A capacity configuration method of an electro-pumped-storage-wind-light combined power generation system

Abstract

The application discloses a kind of water-electricity-pumping-storage-wind-light combined power generation system capacity configuration method, comprising the following steps: step (1), generate typical wind power and photovoltaic output scene;Step (2), according to the runoff frequency distribution characteristics, the runoff corresponding to the typical frequency is generated in each season Runoff scene;Step (3), establish the two-stage complementary strategy of water-electricity collaborative pumping-storage complementary wind, light operation;Step (4), construct water-electricity-pumping-storage-wind-light multi-energy complementary system capacity optimization configuration mathematical model;Step (5), construct the optimal coordinated operation model of wind farm and photovoltaic power station under different planning installed capacity conditions Full scene;Step (6), the wind light capacity and supporting channel capacity configuration method of scenario set optimization result is used to the full scene optimal coordinated operation result obtained in step (5), and wind light capacity and supporting channel capacity configuration scheme are formulated;The application realizes water-electricity combined pumping-storage adaptive complementary wind, light output, and effectively improves the stability of interchannel transmission total output.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of capacity configuration of wind power and photovoltaic installed capacity and supporting transmission channel capacity in a hydropower-pumped storage-wind-photovoltaic combined power generation system, and particularly relates to a capacity configuration method of a hydropower-pumped storage-wind-photovoltaic combined power generation system. BACKGROUND

[0002] The deep adjustment of energy structure and the rapid promotion of emission reduction strategy have promoted the development and utilization of clean energy represented by photovoltaic and wind power. It is necessary and will continue to be the top priority of China's future energy work to develop and utilize clean energy. The overall development and utilization of photovoltaic, wind power and hydropower clean energy in China shows a distribution characteristic of more in the west and less in the east along the Hu Huanyong line, forming an energy encirclement of "three norths" plus coastal areas. From the perspective of energy supply and demand and clean energy replacement, the demand of the eastern region along the Hu Huanyong line is significantly greater than that of the western region with excellent resource endowments, and the spatial mismatch of clean energy supply and demand requires China to take its own energy development road.

[0003] Wind and light energy have special regional endowments and inherent intermittency, volatility and randomness. Large-scale and high-proportion direct grid connection has an impact on the stability and safety of power grid operation and increases the demand for regulation capacity of power grid. In particular, when special high-voltage direct current cross-regional transmission is adopted for consumption, the stability of the transmission process requires high, and if the grid-connected power process does not meet the requirements, it will lead to frequent adjustment of transmission equipment and even failure. Based on this, considering the characteristics of wind and light resource endowments and their inherent intermittency, volatility and randomness, combined with the flexible characteristics of hydropower output regulation, large-scale water-wind-photovoltaic clean energy systems in the west have been developed and planned, and the clean electricity produced will be transmitted to the eastern region for consumption through special high-voltage transmission lines. With the access and large-scale of wind and light energy in the basin, the new complementary operation requirements increase the difficulty of water power station dispatching decision. How to adapt to the integration of multiple types of new energy on the basis of guaranteeing the original functional requirements, realize the complementation of energy in multiple time scales and multiple types, and compensate for water resources by clean energy, has become a difficult problem to be solved by the basin development and management institutions.

[0004] In recent years, a water-electricity-pumped storage-wind-solar multi-energy complementary system development mode has been proposed in China, which uses the upper and lower reservoirs of cascade hydropower stations as regulating pools to develop pumped storage power stations. The addition of pumped storage power stations will effectively improve the ability of hydropower stations to complement wind and solar power, making the multi-energy complementary system more secure for grid-connected power generation. However, the above-mentioned projects and equipment, as well as the supporting transmission channels, significantly increase the investment. How to balance the investment and output is the key problem that needs to be solved first. On the other hand, hydropower stations have their own planning functions, inflow characteristics, storage and regulation performance. After participating in the multi-energy complementary operation, how to maintain the same function while optimally utilizing pumped storage to achieve the best operation and control of the complementary system is also a key problem that needs to be solved. Therefore, it is necessary to propose a water-electricity-pumped storage-wind-solar combined power generation system capacity configuration method based on the bundled transmission of ultra-high voltage direct current channels. SUMMARY

[0005] In view of the problems in the prior art, the present application provides a water-electricity-pumped storage-wind-solar combined power generation system capacity configuration method based on the bundled transmission of ultra-high voltage direct current channels. The method can be used to determine the water-electricity-pumped storage-wind-solar multi-energy complementary system capacity optimization configuration mathematical model by considering the uncertainty of wind power and photovoltaic energy and runoff in large-scale water-electricity-pumped storage-wind-solar multi-energy complementary system and the characteristics of ultra-high voltage cross-network transmission, and using the proposed two-stage complementary strategy of water-electricity-pumped storage-wind-solar multi-energy complementary system. A multi-objective, multi-level comprehensive evaluation index of water-electricity-pumped storage-wind-solar multi-energy complementary system is proposed for the full-scenario simulation optimization results, and a system full-life cycle evaluation method considering multi-objective cost is established. Based on the system comprehensive evaluation, the best capacity configuration scheme of water-electricity-pumped storage-wind-solar multi-energy complementary system under the transmission and consumption of ultra-high voltage direct current and the corresponding system operation mode are formed, which can realize the self-adaptive complementation of wind and solar power in water-electricity-pumped storage-wind-solar multi-energy complementary system and effectively improve the stability of total output of inter-channel transmission. The present application can provide technical support for the planning and construction of water-electricity-pumped storage-wind-solar multi-energy complementary system, and is suitable for popularization and application in the capacity configuration of wind power, photovoltaic power and supporting channels in large-scale water-electricity-pumped storage-wind-solar multi-energy complementary system.

[0006] In order to solve the problems in the prior art, the present application adopts the following technical scheme:

[0007] A water-electricity-pumped storage-wind-solar combined power generation system capacity configuration method, comprising the following steps:

[0008] Step (1), the historical measured daily output process of the built wind power plant and photovoltaic power station in the research area is divided into four categories according to seasons, and typical wind power and photovoltaic output scenarios are generated;

[0009] Step (2), the historical daily runoff data of the upstream hydrological station of the hydropower station is divided into four categories according to seasons, and the frequency of the historical daily runoff is counted respectively, and the runoff corresponding to the typical frequency is selected according to the runoff frequency distribution characteristics to generate the runoff scenario of each season;

[0010] Step (3), according to the characteristics of the ultra-high voltage transmission line of the large-scale hydropower-pumping-storage-wind-solar combined power generation system, and considering the uncertainty of wind power and photovoltaic output and reservoir runoff, the output characteristics of hydropower and pumping storage units, the time parameter and the characteristic parameter are used to describe the total output process of the hydropower-pumping-storage-wind-solar combined power generation system under the ultra-high voltage transmission demand, and a two-stage complementary strategy of hydropower cooperating with pumping storage to complement wind and light operation is set.

[0011] Step (4), a mathematical model for optimizing the capacity configuration of the hydropower-pumping-storage-wind-solar multi-energy complementary system is established based on the complementary strategy of step (3);

[0012] Step (5), the typical wind-solar joint scenario daily output process obtained in step (1) and the typical runoff scenario obtained in step (2) are used as input variables of the multi-objective optimization model established in step (4), and a multi-objective optimization algorithm is used to solve the model, to obtain the channel sending capacity and the optimal cooperative operation process under different planning installed capacity conditions, and to calculate the daily output (power) process of the hydropower station and the pumped storage power station and the channel sending process;

[0013] Step (6), considering the factors such as the hydropower joint pumping storage complementary ability, the channel sending characteristics, the wind power and photovoltaic on-grid price, the component cost, the land cost, the social discount rate and the like, a wind-solar capacity and supporting channel capacity configuration method based on the optimization results of the scenario set is proposed;

[0014] Step (7), based on the full-scenario optimal cooperative operation results obtained in step (5), the configuration method proposed in step (6) is used to develop a wind-solar capacity and supporting channel capacity configuration scheme according to the target orientation of the managers and decision makers.

[0015] Further, in step (1), spring is March, April and May, summer is June, July and August, autumn is September, October and November, and winter is December, January and February; the scenario generation step specifically includes: using the Copula function to construct a wind-solar output joint probability distribution model for each season and each time period; using the Latin hypercube sampling method to sample the output data of each season and each time period respectively to obtain a wind-solar joint output data set for each season; generating a large number of wind-solar joint output initial scenario sets satisfying the wind-solar output fluctuation characteristics according to the samples with random characteristics obtained by sampling; finally, using the FCM clustering method of eigenvalue dimension reduction to reduce the initial scenario set to obtain a typical wind-solar joint output scenario.

[0016] Further, in step (2), the spring is March, April, May, the summer is June, July, August, the autumn is September, October, November, and the winter is December, January, February; the runoff scenario generation step of each season specifically includes: dividing the area surrounded by the runoff frequency curve and the coordinate axis using different probability intervals, and the area surrounded by each boundary of each interval represents the inflow value in the runoff scenario, and finally a typical runoff scenario is obtained.

[0017] Further, in step (3), the two-stage complementary strategy includes: in the first complementary adjustment stage, pumped storage power station is used to complementally adjust the wind-solar combined output, and the wind-solar output curve is complemented to a multi-segment line, in each segment of the multi-segment line, the pumped storage power station generates power when the output of the segment is greater than the wind-solar output, and the pumped storage power station pumps water when the output of the segment is less than the wind-solar output; in the second complementary adjustment stage, the hydropower station is used to complementally adjust the multi-segment line output obtained in the first stage, and the hydropower station compensates it to a U+1 segment line; wherein: according to the extra-high voltage transmission characteristics, the U+1 segment line divides the total output process of the hydropower-pumped storage-wind-solar combined power generation system into U+1 stages, each stage is subdivided into a plurality of time periods according to the decision time step, and the total output of the hydropower-pumped storage-wind-solar combined power generation system in each stage is a certain constant value, and the characteristic parameters are used to represent the output characteristics of different stages.

[0018] Further, in step (4), the capacity optimization configuration mathematical model of the hydropower-pumped storage-wind-solar multi-energy complementary system is a multi-objective optimization model, which is composed of an objective function, decision variables and constraint conditions.

[0019] a. Objective function:

[0020] f1: maximize the complementary system power generation

[0021]

[0022] In the formula:

[0023] Pj is the total output of the complementary system in the jth time period, (MW);

[0024] Pj is the output of the hydropower station in the jth time period, (MW);

[0025] Pj is the combined output of wind power and photovoltaic power in the jth time period, (MW);

[0026] Pj is the pumping power of the pumped storage power station in the jth time period, (MW);

[0027] Pj is the generation power of the pumped storage power station in the jth time period, (MW);

[0028] ηj is the comprehensive output coefficient of the hydropower station in the jth time period, which is related to the unit output and the generation water head;

[0029] Qj is the average generation flow of the hydropower station in the jth time period, (m / s); 3

[0030] Hj is the average generation water head of the hydropower station in the jth time period, (m);

[0031] C wp Ptotal is the total capacity of wind power and photovoltaic, (MW);

[0032] Ppv is the proportion of photovoltaic capacity in the total capacity of wind and light, (MW);

[0033] Pw is the unit megawatt machine output of wind power in the jth time period, (MW);

[0034] Ppv is the unit megawatt machine output of photovoltaic in the jth time period, (MW);

[0035] J is the number of time periods in the dispatching period;

[0036] Pj is the operating state of the pumped storage unit in the jth time period, (MW);

[0037] Qj is the average generation flow of the pumped storage power station in the jth time period, (m / s); 3

[0038] Qj is the average pumping flow of the pumped storage power station in the jth time period, (m / s); 3

[0039] H ph H is the difference between the upper and lower reservoir water levels of the pumped storage power station, (m);

[0040] η p ηj is the comprehensive output coefficient of the pumped storage power station in the pumping condition;

[0041] η t ηj is the comprehensive output coefficient of the pumped storage power station in the generation condition;

[0042] f2: minimize the total output fluctuation of the system

[0043] ​​​

[0044] where,

[0045] C line is the total capacity of power transmission corridor, (MW);

[0046] b. Decision variables

[0047] with total capacity of corridor C line , time parameter t of piecewise line u and power output parameter P of piecewise line u+1 as decision variables.

[0048] c. Constraints, specifically as follows:

[0049] ① System power balance constraint:

[0050]

[0051] ② Transmission corridor capacity constraint:

[0052] C hydro <C line ≤C line，max

[0053] where, C hydro is the total installed capacity of hydropower station, (MW);

[0054] ③ Total capacity of wind and solar constraint:

[0055] 0<C wp ≤C wp,max

[0056] where, C wp，max is the upper limit of total capacity of wind and solar, (MW);

[0057] ④ Total capacity of pumped storage power station constraint:

[0058] 0<C ph ≤C ph,max

[0059] where, C ph，max is the upper limit of total capacity of wind and solar, (MW);

[0060] ⑤ Pumped storage power station power constraint:

[0061]

[0062] where, are the minimum and maximum output of pumped storage power station in the jth period, (MW), respectively.

[0063] ⑥ Pumped storage power station operating condition constraint:

[0064]

[0065] (6) Reservoir water balance constraint:

[0066]

[0067] where Vj represents the initial reservoir storage at the jth time interval of the day, m3; j 3 ; represents the average inflow to the reservoir at the jth time interval of the day, (m 3 / s); represents the spillage flow at the jth time interval of the day, (m 3 / s); and Δt is the length of the time interval, (h).

[0068] (7) Hydropower station output constraint:

[0069]

[0070] where represents the minimum output of the hydropower station at the jth time interval of the day, (MW); represents the maximum output of the hydropower station at the jth time interval of the day, (MW);

[0071] (8) Hydropower station output ramping constraint:

[0072]

[0073] where UP hydro represents the maximum upward ramping value (increased load) of the output of the hydropower station, (MW); and LP hydro represents the maximum downward ramping value (decreased load) of the output of the hydropower station, (MW).

[0074] (9) Hydropower station allowable discharge flow constraint:

[0075]

[0076] where represents the minimum allowable discharge flow of the hydropower station at the jth time interval of the day, (m 3 / s); represents the maximum allowable discharge flow of the hydropower station at the jth time interval of the day, (m 3 / s);

[0077] (10) Hydropower station power generation head constraint:

[0078]

[0079] where ​Hmin(j) represents the minimum power generation water head of the jth time period in a day of the hydropower station, (m); Hmax(j) represents the maximum power generation water head of the jth time period in a day of the hydropower station, (m);

[0080] Reservoir water level constraint:

[0081]

[0082] In the formula, Hmin(j) represents the lower limit water level of the jth time period in a day of the reservoir, (m); Hmin(j) represents the lower limit water level of the jth time period in a day of the reservoir, (m).

[0083] Initial and final water level constraints of reservoir dispatching period:

[0084] Z1 = Z start Z J = Z end

[0085] In the formula, Z start Z0 represents the initial reservoir water level of the dispatching period, (m); and Z end Z1 represents the final reservoir water level of the dispatching period, (m).

[0086] Total output constraint:

[0087]

[0088] In the formula, C trans，min , and C trans，max are respectively the minimum output and the maximum output allowed to be sent out by the sending channel, (MW).

[0089] Further, in step (5), the wind and light total capacity value as the input variable is set to take an equal increment from the minimum wind and light capacity until the wind and light capacity upper limit value that simultaneously satisfies the maximum power generation of the complementary system and the minimum total output fluctuation of the system is calculated;

[0090] The optimization algorithm adopts one of dynamic programming and its improved algorithm or heuristic algorithm:

[0091] The dynamic programming and its improved algorithm includes discrete differential dynamic programming, successive approximation dynamic programming and successive optimization method.

[0092] The heuristic algorithm includes genetic algorithm, artificial neural network algorithm, particle swarm algorithm and ant colony algorithm.

[0093] Further, in step (6), the capacity configuration method is specifically as follows: an annual time scale index system representing the comprehensive characteristics of the water-electricity-pumping-storage-wind-solar multi-energy complementary system is proposed; a system full life cycle (25 years) evaluation method considering multi-objective cost is established; and a wind-solar capacity and supporting channel capacity configuration scheme is formulated based on the full life cycle evaluation result.

[0094] Advantages

[0095] Compared with the prior art, the advantages brought by the technical scheme of the present application are:

[0096] Compared with the prior art, the advantages brought by the technical scheme of the present application are: the present application proposes a water-electricity-pumping-storage-wind-solar combined power generation system capacity configuration method based on extra-high voltage direct current channel baling and sending out. According to the historical measured daily output process of the built wind power plant and photovoltaic power station in the research area, a typical combined wind power-photovoltaic power daily output process is generated. According to the historical daily runoff data of the hydrological station upstream of the hydropower station, a runoff scenario is generated. According to the characteristics of the extra-high voltage transmission line cross-network power transmission of the large-scale water-electricity-pumping-storage-wind-solar combined power generation system and the regulation capacity of the hydropower station and the pumped storage power station, a two-stage complementary strategy of the water-electricity-pumping-storage-wind-solar combined power generation system is set. A water-electricity-pumping-storage-wind-solar combined power generation system capacity configuration mathematical model is constructed, and an optimization algorithm is used for solving, so as to obtain the full-scenario optimal cooperative operation process of the wind power plant and the photovoltaic power station under different planning installed capacities. A wind-solar capacity and supporting channel capacity configuration method based on the optimization result of the scenario set is proposed, and the optimal capacity configuration scheme of the water-electricity-pumping-storage-wind-solar combined power generation system is determined according to the target orientation of the managers and decision makers.

[0097] The capacity configuration method proposed by the present application considers the characteristics of extra-high voltage transmission and the uncertainty of wind, light and water output, and determines the capacity configuration scheme of the water-electricity-pumping-storage-wind-solar combined power generation system based on full life cycle comprehensive evaluation, which can provide technical support for the planning and construction of the water-electricity-pumping-storage-wind-solar combined power generation system, and is suitable for popularization and application in the capacity configuration of wind power, photovoltaic capacity and supporting sending-out channel capacity of large-scale water-electricity-pumping-storage-wind-solar combined power generation system. BRIEF DESCRIPTION OF DRAWINGS

[0098] Figure 1 The technical scheme of the present application is executed in the flowchart;

[0099] Figure 2 The daily output process of the typical wind-solar scenario under the unit megawatt installed capacity in step (1) of the method of the present application;

[0100] Figure 3 The runoff frequency curve of different seasons in step (2) of the method of the present application;

[0101] Figure 4 A two-stage complementary strategy diagram of the water-electricity-pumped storage-wind-solar hybrid power generation system in step (3) of the method of the present application;

[0102] Figure 5 The system collaborative operation optimization results of all runoff scenarios in a certain wind-solar scenario in step (5) of the method of the present application;

[0103] Figure 6 The system technical property and economic property index calculation results in step (6) of the method of the present application. DETAILED DESCRIPTION

[0104] The following will be combined with the accompanying Figures 1-6 The present application is described as follows:

[0105] In order to further illustrate the technical solutions and features of the present application, the present application will be described in detail below in combination with the accompanying drawings and specific embodiments, but the content of the present application is not limited to the content described in the specific embodiments.

[0106] The present example takes a certain hydropower station and its supporting pumped storage power station as an example, as shown in Figure 1 A water-electricity-pumped storage-wind-solar hybrid power generation system capacity configuration method based on extra-high voltage direct current channel bundling and sending, the specific implementation steps are as follows:

[0107] Step 101, divide the historical measured daily output process (time step is 10 min) of the built wind power plant and photovoltaic power station in the research area according to seasons (spring is March, April and May, summer is June, July and August, autumn is September, October and November, and winter is December, January and February), use Copula function to construct the hourly wind power-photovoltaic output joint probability distribution model of each season, use Latin hypercube sampling method to sample the output data of each season, and obtain the wind-solar joint output data set of each season; generate a large number of wind-solar joint output initial scenario sets satisfying the wind power and photovoltaic output fluctuation characteristics according to the samples of the random characteristics, and use the hourly output fluctuation interval constraint to eliminate the scenarios that do not meet the requirements; finally, use the FCM clustering method of eigenvalue dimension reduction to reduce the initial scenario set, and obtain the typical wind-solar scenario of each season (see Figure 2 ). Adopt the ratio method to obtain the daily output process of the typical joint wind power-photovoltaic output scenario of each season under different planned installed capacities of the wind power plant and photovoltaic power station.

[0108] Step 102, count the frequency of historical daily average runoff of the water power station upstream hydrological station according to seasons (see Figure 3), the area surrounded by each boundary of different probability interval represents the inflow value in the runoff scenario, and finally the runoff scenarios with typicality are obtained (see Table 1).

[0109] Table 1 Inflow value of each runoff scenario and its corresponding probability

[0110]

[0111]

[0112] Step 103, according to the characteristics of UHV power transmission, the total output process of the hydropower-pumped storage-wind-solar hybrid power generation system is divided into U+1 stages by using time parameter, each stage is subdivided into a plurality of time periods according to the decision time step, the output of the hydropower-pumped storage-wind-solar hybrid power generation system in each stage is a constant value, and the characteristic parameters are used to represent the output characteristics of different stages (see Figure 4 );

[0113] Step 104, a mathematical model for capacity configuration of the hydropower-pumped storage-wind-solar hybrid power generation system is constructed.

[0114] The multi-objective optimization model is composed of objective function, decision variable and constraint condition:

[0115] a. Objective function:

[0116] f1: maximize the power generation of complementary system

[0117]

[0118] In the formula:

[0119] is the total output of the complementary system in the jth time period, (MW);

[0120] is the output of the hydropower station in the jth time period, (MW);

[0121] is the joint output of wind power and photovoltaic in the jth time period, (MW);

[0122] is the pumping power of the pumped storage power station in the jth time period, (MW);

[0123] is the power generation of the pumped storage power station in the jth time period, (MW);

[0124] Represents the comprehensive output coefficient of the hydropower station in the jth period, which is related to the unit output and generating head;

[0125] represents the average power generation flow of the hydropower station in the jth period, (m 3 / s);

[0126] represents the average power generation head of the hydropower station in the jth period, (m);

[0127] C wp is the total capacity of wind power and photovoltaic power, (MW);

[0128] γ is the proportion of photovoltaic capacity in the total wind-solar capacity, (MW);

[0129] is the installed capacity of wind power in megawatts in the jth period, (MW);

[0130] is the installed output of PV in megawatts in the jth period, (MW);

[0131] J is the number of time periods in the scheduling period;

[0132] is the operating status of the pumped storage unit in the jth period, (MW);

[0133] represents the average power generation flow of the pumped storage power station in the jth period, (m 3 / s);

[0134] represents the average pumping flow of the pumped storage power station in the jth period, (m 3 / s);

[0135] H ph represents the water level difference between the upper and lower reservoirs of the pumped storage power station, (m);

[0136] η p are the comprehensive output coefficients of the pumped storage power station under pumping conditions;

[0137] η t are the comprehensive output coefficients of the pumped storage power station under power generation conditions;

[0138] f2: Minimize the total system output fluctuation

[0139]

[0140] Where:

[0141] C lineTotal capacity of power transmission corridor, (MW).

[0142] b. Decision variables

[0143] Total capacity of corridor C line Time parameter of polyline t u and output parameter of polyline P u+1 are decision variables.

[0144] c. Constraints, as follows:

[0145] ① System power balance constraint:

[0146]

[0147] ② Transmission corridor capacity constraint:

[0148] C hydro <C line ≤C line，max

[0149] In the formula, C hydro is the total installed capacity of hydropower station, (MW).

[0150] ③ Wind and light total capacity constraint:

[0151] 0<C wp ≤C wp,max

[0152] In the formula, C wp，max is the upper limit of wind and light total capacity, (MW).

[0153] ④ Pumped storage power station total capacity constraint:

[0154] 0<C ph ≤C ph，max

[0155] In the formula, C ph，max is the upper limit of wind and light total capacity, (MW).

[0156] ⑤ Pumped storage power station power constraint:

[0157]

[0158] In the formula, are the minimum and maximum output of pumped storage power station in the jth period, (MW).

[0159] ⑥ Pumped storage power station working condition constraint:

[0160]

[0161] ⑦ Reservoir water balance constraint:

[0162]

[0163] where V j represents the initial reservoir storage at the jth time period of the day, m 3 ; represents the average inflow to the reservoir at the jth time period of the day, (m 3 / s); represents the spillage at the jth time period of the day, (m 3 / s); and Δt is the length of the time period, (h).

[0164] (8) Power output constraints of the hydropower station:

[0165]

[0166] where represents the minimum power output of the hydropower station at the jth time period of the day, (MW); represents the maximum power output of the hydropower station at the jth time period of the day, (MW);

[0167] (9) Power output ramping constraints of the hydropower station:

[0168]

[0169] where UP hydro represents the maximum upward ramping value (increased load) of the power output of the hydropower station, (MW); and LP hydro represents the maximum downward ramping value (decreased load) of the power output of the hydropower station, (MW).

[0170] (10) Discharge constraints of the hydropower station:

[0171]

[0172] where represents the minimum discharge allowed at the jth time period of the day, (m 3 / s); represents the maximum discharge allowed at the jth time period of the day, (m 3 / s).

[0173] Power generation head constraints of the hydropower station:

[0174]

[0175] where represents the minimum power generation head at the jth time period of the day, (m); represents the maximum power generation head at the jth time period of the day, (m).

[0176] Reservoir water level constraints:

[0177]

[0178] wherein, represents the lower limit of the water level of the reservoir in the jth period of the day, (m); represents the lower limit of the water level of the reservoir in the jth period of the day, (m).

[0179] Reservoir water level constraints at the beginning and end of the dispatching period:

[0180] Z1= Z start Z J = Z end

[0181] wherein, Z start represents the initial reservoir water level, (m); Z end represents the final reservoir water level, (m).

[0182] Total output constraint:

[0183]

[0184] wherein, C trans，min and C trans，max are the minimum and maximum output allowed by the sending channel, respectively, (MW).

[0185] Step 105, combine the typical wind-solar photovoltaic scenario obtained in step (1) and the runoff scenario obtained in step (2), and take the wind power and solar photovoltaic capacity ratio as the input variable of the multi-objective optimization model established in step (4), solve by using an optimization algorithm, obtain the optimal coordinated operation mode of the hydropower-pumping storage-wind-solar photovoltaic combined power generation system under all scenarios, and calculate the output process (see Figure 5 ).

[0186] Step 106, calculate and count the technical and economic characteristic indexes of the hydropower-pumping storage-wind-solar photovoltaic combined power generation system under all scenarios. According to the goal orientation of the managers and decision makers, determine the optimal capacity configuration scheme of the hydropower-pumping storage-wind-solar photovoltaic combined power generation system (see Figure 6 ). For example, if the goal orientation of the managers and decision makers is greater economic benefit of the system, the optimal configuration scheme of the hydropower-pumping storage-wind-solar photovoltaic combined power generation system is: wind power 3000 MW, solar photovoltaic 1500 MW, and supporting channel capacity 3700 MW.

[0187] Although the present application has been described above with reference to specific embodiments, the above embodiments are merely illustrative and not restrictive, and many modifications and other embodiments of the present application can occur to those skilled in the art upon reading the foregoing description, which modifications and other embodiments fall within the scope of the present application.

Claims

1. A method for capacity configuration of a hydropower-pumped storage-wind-solar combined power generation system, characterized in that: The steps include: Step (1) divide the historical measured daily output of wind farms and photovoltaic power stations in the study area into four categories according to season, and generate typical wind power and photovoltaic output scenarios respectively; Step (2) divides the historical average daily runoff data of the hydrological station upstream of the hydropower station into four categories according to season, calculates the frequency of the historical average daily runoff, and selects the inflow corresponding to the typical frequency according to the runoff frequency distribution characteristics to generate the runoff scenario for each season; Step (3): Based on the characteristics of cross-grid power transmission of ultra-high voltage transmission lines of large-scale hydropower-pumped storage-wind-solar combined power generation system, and taking into account the uncertainty of wind power output, photovoltaic output and reservoir runoff, and the output characteristics of hydropower and pumped storage units, the total output process of the hydropower-pumped storage-wind-solar combined power generation system under the ultra-high voltage transmission demand is described using time parameters and characteristic parameters, and a two-stage complementary strategy of hydropower coordinated pumped storage and complementary wind and solar operation is set; Step (4): constructing a capacity optimization configuration mathematical model for the hydropower-pumped storage-wind-solar multi-energy complementary system based on the complementary strategy of step (3); the capacity optimization configuration mathematical model for the hydropower-pumped storage-wind-solar multi-energy complementary system is a multi-objective optimization model, which is composed of an objective function, decision variables and constraints: wherein: The objective function: : Maximize the power generation of complementary systems; ； ； ； ； Where: For the complementary system Total output in each period, (MW); For the hydropower station Output in each period, (MW); For wind power and photovoltaic Combined power output in each period, (MW); For pumped storage power station Pumping power in each period, (MW); For pumped storage power station Power generation in each period, (MW); Representing the hydropower station The comprehensive output coefficient of each period is related to the unit output and generating head; Representing the hydropower station The average power generation flow in each period, (m 3 / s); Representing the hydropower station Average power generation head in each period, (m); is the total capacity of wind power and photovoltaic power, (MW); is the proportion of photovoltaic capacity in the total wind-solar capacity, (MW); For wind power in The installed power output per unit time period is megawatt (MW); For photovoltaic The installed power output per unit time period is megawatt (MW); is the number of time periods in the scheduling period; Representative of pumped storage power station The average power generation flow in each period, (m 3 / s); Representative of pumped storage power station Average pumping flow rate per period, (m 3 / s); represents the water level difference between the upper and lower reservoirs of the pumped storage power station, (m); are the comprehensive output coefficients of the pumped storage power station under pumping conditions; are the comprehensive output coefficients of the pumped storage power station under power generation conditions; : Minimize the total system output fluctuation; ； Where: is the total capacity of the power transmission channel (MW); Step (5), using the typical wind power-photovoltaic combined scenario daily power generation process obtained in step (1) and the typical runoff scenario obtained in step (2) as input variables of the multi-objective optimization model established in step (4), using the multi-objective optimization algorithm to solve the model, and obtaining the full-scenario optimal coordinated operation model of the wind farm and the photovoltaic power station under different planned installed capacity conditions; calculating the daily power generation of the hydropower station and the pumped storage power station and the channel delivery power according to the full-scenario optimal coordinated operation model; In step (6), a wind / solar capacity and supporting channel capacity configuration method based on the scenario set optimization results is used to formulate a wind / solar capacity and supporting channel capacity configuration plan based on the full scenario optimal coordinated operation results obtained in step (5).

2. A method for capacity configuration of a hydropower-pumped storage-wind-solar combined power generation system according to claim 1, characterized in that: In step (1), the process of generating typical wind power and photovoltaic output scenarios includes: Use Copula function to build a joint probability distribution model of wind power and photovoltaic power output in each season and time period; The Latin hypercube sampling method was used to sample the output data of each season and period, and the wind and solar power combined output data set of each season was obtained. Based on the random samples obtained by sampling, a large number of initial scenarios of wind-solar combined output that meet the fluctuation characteristics of wind power and photovoltaic output are generated; The FCM clustering method with eigenvalue dimensionality reduction was used to reduce the initial scenario set and obtain a typical wind-solar combined output scenario.

3. The method for capacity configuration of a hydropower-pumped storage-wind-solar combined power generation system according to claim 1, characterized in that: In step (3), the two-stage complementary strategy includes: In the first complementary regulation stage, pumped storage complements the wind and solar power output, transforming the wind and solar power output curves into a multi-segment line. In each segment of the multi-segment line, when the output of that segment is greater than the wind and solar power output, pumped storage generates electricity; when the output of that segment is less than the wind and solar power output, pumped storage pumps water. In the second complementary regulation stage, hydropower makes complementary adjustments to the multi-segment line output obtained in the first stage, compensating it into a U+1 segment line; where: The U+1 segment line divides the total output process of the hydropower-pumped storage-wind-solar combined power generation system into U+1 stages using U time parameters based on the ultra-high voltage transmission characteristics. Each stage is subdivided into several time periods based on the decision time step. The total output of the hydropower-pumped storage-wind-solar combined power generation system in all time periods within each stage is a constant value, and characteristic parameters are used to characterize the output characteristics of different stages.

4. The method for capacity configuration of a hydropower-pumped storage-wind-solar combined power generation system according to claim 1, characterized in that: In step (4), the capacity optimization configuration mathematical model of the hydropower-pumped storage-wind-solar multi-energy complementary system is a multi-objective optimization model whose decision variables and constraints are: Decision variables: Total channel capacity , time parameters of polylines and the output parameters of the polyline is the decision variable; The constraints are as follows: System power balance constraints: ； Outgoing channel capacity constraints: ； Where, is the total installed capacity of the hydropower station, (MW); Constraints on total wind and solar capacity: ； Where, is the upper limit of total wind and solar capacity (MW); Total capacity constraints of pumped storage power stations: ； Where, is the upper limit of total wind and solar capacity (MW); Power constraints of pumped storage power stations: ； Where, 、 Pumped storage power station Minimum and maximum output of the time period (MW); Pumped storage power station operating constraints: ； Reservoir water balance constraints: ； Where, Reservoir Day The initial storage capacity of each period, m 3 ; On behalf of the hydropower station Average inflow flow in each period, (m 3 / s); On behalf of the hydropower station The amount of water discarded in each period, (m 3 / s); is the duration of a period, (h); Hydropower station output constraints: ； Where, On behalf of the hydropower station Minimum output during the period (MW); On behalf of the hydropower station Maximum output during the period (MW); Hydropower station output ramp constraints: ； Where, Represents the maximum value of the hydropower station's output ramping up (load increase), (MW); Represents the maximum output of the hydropower station when it ramps down (load reduction), (MW); Constraints on the discharge flow allowed by a hydropower station: ； Where, On behalf of the hydropower station The minimum discharge flow allowed during the period (m 3 / s); On behalf of the hydropower station The maximum discharge flow allowed during the period (m 3 / s); ⑪ Constraints on generating head of hydropower station: ； Where, On behalf of the hydropower station Minimum generating head during the period, (m); On behalf of the hydropower station Maximum generating head during the period, (m); ⑫Reservoir water level constraints: ； Where, Reservoir Day Lower limit water level of the time period, (m); Reservoir Day Lower limit water level of the time period, (m); ⑬ Constraints on water levels at the beginning and end of the reservoir operation period: ； Where, represents the initial reservoir water level during the reservoir operation period, (m); represents the reservoir water level at the end of the reservoir operation period, (m); ⑭Total output constraint: ； Where, 、 They are the minimum and maximum outputs allowed by the output channel, respectively (MW).

5. The method for capacity configuration of a hydropower-pumped storage-wind-solar combined power generation system according to claim 1, characterized in that: In step (5), the total wind and solar capacity value as the input variable is set to start from the minimum wind and solar capacity, and to increase in equal value until the wind and solar capacity upper limit value that satisfies both the maximum power generation of the complementary system and the minimum fluctuation of the total output of the system is obtained; The optimization algorithm adopts one of dynamic programming and its improved algorithm or heuristic algorithm: The dynamic programming and its improved algorithm include discrete differential dynamic programming, successive progressive dynamic programming and successive optimization method; The heuristic algorithms include genetic algorithm, artificial neural network algorithm, particle swarm algorithm and ant colony algorithm.

6. The method for capacity configuration of a hydropower-pumped storage-wind-solar combined power generation system according to claim 1, characterized in that: In step (6), the capacity configuration includes: proposing an annual time scale indicator system to characterize the comprehensive characteristics of the hydropower-pumped storage-wind-solar multi-energy complementary system; establishing a system full life cycle evaluation method considering multi-object costs; and formulating a wind and solar capacity and supporting channel capacity configuration plan based on the full life cycle evaluation results.

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