Method, system and equipment for formulating water-light complementation short-term scheduling rule

Abstract

The invention discloses a method, a system and equipment for formulating a water-light complementation short-term scheduling rule, and relates to the field of reservoir scheduling and new energy grid-connected cross application. Taking the maximum generating capacity, the minimum residual load standard deviation, the minimum comprehensive risk and the minimum deviation target flow of the water-optical complementary system as objective functions, and constructing a water-optical complementary system short-term scheduling rule compilation model according to required constraint conditions; taking the monthly discharged flow as a boundary condition of the water-optical complementary system short-term scheduling rule compiling model; according to a parameter-simulation-optimization framework used for solving a complex system optimization problem, a multi-target cuckoo algorithm is used for optimizing a water-optical complementary system short-term scheduling rule compiling model, a fuzzy decision method is used for selecting an equilibrium solution, and therefore a water-optical complementary system short-term scheduling rule is formulated. According to the method, the water-light complementary system short-term scheduling rule suitable for different photovoltaic installed capacity scenes can be constructed.

Description

Technical Field

[0001] The present invention relates to the cross-application field of reservoir scheduling and clean energy grid connection, and in particular to a method, system and device for formulating short-term scheduling rules for water-photovoltaic complementarity. Background Art

[0002] In order to guide the capacity planning of the hydro-photovoltaic complementary system and to simulate the operation and dispatching process of the hydro-photovoltaic complementary system under different installed capacity scales, it is necessary to formulate the short-term dispatching rules of the hydro-photovoltaic complementary system. Based on various photovoltaic installed capacity scenarios, in order to improve the rationality of the short-term dispatching rules formulated in the hydro-photovoltaic complementary system, how to determine the short-term dispatching rules of the hydro-photovoltaic system applicable to various photovoltaic installed capacity scenarios is a key issue to be solved in the current implementation of multi-energy complementary operation management.

[0003] In the prior art, the short-term scheduling rules for hydro-solar complementarity directly obtain the daily scheduling process of the system by inputting the daily available energy, thereby improving the capacity configuration efficiency.

[0004] However, existing technologies do not consider the applicability of short-term scheduling rules for hydro-photovoltaic complementarity in different photovoltaic installed capacity scenarios. Summary of the invention

[0005] The embodiments of the present invention provide a method, system and device for formulating short-term scheduling rules for water-photovoltaic complementarity, which can solve the problem in the prior art that the applicability of short-term scheduling rules for water-photovoltaic complementarity in different photovoltaic installed capacity scenarios is not considered.

[0006] The embodiment of the present invention provides a method for formulating short-term dispatching rules for hydro-photovoltaic complementarity, comprising the following steps: obtaining the monthly discharge flow of a hydropower station in a hydro-photovoltaic complementarity power station, determining the time node and the output per unit value that describe the type of the hydro-photovoltaic complementarity short-term dispatching rule; under different photovoltaic installed capacity scenarios, using the time node and the output per unit value as decision variables, taking the maximum power generation of the hydro-photovoltaic complementarity system, the minimum comprehensive risk rate of the hydro-photovoltaic complementarity system, the minimum deviation of the hydro-photovoltaic complementarity system from the target discharge flow and the minimum standard deviation of the residual load of the power grid as objective functions, and taking the water balance constraint, the reservoir capacity constraint, the discharge flow constraint, the hydropower output constraint as decision variables, and the hydro-photovoltaic complementarity short-term dispatching rule as decision variables; The short-term dispatching rule compilation model of the hydro-photovoltaic complementary system is constructed with the constraints of the beam and the characteristic constraints of the hydropower station as constraints; and the monthly discharge flow is used as the boundary condition of the short-term dispatching rule compilation model of the hydro-photovoltaic complementary system; according to the parameter-simulation-optimization framework for solving complex system optimization problems, the multi-objective cuckoo algorithm is used to optimize the short-term dispatching rule compilation model of the hydro-photovoltaic complementary system; according to the operating parameters of the hydro-photovoltaic complementary power station, the optimized short-term dispatching rule compilation model of the hydro-photovoltaic complementary system is used to obtain the model solution set; the fuzzy decision method is used to select the equilibrium solution from the model solution set to obtain the short-term dispatching rule of the hydro-photovoltaic complementary system.

[0007] Furthermore, the construction of the short-term dispatch rule compilation model for the hydro-solar complementary system also needs to be based on the "five-segment line" transmission curve type, which divides a day into five time periods, and each time period has a different output per unit value.

[0008] Furthermore, the fuzzy decision-making method is used to select the equilibrium solution, and the specific steps include: using a multi-objective cuckoo algorithm to solve the short-term scheduling rule compilation model of the water-photovoltaic complementary system, and obtaining a Pareto solution set as a model solution set, each solution of the Pareto solution set corresponds to a set of objective function values; using fuzzy membership to express the satisfaction level of each objective function, and calculating the average satisfaction level of each solution, arranging the average satisfaction levels in descending order, and selecting the solution corresponding to the highest satisfaction level as the equilibrium solution.

[0009] Furthermore, the method of obtaining the monthly downstream discharge flow of the hydropower station in the hydro-photovoltaic complementary power station comprises the following specific steps: taking the maximum power generation of the hydro-photovoltaic complementary system and the highest power generation guarantee rate as the objective function, and constructing a long-term optimization model for the hydro-photovoltaic complementary system according to the economy and reliability of the hydro-photovoltaic complementary power station, taking water balance constraints, reservoir capacity constraints, hydropower output constraints, downstream discharge constraints, water level boundary condition constraints and hydropower station characteristic constraints as constraints; inputting historical runoff data, historical solar radiation data and historical temperature data of the hydro-photovoltaic complementary power station into the long-term optimization model of the hydro-photovoltaic complementary system, obtaining a long sequence scheduling process based on the parameter-simulation-optimization framework processing model, and obtaining the monthly downstream discharge flow of the hydropower station in the hydro-photovoltaic complementary power station according to the long sequence scheduling process.

[0010] The embodiment of the present invention provides a system for formulating short-term scheduling rules for water-solar complementarity, including:

[0011] The data acquisition module obtains the monthly discharge flow of the hydropower station in the hydro-photovoltaic complementary power station, and determines the time node and output per unit value that describe the short-term dispatch rule type of hydro-photovoltaic complementary power station; the model construction module is used to use the time node and output per unit value as decision variables under different photovoltaic installed capacity scenarios, and takes the maximum power generation of the hydro-photovoltaic complementary system, the minimum comprehensive risk rate of the hydro-photovoltaic complementary system, the minimum deviation of the hydro-photovoltaic complementary system from the target discharge flow and the minimum standard deviation of the residual load of the power grid as the objective function, and takes the water balance constraint, reservoir capacity constraint, discharge flow constraint, hydropower output constraint, and hydropower station characteristic constraint as constraint conditions. A model for compiling short-term dispatching rules for a hydro-photovoltaic complementary system is constructed; and the monthly discharge flow is used as the boundary condition of the model for compiling short-term dispatching rules for a hydro-photovoltaic complementary system; based on the parameter-simulation-optimization framework used to solve complex system optimization problems, a multi-objective cuckoo algorithm is used to optimize the model for compiling short-term dispatching rules for a hydro-photovoltaic complementary system; a short-term dispatching rule formulation module is used to obtain a model solution set using the optimized model for compiling short-term dispatching rules for a hydro-photovoltaic complementary system according to the operating parameters of the hydro-photovoltaic complementary power station; a fuzzy decision method is used to select an equilibrium solution from the model solution set to obtain the short-term dispatching rules for a hydro-photovoltaic complementary system.

[0012] An embodiment of the present invention provides a computer device, including: a memory and a processor; the memory stores a computer program, and when the processor executes the computer program, it implements the above-mentioned method for formulating short-term scheduling rules for water-wind-solar complementarity.

[0013] The embodiment of the present invention provides a method, system and device for formulating short-term scheduling rules for water-wind-solar complementarity. Compared with the prior art, the beneficial effects thereof are as follows:

[0014] Under different photovoltaic installed capacity scenarios, with time nodes and output per unit value as decision variables, maximum power generation of hydro-photovoltaic complementary system, minimum comprehensive risk rate of hydro-photovoltaic complementary system, minimum deviation of hydro-photovoltaic complementary system from target downstream flow and minimum standard deviation of grid residual load as objective functions, and water balance constraint, reservoir capacity constraint, downstream flow constraint, hydropower output constraint and hydropower station characteristic constraint as constraint conditions, a short-term dispatching rule compilation model for hydro-photovoltaic complementary system is constructed; and the monthly downstream flow is used as the boundary condition of the short-term dispatching rule compilation model for hydro-photovoltaic complementary system; according to the parameter-simulation-optimization framework for solving complex system optimization problems, the multi-objective cuckoo algorithm is used to optimize the short-term dispatching rule compilation model for hydro-photovoltaic complementary system; according to the operating parameters of the hydro-photovoltaic complementary power station, the optimized short-term dispatching rule compilation model for hydro-photovoltaic complementary system is used to obtain the model solution set; the fuzzy decision method is used to select the equilibrium solution from the model solution set to obtain the short-term dispatching rule for the hydro-photovoltaic complementary system.

[0015] Among them, different photovoltaic installed capacity scenarios have different corresponding output per unit values ​​at the selected time nodes. The time nodes and output per unit values ​​are used as decision variables to construct a model for compiling short-term scheduling rules for water-photovoltaic complementary systems. The short-term scheduling rules for the water-photovoltaic complementary system obtained by the model are also applicable to different photovoltaic installed capacity scenarios. Finally, the effect of the short-term scheduling rules of the water-photovoltaic complementary system being applicable to different photovoltaic installed capacity scenarios is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematic diagram of short-term scheduling rules for water-solar complementarity provided by an embodiment of the present invention;

[0017] Figure 2 A schematic diagram of a model solution provided by an embodiment of the present invention;

[0018] Figure 3 Schematic diagram of the objective function of the short-term scheduling rule compilation model of the water-photovoltaic complementary system provided by an embodiment of the present invention;

[0019] Figure 4 A schematic diagram of constraint conditions for a short-term scheduling rule compilation model for a water-photovoltaic complementary system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0021] See also Figure 1 to Figure 4 The embodiment of the present invention provides a method for formulating short-term scheduling rules for water-solar complementarity, comprising the following steps:

[0022] Step 1: Obtain the monthly discharge flow of the hydropower station in the hydro-solar complementary power station, and determine the time node and output per unit value that describe the short-term scheduling rule type of the hydro-solar complementary power station.

[0023] Step 2: Under different PV installed capacity scenarios, with time nodes and output per unit value as decision variables, and maximum power generation of the hydro-photovoltaic complementary system, minimum comprehensive risk rate of the hydro-photovoltaic complementary system, minimum deviation of the hydro-photovoltaic complementary system from the target downstream flow, and minimum standard deviation of the grid residual load as objective functions, considering constraints such as water balance constraints, reservoir capacity constraints, downstream flow constraints, hydropower output constraints, and hydropower station characteristics constraints as constraints, a short-term dispatching rule compilation model for the hydro-photovoltaic complementary system is constructed; and the monthly downstream flow is used as the boundary condition of the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; according to the parameter-simulation-optimization framework used to solve complex system optimization problems, the multi-objective cuckoo algorithm is used to optimize the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system.

[0024] Step 3: According to the operating parameters of the hydro-photovoltaic complementary power station, the optimized short-term dispatching rules of the hydro-photovoltaic complementary system are used to compile a model to obtain a model solution set; the fuzzy decision method is used to select the equilibrium solution from the model solution set to obtain the short-term dispatching rules of the hydro-photovoltaic complementary system.

[0025] 1. Determine the short-term scheduling boundary conditions. The historical runoff data, historical solar radiation data, and historical temperature data of the hydro-photovoltaic complementary power station are used as the input of the established medium- and long-term optimization model of the hydro-photovoltaic complementary system. Considering the economy and reliability of the hydro-photovoltaic complementary power station, the medium- and long-term optimization model is constructed with the maximum power generation and the highest power generation guarantee rate of the hydro-photovoltaic complementary system as the objective function.

[0026] The objective function of the medium- and long-term optimization model is as follows:

[0027] Objective function 1: The power generation of the water-photovoltaic complementary system is maximized.

[0028]

[0029] Objective function 2: The water-photovoltaic complementary system has the highest power generation guarantee rate.

[0030]

[0031] Where: EP is the total power generation during the complementary system dispatch period; t and T are the mid- and long-term dispatch period number and the total dispatch period, respectively; is the actual average monthly output of hydropower in the tth period; Q t is the power generation flow of the hydropower station in the tth period; ΔH t is the generating head in the tth period; ER is the power generation guarantee rate of the complementary system; It is the number of times the net output of the complementary system exceeds the guaranteed output during the entire dispatch period.

[0032] The constraints considered in this model are as follows:

[0033] (1) Water balance constraints:

[0034] V t+1 =V t +(I t -Q t -EI t )ΔT

[0035] (2) Storage capacity constraints:

[0036] V t min ≤V t ≤V t max

[0037] (3) Hydropower output constraints:

[0038]

[0039] (4) Downflow flow restriction:

[0040] Q out,min ≤Q out,t ≤Q out,max

[0041] (5) Water level boundary condition constraints:

[0042] Z q =Z i

[0043] (6) Hydropower station characteristic constraints:

[0044] Z t =f zv (V t )

[0045] Z tail,t =f zq (Q e,t +Q s,t )

[0046] Where: V t and V t+1 are the storage capacity of the reservoir in period t and period t+1 respectively; I t , Q t , and EI t are the inflow, outflow, and evaporation and leakage losses of the reservoir in period t respectively; V t min and V t max are the minimum and maximum storage capacities of the reservoir in period t respectively; Z q is the actual value of the reservoir water level during the dispatch period; Z i is the design value of the reservoir water level; Z t is the water level of the reservoir at time t; Ztail,t is the tailwater level of the reservoir in period t; Q s,t is the discharge flow of the conventional unit of the reservoir in period t; Q e,t is the discharge flow of the reservoir ecological unit in period t; Q out,min and Q out,max are the minimum and maximum discharge flows of the reservoir respectively; Q out,t is the discharge flow of the reservoir in period t; and are the lower and upper limits of the power output of the hydropower station in period t respectively.

[0047] At the same time, based on the parameter-simulation-optimization framework, the model is solved to obtain the long-sequence scheduling process. Its average monthly hydropower output is used as the input of the short-term scheduling model, and the downstream flow process is used as the boundary condition of the short-term scheduling model.

[0048] 2. Establish a model for the compilation of short-term dispatch rules for the hydro-photovoltaic complementary system. Taking the time nodes and their corresponding time nodes and output per unit values ​​as decision variables, considering the operation risks of the hydro-photovoltaic complementary system, the economic efficiency of the hydropower station, peak load regulation and power generation benefits, a model for the compilation of short-term dispatch rules for the hydro-photovoltaic complementary system is established.

[0049] Objective function 1: The power generation of the water-photovoltaic complementary system is maximized.

[0050]

[0051] Objective function 2: The comprehensive risk rate of the water-photovoltaic complementary system is minimized.

[0052]

[0053] Objective function 3: The deviation of the hydro-photovoltaic complementary system from the target downstream flow is minimized.

[0054]

[0055] Objective function 4: The standard deviation of the grid residual load is minimized.

[0056]

[0057] Where: s and S are the sth photovoltaic installed capacity scenario and the total number of photovoltaic installed capacity scenarios, respectively; EP is the mean of the total power generation under various photovoltaic installed capacity scenarios; EG is the mean of the standard deviation of the grid residual load under various photovoltaic installed capacity scenarios; TR is the mean of the comprehensive risk rate under various photovoltaic installed capacity scenarios of the complementary system; and are the power abandonment rate and load loss rate in the tth dispatching period respectively; L t is the large power grid load in the tth dispatching period; is the remaining load in the tth dispatch period; is the simulated value of the discharge flow in the mth month under the sth PV installed capacity scenario; is the discharge flow constraint value in the mth month under the sth PV installed capacity scenario.

[0058] The constraints considered in the established short-term dispatching rule compilation model for the hydro-photovoltaic complementary system include water balance constraints, reservoir capacity constraints, downstream flow constraints, hydropower output constraints, and hydropower station characteristic constraints.

[0059] 3. Use a multi-objective optimization algorithm to solve the constructed optimization model and obtain the Pareto solution set of the problem.

[0060] Based on the parameter-simulation-optimization framework, the Multi-objective Cuckoo Search (MOCS) algorithm is used to optimize the short-term scheduling rule compilation model of the water-solar hybrid system. The basic process of the MOCS algorithm is shown in Figure 2 shown.

[0061] 4. Use fuzzy decision-making method to select equilibrium solutions from Pareto solution set, and then output the short-term scheduling rules of water-solar hybrid system. The specific selection steps are: express the satisfaction degree corresponding to each objective function on the Pareto solution set with fuzzy membership function, and calculate the average satisfaction degree of each solution, and take the solution with the highest average satisfaction as the equilibrium solution of this model. The satisfaction calculation formula is as follows:

[0062]

[0063] Where: f i is the objective function value; N obj is the number of objective functions; f i max and f i min Respectively represent the maximum and minimum values ​​of the i-th objective function; h i is the satisfaction degree corresponding to each objective function. When it is 0, it means completely dissatisfied. When it is 1, it means satisfied with the value of the i-th objective function.

[0064] The present invention also has the following beneficial effects:

[0065] The present invention establishes a model for compiling short-term dispatching rules for a water-photovoltaic complementary system by comprehensively considering the operating risks of the water-photovoltaic complementary system, the economic efficiency of the hydropower station, peak regulation and power generation benefits, and can theoretically output the optimal short-term dispatching rules at the same time; moreover, the dispatching rule results can adapt to a variety of photovoltaic installed capacity scenarios, which is of great significance for guiding the multi-energy complementary operation management under photovoltaic installed capacity planning.

[0066] The embodiment of the present invention provides a system for formulating short-term scheduling rules for water-solar complementarity, including:

[0067] The data acquisition module is used to obtain the monthly discharge flow of the hydropower station in the hydro-photovoltaic complementary power station, and determine the time node and output per unit value describing the short-term scheduling rule type of the hydro-photovoltaic complementary power station.

[0068] The model building module is used to build a short-term dispatching rule compilation model for the hydro-photovoltaic complementary system under different photovoltaic installed capacity scenarios, with time nodes and output per unit value as decision variables, maximum power generation of the hydro-photovoltaic complementary system, minimum comprehensive risk rate of the hydro-photovoltaic complementary system, minimum deviation of the hydro-photovoltaic complementary system from the target downstream flow and minimum standard deviation of the grid residual load as objective functions, and water balance constraints, reservoir capacity constraints, downstream flow constraints, hydropower output constraints, and hydropower station characteristic constraints as constraints; and monthly downstream flow is used as the boundary condition of the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; according to the parameter-simulation-optimization framework used to solve complex system optimization problems, the multi-objective cuckoo algorithm is used to optimize the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system.

[0069] The short-term dispatch rule formulation module is used to compile a model using the optimized short-term dispatch rule of the hydro-photovoltaic complementary system according to the operating parameters of the hydro-photovoltaic complementary power station to obtain a model solution set; a fuzzy decision method is used to select an equilibrium solution from the model solution set to obtain the short-term dispatch rule of the hydro-photovoltaic complementary system.

[0070] An embodiment of the present invention provides a computer device, including: a memory and a processor; the memory stores a computer program, and when the processor executes the computer program, the steps of a method for formulating short-term scheduling rules for water-solar complementarity are implemented.

[0071] A specific embodiment is as follows:

[0072] Step 1: Considering the economy and reliability of the hydro-photovoltaic complementary power station, a medium- and long-term optimization model of the hydro-photovoltaic complementary system is constructed, and the monthly discharge flow obtained by the model is solved and used as the boundary condition for short-term scheduling.

[0073] Taking the maximum power generation and the highest power generation guarantee rate of the hydro-photovoltaic complementary system as the objective function, a medium- and long-term optimization scheduling model is constructed. Based on the parameter-simulation-optimization framework, the model is solved to obtain the optimal medium- and long-term scheduling rule form, and then long-sequence simulation scheduling is carried out, and the monthly average downstream flow process is used as the boundary condition for short-term scheduling.

[0074] Step 2: Assuming that there are S scenarios of photovoltaic installed capacity, based on the "five-segment line" transmission curve type, with time nodes and output per unit value as decision variables, considering the operation risk of the hydro-photovoltaic complementary system, the economy of the hydropower station, peak regulation and power generation benefits, a short-term scheduling rule compilation model for the hydro-photovoltaic complementary system is constructed.

[0075] Objective function 1: The power generation of the water-photovoltaic complementary system is maximized.

[0076]

[0077] Objective function 2: The comprehensive risk rate of the water-photovoltaic complementary system is minimized.

[0078]

[0079] Objective function 3: The deviation of the hydro-photovoltaic complementary system from the target downstream flow is minimized.

[0080]

[0081] Objective function 4: The standard deviation of the grid residual load is minimized.

[0082]

[0083] The constraints of the model include water balance constraints, reservoir capacity constraints, downstream flow constraints, hydropower output constraints and hydropower station characteristic constraints.

[0084] Step 3: Use a multi-objective optimization algorithm to solve the optimization model and obtain the Pareto solution set of the problem.

[0085] The cuckoo search algorithm optimization model is used to obtain the optimal short-term dispatch rules for each month suitable for different photovoltaic installed capacity, with a total of 12 short-term dispatch rule curves. The daily available electricity is allocated according to the short-term dispatch rule curves of the corresponding month, and the short-term power generation plan of the water-photovoltaic complementary system can be obtained, as shown in the following formula.

[0086]

[0087] Where: is the short-term dispatching rule of the water-photovoltaic complementary system in the t period under the photovoltaic installed capacity x; unitline y,t is the short-term scheduling rule for month y corresponding to period t; It is the daily power generation of the water-photovoltaic complementary system in the t period under the photovoltaic installed capacity x.

[0088] Step 4: Use the multi-attribute decision-making method to select the short-term scheduling rules of the water-photovoltaic complementary system from the Pareto solution set to compile the model equilibrium solution, thereby outputting the optimal short-term scheduling rules for the water-photovoltaic complementary system in each month.

[0089] The process of preparing a hydro-photovoltaic complementary power generation plan based on short-term dispatch rules is as follows:

[0090] (1) The medium- and long-term optimization scheduling model is used to calculate the hydropower output.

[0091] (2) Calculate the daily available electricity based on the hydropower output and photovoltaic output.

[0092] (3) Scale the daily available electricity according to the shape of the short-term dispatch rule to obtain the short-term dispatch rule curve.

[0093] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for formulating short-term scheduling rules for water-solar complementarity, characterized in that: The following steps are involved: Obtain the monthly discharge flow of the hydropower station in the hydro-solar hybrid power station, and determine the time node and output per unit value that describe the short-term dispatch rule type of the hydro-solar hybrid power station; Under different photovoltaic installed capacity scenarios, the time node and output per unit value are used as decision variables, the maximum power generation of the hydro-photovoltaic complementary system, the minimum comprehensive risk rate of the hydro-photovoltaic complementary system, the minimum deviation of the hydro-photovoltaic complementary system from the target downstream flow and the minimum standard deviation of the residual load of the power grid are used as objective functions, and the water balance constraint, reservoir capacity constraint, downstream flow constraint, hydropower output constraint and hydropower station characteristic constraint are used as constraint conditions to construct a short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; and the monthly downstream flow is used as the boundary condition of the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; according to the parameter-simulation-optimization framework used to solve complex system optimization problems, the multi-objective cuckoo algorithm is used to optimize the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; According to the operating parameters of the hydro-photovoltaic complementary power station, the optimized short-term dispatching rules of the hydro-photovoltaic complementary system are used to compile a model to obtain the model solution set; the fuzzy decision method is used to select the equilibrium solution from the model solution set to obtain the short-term dispatching rules of the hydro-photovoltaic complementary system.

2. The method for formulating short-term scheduling rules for water-solar complementary power generation according to claim 1, characterized in that: The construction of the short-term dispatch rule compilation model for the hydro-photovoltaic complementary system also needs to be based on the "five-segment line" transmission curve type. The "five-segment line" transmission curve type divides a day into five time periods, and each time period has a different output per unit value.

3. The method for formulating short-term scheduling rules for water-solar complementary power generation according to claim 1, characterized in that: The fuzzy decision method is used to select the equilibrium solution, and the specific steps include: A multi-objective cuckoo algorithm is used to solve a short-term scheduling rule compilation model of a water-solar hybrid system, and a Pareto solution set is obtained as a model solution set, wherein each solution of the Pareto solution set corresponds to a set of objective function values; The fuzzy membership degree is used to express the satisfaction degree of each objective function, and the average satisfaction degree of each solution is calculated. The average satisfaction degrees are arranged in descending order, and the solution corresponding to the highest satisfaction degree is selected as the equilibrium solution.

4. The method for formulating short-term scheduling rules for water-solar complementarity according to claim 1, characterized in that: The specific steps of obtaining the monthly discharge flow of the hydropower station in the hydro-photovoltaic complementary power station include: Taking the maximum power generation and the highest power generation guarantee rate of the hydro-photovoltaic complementary system as the objective function, according to the economy and reliability of the hydro-photovoltaic complementary power station, with water balance constraints, reservoir capacity constraints, hydropower output constraints, downstream flow constraints, water level boundary conditions constraints and hydropower station characteristics constraints as constraints, a long-term optimization model of the hydro-photovoltaic complementary system is constructed; The historical runoff data, historical solar radiation data and historical temperature data of the hydro-photovoltaic complementary power station are input into the long-term optimization model of the hydro-photovoltaic complementary system. The model is processed based on the parameter-simulation-optimization framework to obtain the long-sequence scheduling process. According to the long-sequence scheduling process, the monthly discharge flow of the hydropower station in the hydro-photovoltaic complementary power station is obtained.

5. A system for formulating short-term scheduling rules for water-solar complementary power generation, characterized in that: include: A data acquisition module is used to obtain the monthly discharge flow of the hydropower station in the hydro-solar complementary power station, and determine the time node and output per unit value describing the short-term dispatch rule type of the hydro-solar complementary power station; The model building module is used to build a short-term dispatching rule compilation model for the hydro-photovoltaic complementary system under different photovoltaic installed capacity scenarios, with time nodes and output per unit value as decision variables, maximum power generation of the hydro-photovoltaic complementary system, minimum comprehensive risk rate of the hydro-photovoltaic complementary system, minimum deviation of the hydro-photovoltaic complementary system from the target downstream flow, and minimum standard deviation of the residual load of the power grid as objective functions, and water balance constraints, reservoir capacity constraints, downstream flow constraints, hydropower output constraints, and hydropower station characteristic constraints as constraints; and monthly downstream flow is used as the boundary condition of the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; according to the parameter-simulation-optimization framework used to solve complex system optimization problems, the multi-objective cuckoo algorithm is used to optimize the short-term dispatching rule compilation model for the hydro-photovoltaic complementary system; The short-term dispatch rule formulation module is used to compile a model using the optimized short-term dispatch rule of the hydro-photovoltaic complementary system according to the operating parameters of the hydro-photovoltaic complementary power station to obtain a model solution set; a fuzzy decision method is used to select an equilibrium solution from the model solution set to obtain the short-term dispatch rule of the hydro-photovoltaic complementary system.

6. A computer device comprising: Memory and processor; The memory stores a computer program, wherein the processor implements a method for formulating short-term scheduling rules for water-solar complementary power as described in any one of claims 1 to 4 when executing the computer program.

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