A reservoir power generation optimal scheduling method considering spawning protection of four major Chinese carps

Abstract

This invention discloses a reservoir power generation optimization scheduling method that takes into account the spawning protection of the four major Chinese carps, including: 1) establishing a mathematical model of an ecological scheduling mode that takes into account the spawning protection of the four major Chinese carps; 2) establishing a reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps; 3) proposing a dual-state dynamic programming model (DPTS) that couples the optimal state of the scheduling process with the additional state of the scheduling mode; 4) using the proposed dual-state dynamic programming model (DPTS) to solve the reservoir power generation optimization scheduling model established in step 2) to obtain the optimal reservoir power generation scheduling process. This invention addresses the problem of coordinating the power generation scheduling process and the ecological scheduling mode, which cannot be solved by traditional mathematical programming methods or intelligent optimization methods. It proposes a dual-state dynamic programming model (DPTS) optimization modeling method, which can effectively solve the aforementioned mathematical model and obtain the optimal reservoir power generation scheduling process that coordinates the conflict between the ecological scheduling mode that takes into account the spawning protection of the four major Chinese carps and the power generation scheduling process.

Description

Technical Field

[0001] This invention relates to the field of reservoir scheduling technology, specifically, to an optimized scheduling method for reservoir power generation that takes into account the protection of the spawning of the four major freshwater fish species. Background Technology

[0002] The four major freshwater fish species require a continuous flow increase scheduling pattern during their breeding season to stimulate spawning. Optimal reservoir power generation scheduling necessitates a specific scheduling process to maximize power generation. This creates a conflict between the ecological scheduling mode, which aims to protect the spawning of these fish, and the power generation scheduling process. Traditional mathematical programming or intelligent optimization methods cannot solve this problem of co-optimizing the scheduling process and mode. Therefore, there is an urgent need to explore an effective modeling and optimization method to achieve optimal reservoir power generation scheduling modeling that balances spawning protection with the co-optimization of the power generation scheduling process and the ecological scheduling mode. Summary of the Invention

[0003] The purpose of this invention is to address the shortcomings of existing technologies by proposing a reservoir power generation optimization scheduling method that takes into account the spawning protection of the four major Chinese carps. By proposing a dual-state dynamic programming (DPTS) optimization modeling method that couples the optimized state of the power generation scheduling process with the additional state of the ecological scheduling mode, the problem of coordinated optimization of the power generation scheduling process and the ecological scheduling mode can be effectively solved, thus realizing reservoir power generation optimization scheduling modeling that takes into account the spawning protection of the four major Chinese carps and the coordinated optimization of the power generation scheduling process and the ecological scheduling mode.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] A reservoir power generation optimization scheduling method that takes into account both spawning protection of the four major freshwater fish species includes the following steps:

[0006] Step S1: Establish a mathematical model that takes into account the ecological scheduling mode for the spawning protection of the four major freshwater fish species.

[0007] To stimulate spawning in the four major Chinese freshwater fish species, a continuous flow increase scheduling model is needed during their breeding season, thereby establishing a continuous flow increase mechanism. and duration T S Two key control parameters, determined by the start-up timing t S Existing time window Constraints and flow discharge during startup and discharge flow at the end Existence of flow range constraints and Establish a mathematical model for ecological scheduling that takes into account the spawning protection of the four major freshwater fish species:

[0008]

[0009] Step S2: For the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps, it is required that the scheduling mode that takes into account the ecological protection of the spawning of the four major Chinese carps be executed during the scheduling process. Then, the objective function of the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps is expressed as:

[0010]

[0011] In the above formula, E represents the power generation during the dispatch period; T represents the number of dispatch periods; ΔT t N represents the scheduling time step; t A, H t Q t These are the power output, power output coefficient, head of water used for power generation, and flow rate of the hydropower station.

[0012] Step S3: Propose a dual-state dynamic programming method (DPTS) that combines the optimized state of the coupled scheduling process with the additional state of the scheduling mode.

[0013] Step S3.1: Taking the reservoir capacity as the state and the discharge flow as the decision, establish the state transition equation and recursive basic equation for the reservoir power generation optimization scheduling problem based on traditional dynamic programming:

[0014]

[0015] In the above formula, E t (V t ) represents the cumulative benefit from the initial time period to the current time period t, g t (V t O t () represents the current stage benefit at stage t;

[0016] Step 3.2: For the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major freshwater fish species, design the original state VI. t To optimize the power generation scheduling process, add additional state VII. t To correspond to the ecological scheduling model, establish the recursive basic equations, state transition equations, and optimal decision equations for DPTS that consider both the original state and the additional state:

[0017]

[0018]

[0019] Optimal decision

[0020] Step S4: Use the dual-state dynamic programming DPTS proposed in step S3 to solve the reservoir power generation optimization scheduling model established in step S2 that takes into account the spawning protection of the four major Chinese carp, and obtain the optimal scheduling process of reservoir power generation that takes into account the spawning protection of the four major Chinese carp.

[0021] Step S4.1: First, determine the input and control parameters related to the reservoir power generation optimization scheduling process, including: input water inflow sequence {I t}, Initial control storage capacity V0 and final control storage capacity V during the scheduling period T The relationship between the comprehensive power generation output coefficient A, the relationship between water level and reservoir capacity, and the relationship between the outflow and tailwater level;

[0022] Step S4.2: Then determine the control parameters related to the ecological scheduling mode that takes into account the spawning protection of the four major freshwater fish species, including: flow rate increase. Duration T S Start-up timing t S Time window constraints Discharge flow during startup interval constraints Discharge flow at the end interval constraints

[0023] Step S4.3: Based on the model input and control parameters determined in steps S4.1 and S4.2, establish the reservoir power generation optimization scheduling model described in step S2, which takes into account the spawning protection of the four major freshwater fish species.

[0024] Step S4.4: Taking the reservoir capacity as the state and the discharge flow as the decision, establish the recursive basic equation, state transition equation and optimal decision equation of the dual-state dynamic programming (DPTS) based on traditional dynamic programming.

[0025] Step S4.5: Set the state discretization precision of the dual-state dynamic programming (DPTS). Discretize the reservoir capacity for each time period according to the discretization precision to obtain the state discretization set {{V0},{V1},K,{V1} for each time period. t},K,{V T}};

[0026] Step S4.6: Set the time stage variable of the optimization process as t, and initialize t = 0;

[0027] Step S4.7: For the optimization of the initial state in the power generation dispatching process, based on the recursive basic equation (4a), state transition equation (5a), and optimal decision equation (6a) of DPTS, find the optimal decision O. t And determine the discrete set of states {V} at time t during the state transition process of optimal decision-making. t Each primitive state VI in} t,jThe corresponding discrete set of states at time t-1 {V t-1 The original state VI of} t-1,i .

[0028] Step S4.8: If the time is longer than the time window for the ecological scheduling mode that takes into account the spawning protection of the four major freshwater fish species... The earliest time ( t S If ≤t), then the additional state needs to be included in the calculation.

[0029] For the optimization of additional states in the ecological scheduling model, the optimal decision O is found based on the recursive basic equation (4b), state transition equation (5b), and optimal decision equation (6b) of DPTS. t And determine the discrete set of states {V} at time t during the state transition process of optimal decision-making. t Each additional state VII in} t,j The corresponding discrete set of states at time t-1 {V t-1 Additional state VII of} t-1,i ;

[0030] Step S4.9: If the time falls within the time window that balances the ecological scheduling mode for protecting the spawning of the four major freshwater fish species... Inside Then it is necessary to transform the original state into the additional state;

[0031] To optimize the ecological scheduling mode that balances the spawning protection of the four major freshwater fish species, the process involves finding the optimal state from the initial state of the power generation scheduling process to the additional state of the ecological scheduling mode. Based on the state transition equation (5c) and optimal decision equation (6c) of the DPTS, the discrete set of states at time t {V t Each primitive state VI in} t,i Execute the scheduling mode; then, check whether the operation of the scheduling mode meets the requirements of the outflow rate at startup. interval constraints Discharge flow at the end interval constraints If the above constraints are met, then record the discrete set of states {V} from time t. t The original state VI in} t,i At time t+T S Discrete set of states Additional state The process is an additional state The state transition process for optimal decision-making; if the conditions are not met, skip to the next step and continue calculating the discrete set of states at time t, {V}. t The next primitive state VI in} t,i+1 ;

[0032] Step S4.10, the discrete set of states at time t {V t After each discrete state in} participates in the optimization process of the original state and additional state in steps S4.7 to S4.9, it is determined whether t is greater than T; if t < T, t = t + 1, and jump to step S4.7; if t = T, the optimization process ends, and step S4.11 is executed.

[0033] Step 4.11: Discretize the state set {V} at time T. t The optimal initial state VI for maximizing power generation is selected. T and additional state VII T Then, based on the recursive basic equation (4), state transition equation (5), and optimal decision equation (6) of DPTS, the optimal process for reservoir power generation optimization scheduling at time 0-T is obtained step by step in reverse deduction {VI t} and the optimal process for reservoir power generation scheduling that also considers the protection of the spawning grounds of the four major freshwater fish species {VII} t}

[0034] The beneficial effects of this invention are:

[0035] This invention addresses the problem of co-optimization between power generation scheduling and ecological scheduling modes, which traditional mathematical programming or intelligent optimization methods cannot solve. It proposes a dual-state dynamic programming (DPTS) optimization modeling method that couples the optimized state of the power generation scheduling process with the additional state of the ecological scheduling mode. This method can effectively solve the problem of co-optimization between power generation scheduling and ecological scheduling modes, and realize reservoir power generation optimization scheduling modeling that takes into account the protection of the spawning of the four major freshwater fish species, as well as the co-optimization of power generation scheduling process and ecological scheduling mode. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating an optimized scheduling method for reservoir power generation that takes into account the spawning protection of the four major freshwater fish species, as proposed in this invention. Detailed Implementation

[0037] To enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0038] like Figure 1 As shown, this invention provides a reservoir power generation optimization scheduling method that takes into account both spawning protection of the four major freshwater fish species, including the following steps:

[0039] Step S1: Establish a mathematical model that takes into account the ecological scheduling mode for the spawning protection of the four major freshwater fish species.

[0040] To stimulate spawning in the four major Chinese freshwater fish species, a continuous flow increase scheduling model is needed during their breeding season, thereby establishing a continuous flow increase mechanism. and duration T S Two key control parameters, determined by the start-up timing t S Existing time window Constraints and flow discharge during startup and discharge flow at the end Existence of flow range constraints and Establish a mathematical model for ecological scheduling that takes into account the spawning protection of the four major freshwater fish species:

[0041]

[0042] Step S2: For the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps, it is required that the scheduling mode that takes into account the ecological protection of the spawning of the four major Chinese carps be executed during the scheduling process. Then, the objective function of the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps is expressed as:

[0043]

[0044] In the above formula, E represents the power generation during the dispatch period; T represents the number of dispatch periods; ΔT t N represents the scheduling time step; t A, H t Q t These are the power output, power output coefficient, head of water used for power generation, and flow rate of the hydropower station.

[0045] Step S3: Propose a dual-state dynamic programming method (DPTS) that combines the optimized state of the coupled scheduling process with the additional state of the scheduling mode.

[0046] Step S3.1: Taking the reservoir capacity as the state and the discharge flow as the decision, establish the state transition equation and recursive basic equation for the reservoir power generation optimization scheduling problem based on traditional dynamic programming:

[0047]

[0048] In the above formula, E t (V t ) represents the cumulative benefit from the initial time period to the current time period t, g t (V t O t () represents the current stage benefit at stage t;

[0049] Step 3.2: For the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major freshwater fish species, design the original state VI. tTo optimize the power generation scheduling process, add additional state VII. t To correspond to the ecological scheduling model, establish the recursive basic equations, state transition equations, and optimal decision equations for DPTS that consider both the original state and the additional state:

[0050]

[0051]

[0052] Optimal decision

[0053] Step S4: Use the dual-state dynamic programming DPTS proposed in step S3 to solve the reservoir power generation optimization scheduling model established in step S2 that takes into account the spawning protection of the four major Chinese carp, and obtain the optimal scheduling process of reservoir power generation that takes into account the spawning protection of the four major Chinese carp.

[0054] Step S4.1: First, determine the input and control parameters related to the reservoir power generation optimization scheduling process, including: input water inflow sequence {I t}, Initial control storage capacity V0 and final control storage capacity V during the scheduling period T The relationship between the comprehensive power generation output coefficient A, the relationship between water level and reservoir capacity, and the relationship between the outflow and tailwater level;

[0055] Step S4.2: Then determine the control parameters related to the ecological scheduling mode that takes into account the spawning protection of the four major freshwater fish species, including: flow rate increase. Duration T S Start-up timing t S Time window constraints Discharge flow during startup interval constraints Discharge flow at the end interval constraints

[0056] Step S4.3: Based on the model input and control parameters determined in steps S4.1 and S4.2, establish the reservoir power generation optimization scheduling model described in step S2, which takes into account the spawning protection of the four major freshwater fish species.

[0057] Step S4.4: Taking the reservoir capacity as the state and the discharge flow as the decision, establish the recursive basic equation, state transition equation and optimal decision equation of the dual-state dynamic programming (DPTS) based on traditional dynamic programming.

[0058] Step S4.5: Set the state discretization precision of the dual-state dynamic programming (DPTS). Discretize the reservoir capacity for each time period according to the discretization precision to obtain the state discretization set {{V0},{V1},K,{V1} for each time period. t},K,{V T}};

[0059] Step S4.6: Set the time stage variable of the optimization process as t, and initialize t = 0;

[0060] Step S4.7: For the optimization of the initial state in the power generation dispatching process, based on the recursive basic equation (4a), state transition equation (5a), and optimal decision equation (6a) of DPTS, find the optimal decision O. t And determine the discrete set of states {V} at time t during the state transition process of optimal decision-making. t Each primitive state VI in} t,j The corresponding discrete set of states at time t-1 {V t-1 The original state VI of} t-1,i .

[0061] Step S4.8: If the time is longer than the time window for the ecological scheduling mode that takes into account the spawning protection of the four major freshwater fish species... The earliest time (t) S If ≤t), then the additional state needs to be included in the calculation.

[0062] For the optimization of additional states in the ecological scheduling model, the optimal decision O is found based on the recursive basic equation (4b), state transition equation (5b), and optimal decision equation (6b) of DPTS. t And determine the discrete set of states {V} at time t during the state transition process of optimal decision-making. t Each additional state VII in} t,j The corresponding discrete set of states at time t-1 {V t-1 Additional state VII of} t-1,i ;

[0063] Step S4.9: If the time falls within the time window that balances the ecological scheduling mode for protecting the spawning of the four major freshwater fish species... Inside Then it is necessary to transform the original state into the additional state;

[0064] To optimize the ecological scheduling mode that balances the spawning protection of the four major freshwater fish species, the process involves finding the optimal state from the initial state of the power generation scheduling process to the additional state of the ecological scheduling mode. Based on the state transition equation (5c) and optimal decision equation (6c) of the DPTS, the discrete set of states at time t {V t Each primitive state VI in} t,i Execute the scheduling mode; then, check whether the operation of the scheduling mode meets the requirements of the outflow rate at startup. interval constraints Discharge flow at the end interval constraints If the above constraints are met, then record the discrete set of states {V} from time t.t The original state VI in} t,i At time t+T S Discrete set of states Additional state The process is an additional state The state transition process for optimal decision-making; if the conditions are not met, skip to the next step and continue calculating the discrete set of states at time t, {V}. t The next primitive state VI in} t,i+1 ;

[0065] Step S4.10, the discrete set of states at time t {V t After each discrete state in} participates in the optimization process of the original state and additional state in steps S4.7 to S4.9, it is determined whether t is greater than T; if t < T, t = t + 1, and jump to step S4.7; if t = T, the optimization process ends, and step S4.11 is executed.

[0066] Step 4.11: Discretize the state set {V} at time T. t The optimal initial state VI for maximizing power generation is selected. T and additional state VII T Then, based on the recursive basic equation (4), state transition equation (5), and optimal decision equation (6) of DPTS, the optimal process for reservoir power generation optimization scheduling at time 0-T is obtained step by step in reverse deduction {VI t} and the optimal process for reservoir power generation scheduling that also considers the protection of the spawning grounds of the four major freshwater fish species {VII} t}

[0067] Example 1

[0068] The method of the present invention will be further explained below using a key control reservoir on the main stream of the Yangtze River as an example.

[0069] In an ecological scheduling model that balances the protection of the spawning grounds of the four major freshwater fish species, a flow rate increase is set. and duration T S =3 days, start time t S There is a time window constraint [late May, early June], and the discharge flow will be adjusted upon startup. There is a flow range constraint [8000, 14000]m 3 / s and discharge flow at the end Flow range constraints

[0070] From January 1st of the beginning of the year to June 10th before the flood season, a daily-scale optimal scheduling model for power generation in reservoirs was established, taking into account the spawning protection of the four major freshwater fish species. Its objective function is expressed as:

[0071]

[0072] Using typical high-water years (1933), normal-water years (2007), and low-water years (1982) as the input water, and setting a 3-day rise in flow rate of 1000 m³ / s, the data was analyzed. 3 / s is a scheduling mode that takes into account the spawning protection of the four major freshwater fish species.

[0073] Then, the aforementioned mathematical optimization model is solved using the dual-state dynamic programming method (DPTS) proposed in this invention, which combines the optimized state of the coupled power generation dispatching process with the additional state of the ecological dispatching mode.

[0074] Meanwhile, the classic mathematical programming algorithm Stepwise Optimization (POA) and modern heuristic algorithms such as Differential Evolution (DE), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Continuous Domain Ant Colony Optimization (ACOR) were incorporated for comparison. The calculation results are shown in Table 1 below.

[0075] Table 1. Optimized scheduling results of reservoirs that simultaneously protect the spawning grounds of the four major freshwater fish species under different typical water inflow conditions.

[0076]

[0077] The above comparison results show that, compared with the classic mathematical programming method POA and modern heuristic algorithms DE, GA, PSO, and ACOR, only the DPTS proposed in this invention can solve the problem of co-optimization between power generation scheduling and ecological scheduling mode and find a feasible solution. This demonstrates the scientific nature and superiority of the optimization scheduling method of this invention and provides a solution to the conflict between the ecological scheduling mode that takes into account the protection of the spawning of the four major freshwater fish species and the power generation scheduling process in reservoirs.

[0078] The preferred implementation of the present invention has been described in detail above, but the present invention is not limited to the described embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention, and these equivalent modifications or substitutions are all included within the scope defined by the claims of this application.

Claims

1. A reservoir power generation optimization scheduling method that takes into account both spawning protection of the four major freshwater fish species, characterized in that, Includes the following steps: Step S1: Establish a mathematical model that takes into account the ecological scheduling mode for the spawning protection of the four major freshwater fish species. To stimulate spawning in the four major Chinese freshwater fish species, a continuous flow increase scheduling model is needed during their breeding season, thereby establishing a continuous flow increase mechanism. and duration of days Two key control parameters, determined by the start-up timing Existing time window Constraints and flow discharge during startup and discharge flow at the end Existence of flow range constraints and Establish a mathematical model that takes into account the ecological scheduling mode for the spawning protection of the four major freshwater fish species: ； Step S2: For the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps, it is required that the scheduling mode that takes into account the ecological protection of the spawning of the four major Chinese carps be executed during the scheduling process. Then, the objective function of the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major Chinese carps is expressed as: ； In the above formula, This indicates the amount of electricity generated during the dispatch period; Indicates the number of time periods in the scheduling period; Indicates the scheduling time step; , , , These are the power output, power output coefficient, head of water used for power generation, and flow rate of the hydropower station. Step S3: Propose a dual-state dynamic programming method (DPTS) that combines the optimized state of the coupled scheduling process with the additional state of the scheduling mode. Step S3.1: Taking the reservoir capacity as the state and the discharge flow as the decision, establish the state transition equation and recursive basic equation for the reservoir power generation optimization scheduling problem based on traditional dynamic programming: ； In the above formula, Indicates from the initial period to the present. The cumulative benefits of the stage Indicates the current The phase benefits of a phase; Step 3.2: Design the initial state for the reservoir power generation optimization scheduling model that takes into account the spawning protection of the four major freshwater fish species. To optimize the power generation scheduling process, add additional states. To correspond to the ecological scheduling model, establish the recursive basic equations, state transition equations, and optimal decision equations for DPTS that consider both the original state and the additional state: ； ； ； Step S4: Use the dual-state dynamic programming DPTS proposed in step S3 to solve the reservoir power generation optimization scheduling model established in step S2 that takes into account the spawning protection of the four major Chinese carp, and obtain the optimal scheduling process of reservoir power generation that takes into account the spawning protection of the four major Chinese carp. Step S4.1: First, determine the input and control parameters related to the reservoir power generation optimization scheduling process, including: input water inflow sequence. Initial control capacity of the storage area during the scheduling period and end control of warehouse capacity and Comprehensive power generation output coefficient The relationship between water level and reservoir capacity, and the relationship between outflow and tailwater level; Step S4.2: Then determine the control parameters related to the ecological scheduling mode that takes into account the spawning protection of the four major freshwater fish species, including: flow rate increase. Duration of days Start-up timing Time window constraints Flow rate during startup interval constraints Discharge flow at the end interval constraints ; Step S4.3: Based on the model input and control parameters determined in steps S4.1 and S4.2, establish the reservoir power generation optimization scheduling model described in step S2, which takes into account the spawning protection of the four major freshwater fish species. Step S4.4: Taking the reservoir capacity as the state and the discharge flow as the decision, establish the recursive basic equation, state transition equation and optimal decision equation of the dual-state dynamic programming (DPTS) based on traditional dynamic programming. Step S4.5: Set the state discretization precision of the dual-state dynamic programming DPTS, and discretize the reservoir capacity for each time period according to the discretization precision to obtain the state discretization set for each time period. ; Step S4.6: Set the time stage variable of the optimization process as follows ,initialization ; Step S4.7: For the optimization of the initial state in the power generation dispatching process, based on the recursive basic equation (4a), state transition equation (5a), and optimal decision equation (6a) of DPTS, find the optimal decision. And determine the time step during the state transition process of the optimal decision. Discrete set of states Each of the original states corresponding time Discrete set of states original state ; Step S4.8: If the time is longer than the time window for the ecological scheduling mode that takes into account the spawning protection of the four major freshwater fish species... The earliest time ( If the additional state is involved in the calculation, then the additional state needs to be included. For the optimization of additional states in the ecological scheduling model, the optimal decision is found based on the recursive basic equation (4b), state transition equation (5b), and optimal decision equation (6b) of DPTS. And determine the time step during the state transition process of the optimal decision. Discrete set of states Each additional state in corresponding time Discrete set of states Additional state ; Step S4.9: If the time falls within the time window that balances the ecological scheduling mode for protecting the spawning of the four major freshwater fish species... Inside( If so, the original state needs to be transformed into the additional state; To optimize the ecological scheduling mode that balances the spawning protection of the four major Chinese carps, the process involves finding the optimal state from the initial state of the power generation scheduling process to the additional state of the ecological scheduling mode. Based on the state transition equation (5c) and optimal decision equation (6c) of the DPTS, the time... Discrete set of states Each of the original states Execute the scheduling mode; then, check whether the operation of the scheduling mode meets the requirements of the outflow rate at startup. interval constraints Discharge flow at the end interval constraints If the above constraints are met, then record the time from time [time]. Discrete set of states The original state At the time Discrete set of states Additional state The process is an additional state The state transition process for optimal decision-making; if the conditions are not met, skip to the next step and continue calculating the time step. Discrete set of states The next primitive state ; Step S4.10, at time Discrete set of states Each discrete state participates in the optimization process of the original state and additional states in steps S4.7 to S4.9, and then the judgment is made. Is it greater than ;if , Proceed to step S4.7; if The optimization process ends, proceed to step S4.11; Step 4.11, from time... Discrete set of states The optimal original state for maximizing power generation is selected. and additional states Then, based on the recursive basic equation (4), state transition equation (5), and optimal decision equation (6) of DPTS, the following can be obtained step by step through reverse deduction: The optimal process of reservoir power generation optimization scheduling The optimal process for reservoir power generation optimization and scheduling that also takes into account the spawning protection of the four major freshwater fish species. .

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