for photovoltaic and wind power, respectively. energy storage capacity, and These represent the time periods for photovoltaic and wind power, respectively. The amount of abandoned electricity.

4. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage according to claim 2, characterized in that, The objective function includes: Starting from meeting the power demand of power transmission channels, the optimization objective is to minimize the power supply-demand gap: ； or ; in, Let the objective function be 1. Indicates the total time period. Indicates the power transmission channel during the time period The load demand, This indicates that multiple power sources, including water, wind, and solar energy, are present during different time periods. Total power consumption for internet access This indicates the time period for conventional hydropower. Power generation capacity, and These represent the time periods for photovoltaic and wind power, respectively. Internet power, and These represent the pumped storage power station and the reversible unit during the time period, respectively. The power generation capacity; To ensure the flood control safety of the dam, the optimization goal is to establish the lowest possible water level upstream of the highest dam in the cascade reservoirs. ； ； in, Let objective function 2 be represented. Indicates the number of reservoirs. Reservoir At the highest water level in front of the dam during the study period Reservoir The flood season water level limit Reservoir During the period Average water level in front of the dam; To ensure flood control safety in downstream river sections, the optimization objective is to minimize the maximum outflow from cascade reservoirs. ； ； in, Let the objective function be 3. Reservoir The maximum discharge flow during the study period, Reservoir During the period The outflow rate.

5. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage as described in claim 2, characterized in that, The constraints include: Conventional hydropower constraints: When the water storage is a pumped storage power station, the water balance constraint is: ； When the water storage is a reversible unit, the water balance constraint is: ； Initial / Terminal Storage Capacity Constraints: ； ； Reservoir capacity constraints: ； Downflow constraint: ； Power generation flow constraints: ； Hydropower station output constraints: ； in, and Reservoirs During the period The initial and final storage capacity, Reservoir During the period Inbound traffic, Reservoir During the period The outflow rate, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, Indicates a long period of time. and Reservoirs during the scheduling period Initial and final storage capacity, Reservoir At the beginning of the scheduling period, the warehouse capacity Reservoir The target reservoir capacity at the end of the scheduling period needs to be determined based on the scheduling period. If the flood occurs in the middle of the flood season, flood control safety is the primary consideration; if the flood occurs at the end of the flood season, both flood control and water supply safety need to be considered. and Reservoirs During the period Minimum and maximum storage capacity, and Reservoirs During the period The discharge flow and the power plant's power generation flow, and Reservoirs During the period The minimum and maximum discharge flow rates, and Reservoirs The power station during the period The minimum and maximum power generation flow rates, For reservoir The power station during the period of effort, and Reservoirs The power station during the period The minimum and maximum output; Constraints of pumped storage power stations or reversible units: Power generation flow constraints: or ; Pumping flow rate constraint: or ; If the power generation and pumping operations of a pumped storage power station / reversible unit do not occur simultaneously, then: or ; Power generation constraints: or ; Pumping power constraints: or ; If the power consumption for pumping in a pumped-storage power station / reversible unit is provided by photovoltaic and wind power, then: or ; in, and Reservoirs i Pumped storage power station as the lower reservoir i The power generation flow and pumping flow, and Reservoirs With reservoir Reversible units between During the period The power generation flow and pumping flow, and These represent pumped storage power stations. During the period Maximum power generation and pumping flow rate and These represent reversible units. During the period Maximum power generation and pumping flow rate and These represent pumped storage power stations. During the period Power generation and pumping capacity, and These represent reversible units. During the period Power generation and pumping capacity, and These represent pumped storage power stations. During the period Maximum power generation and pumping capacity, and These represent reversible units. During the period Maximum power generation and pumping capacity, and These represent the pumped storage power station and the reversible unit during the time period, respectively. Pumping power, and These represent the time periods for photovoltaic and wind power, respectively. Energy storage capacity; Flood evolution constraints: ； ； in, and Reservoirs Time period The initial and final inbound flow rates , and All indicate reservoir With reservoir Between the river sections The Muskingen evolution parameters, and Reservoirs Time period The initial and final discharge flow rates Indicates river section Time period The inflow rate within the interval.

6. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water storage as described in claim 1, characterized in that, S2 includes the following steps: S201. Initialize the parameters of the reference point-based non-dominated sorting genetic algorithm; S202, Random initialization size is initial population ; S203, Dimensions Based on Target Space Equal fractions on each dimension of the objective ,generate Uniformly distributed inner and outer reference points on the 3D hyperplane; S204. Select real-number encoding to simulate binary crossover, and select polynomial mutation. After crossover and mutation, generate the offspring population. ; S205, Parental population With offspring population Merge into a population ; S206, The merged population Based on the objective function, a fast non-dominated sort is performed to obtain several non-dominated layers with Pareto levels from low to high. S207. Based on the order and reference point of the non-dominated layer, select the population. In Each individual generates a new parent population. ; S208. Determine whether the set number of evolutionary generations has been exceeded. If yes, proceed to S209; otherwise, return to step S204. S209. Obtain the Pareto order and summarize the three-objective Pareto surfaces; S210. Select a compromise solution based on the principle of shortest distance from the origin, and output the water level, flow rate, and power generation process corresponding to the compromise solution.

7. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage according to claim 6, characterized in that, S203 includes the following steps: A1. Define the dimension of the target space as... ; A2. Dimensions based on the target space Generate a set all Combination of elements ; A3, Based on Combinatorial All outer reference points can be obtained using the following formula: ； ； in, The set of outer reference points represents the first... The first reference point The numerical value of the dimension. Indicate combination The Middle The first combination The value of each element. Indicate combination The Middle The first combination The value of each element. express Take from elements The number of combinations of elements; A4. Based on all outer reference points, the inner reference points are obtained using the following formula. : ； A5. Merge outer reference point sets With inner reference point set ,get The inner and outer reference points are uniformly distributed on the hyperplane.

8. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage according to claim 6, characterized in that, S207 includes the following steps: B1. According to the order of the non-dominated layers, put all individuals in the non-dominated layers into the population in sequence. until the critical layer After an individual is introduced into the population The number of individuals is greater than or equal to ; B2. Determining the population Is the number of individuals equal to If it equals, then proceed to B6; if the population... The number of individuals is greater than Enter B3; B3. Generate ideal points, use the ideal points as the origin to transform the objective function, calculate the extreme points and intercepts, and normalize the objective function. B4. Based on the normalized calculation results, the line connecting the origin and the reference point is used as the reference line to calculate the critical layer. The vertical distance from each individual to each reference line is calculated, and each individual is associated with its nearest reference line. B5. Based on the number of reference points associated, in the critical layer Select a number of individuals to add to the population so as to make the population The number of individuals equals ; B6. Setting the Evolutionary Generation for Generate a new parent population .

9. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage according to claim 8, characterized in that, The B3 includes the following steps: C1. Calculate the minimum value in all target directions of the current generation population to generate the ideal point. ,in, , Representing dimension, Indicates the dimension of the target space; C2. Perform objective function transformation to make the objective value of all individuals... Subtract the ideal point from all The value is obtained. ,in, This represents the function after the objective function has been transformed. C3, according to Calculate the extreme points : ； in, This represents the function for calculating extreme points. Indicates the weighting coefficient. Represents the weight coefficients in the b-dimensional space; C4, by The extreme points form a linear hyperplane, from which the intercept is obtained. ; C5. Normalize the objective function using the following formula: ； in, This represents the normalized objective function.

10. The method for optimizing hydro-wind-solar hybrid power generation and flood control scheduling considering water energy storage according to claim 8, characterized in that, The B5 includes the following steps: D1. Select the set of reference points with the fewest associated points. If the reference point set If there are multiple reference points, then any set of reference points can be chosen. A reference point and based on this reference point Solve for the critical layer A set of individuals that are related to each other ,like If it is an empty set, then a new reference point is selected; D2, if the critical layer No individual and reference point Correlation, and critical layer There is at least one individual and a reference point. If associated, then the critical layer will be... Center and reference point Individuals with the smallest vertical distance were selected for the population. If the critical layer At least one individual and reference point If associated, then randomly from the critical layer Select one individual to add to the population. ; D3. Repeat steps D1 to D2 until the population... The number of individuals equals until.

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