Water-wind-light complementary strategy optimization method and system based on large-scale water-wind-light cluster

Abstract

The invention discloses a water-wind-light complementary strategy optimization method and system based on a large-scale water-wind-light cluster, and belongs to the technical field of power system optimization scheduling. The method comprises the steps of performing generalization processing on a water-wind-light complementary power system optimization object of a large-scale water-wind-light cluster through a power grid aggregation model and power supply cluster division to obtain a generalized optimization object; establishing constraint conditions of the water-wind-light complementary power system, wherein the constraint conditions comprise power transmission channel constraint, wind-light output constraint and water-electricity constraint; constructing a complementary strategy optimization model of the water-wind-light complementary power system by taking maximization of the dry-period supply conservation capacity of the cascade water-wind-light system and maximization of the water-wind-light annual energy output as objective functions and combining constraint conditions; and solving the complementary strategy optimization model of the water-wind-light complementary power system to obtain a complementary strategy of the water-wind-light complementary power system. According to the method, the optimization modeling accuracy and the calculation efficiency of the large-scale system are improved, and the multi-target optimization of the water-wind-light complementary power generation based on the large-scale water-wind-light cluster is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of power system optimization and dispatching, and in particular to a method and system for optimizing a complementary strategy for a water-wind-solar complementary power system based on a large-scale water-wind-solar cluster. Background Art

[0004] The technical problems to be solved mainly include:

[0005] The dispatching scale is large, and the optimization algorithm modeling is difficult. The water-wind-solar complementary system based on large-scale water-wind-solar clusters has a complex grid structure and a large-scale power station. Especially for new energy power stations, the dispatching of power generation for large-scale power station clusters faces not only technical difficulties such as unified management and maintenance of massive operation information, but also basic theoretical problems such as the accuracy and computational efficiency of large-scale system optimization modeling. Taking a single power station as the control point and optimizing the entire domain uniformly will greatly increase the modeling complexity and solution efficiency of power production organization strategies, affect the accuracy of the optimization results, and bring great uncertainty to the preparation of power grid power generation plans and dispatching operations.

[0006] The optimization goal is not single. The optimization goal of the daily scheduling of hydro-wind-solar complementarity is not single, but a multi-objective optimization problem.

[0007] Prior art document 1 (CN117543721B) discloses an optimization scheduling method, device, equipment and medium for a cascade hydropower-wind-solar complementary system. Its shortcomings are that the optimization scope is small, and only the optimization of a small-scale cascade hydropower station and wind-solar complementary system is considered; there is a lack of consideration of different periods of hydropower during the wet and dry seasons, and it is impossible to guarantee the impact of the fluctuation of hydropower output during the dry season on the power grid; the result is only the output plan is calculated, and the operating control range of the reservoir water level is not optimized; the output of the hydropower-wind-solar complementary system is mostly a nonlinear target. Although this patent has been processed and optimized with a linearized algorithm, it is far inferior to the solution speed and accuracy of the PSO step-by-step optimization algorithm, which is more in line with the characteristics of hydropower output. Summary of the invention

[0008] In order to address the deficiencies in the prior art, the present invention proposes a complementary strategy optimization method and system for a water-wind-photovoltaic complementary power system based on a large-scale water-wind-photovoltaic cluster. Taking maximizing the dry season supply capacity of the cascaded water-wind-photovoltaic system and maximizing the annual power generation of water, wind and photovoltaic power as the objective function, an optimization model for the complementary strategy of a water-wind-photovoltaic complementary power system based on a large-scale water-wind-photovoltaic cluster is established. This method and system can provide a hydropower-wind-photovoltaic complementary power system power generation plan that meets the constraints, thereby improving the system's dry season power supply capacity and clean energy utilization rate.

[0009] The present invention adopts the following technical solution.

[0010] The first aspect of the present invention proposes a water-wind-solar complementary strategy optimization method based on a large-scale water-wind-solar cluster, comprising:

[0011] Through the grid aggregation model and power cluster division, the optimization object of the hydro-wind-solar complementary power system of the large-scale hydro-wind-solar cluster is generalized to obtain the generalized optimization object;

[0012] According to the generalized optimization object, the objective function is constructed with the goal of maximizing the dry season supply capacity of the cascade hydro-wind-solar system and maximizing the annual power generation of hydro-wind-solar. Combined with the constraints of the hydro-wind-solar complementary power system, the complementary strategy optimization model of the hydro-wind-solar complementary power system is constructed.

[0013] Solve the constructed complementary strategy optimization model of the hydro-wind-solar complementary power system, obtain the complementary strategy of the hydro-wind-solar complementary power system, and realize the optimization of the hydro-wind-solar complementary strategy based on large-scale hydro-wind-solar clusters.

[0014] Preferably, a power grid aggregation model is established, specifically including:

[0015] Considering the power balance of the power grid: The power balance analysis of the power grid is not affected before and after the establishment of the power grid aggregation model;

[0016] Omit the topology and geographical location in the grid aggregation model: The detailed grid topology is not considered, and each power source and load is no longer affected by its physical location;

[0017] Describe the generation constraints of the grid aggregation model;

[0018] Set the number of grid aggregation models included in the target grid: Calculate whether the target grid contains one or more aggregated grids;

[0019] Describe logical relationships: Describe the logical relationships between aggregated power grids according to the actual power grid operation status;

[0020] Aggregate power generation equipment and compliant equipment: When the aggregated grid contains one or more wind power stations, they are combined into the total wind power output; when the aggregated grid contains one or more photovoltaic power stations, they are combined into the total photovoltaic power output; when the aggregated grid contains one or more thermal power stations, they are combined into the total thermal power output; the loads within the aggregated grid are combined into the total load.

[0021] Preferably, the power cluster division specifically includes:

[0022] Hydropower units: Hydropower units of 100MW and above are modeled separately, and small hydropower units below 100MW are modeled as one unit;

[0023] For wind power, centralized wind power in the aggregated power grid is modeled as one unit, and distributed wind power is modeled as one power station;

[0024] Photovoltaic: centralized photovoltaic in the aggregated power grid is modeled as one unit, and distributed photovoltaic is modeled as one power station.

[0025] Preferably, the constraints of the water-wind-solar complementary power system include transmission channel constraints, wind-solar output constraints and hydropower constraints, among which wind-solar output constraints include wind power output constraints and photovoltaic output constraints; hydropower constraints include unit output constraints, reservoir water level daily fluctuation constraints, downstream flow constraints, power generation flow constraints and unit daily power generation constraints. Preferably, the complementary optimization model of the water-wind-solar complementary power system includes an objective function with the goal of maximizing the dry season supply capacity of the cascade water-wind-solar system, which is expressed as the following formula:

[0026]

[0027] in,

[0028] F is the output fluctuation index of the cascade water, wind and solar power system during the dry season,

[0029] The average output of cascade water and wind power during the dry season, which is from November to May of the following year.

[0030] T 1 is the total number of time periods, the time period is from November to May of the next year, T 1 =7,

[0031] pv, w, h are the numbers of the photovoltaic, wind and hydropower stations respectively.

[0032] PV, W, and H are the total number of solar, wind, and hydropower stations, respectively.

[0033] For the tth 1 The photovoltaic output of the time period,

[0034] For the tth 1 Wind power output during the period,

[0035] k h is the output coefficient of the hth hydropower station,

[0036] Q h,t1 The hth hydropower station is located at the tth 1 The power generation flow during the period,

[0037] H h,t1 The hth hydropower station is located at the tth 1 Output head during the period.

[0038] Preferably, the complementary optimization model of the hydro-wind-solar complementary power system includes an objective function with the goal of maximizing the annual power generation of hydro-wind-solar, which is expressed by the following formula:

[0039]

[0040] In the formula,

[0041] E is the total power generation of cascade hydropower, wind and solar power during the period,

[0042] T is the total number of time periods,

[0043] pv, w, h are the numbers of the photovoltaic, wind and hydropower stations respectively.

[0044] PV, W, and H are the total number of solar, wind, and hydropower stations, respectively.

[0045] N pv,t is the photovoltaic output in period t,

[0046] N w,t is the wind power output in period t,

[0047] k h is the output coefficient of the hth hydropower station,

[0048] Q h,t is the power generation flow of the h-th hydropower station in the t-th period,

[0049] H h,t is the output water head of the h-th hydropower station in the t-th period,

[0050] m t is the number of hours in the tth period.

[0051] Preferably, the PSO algorithm of the Sigmoid function is used to solve the complementary strategy optimization model of the water-wind-solar complementary power system to obtain the optimization strategy results, including the medium- and long-term water level utilization mode of the reservoir, the medium- and long-term power generation output plan of the reservoir, and the wind power and photovoltaic output plan of the system. Among them, the medium- and long-term water level utilization mode of the reservoir includes the water level control intervals before the flood season, at the end of the flood season and at the end of the year.

[0052] The second aspect of the present invention proposes a water-wind-solar complementary strategy optimization system based on a large-scale water-wind-solar cluster, which is used to run the water-wind-solar complementary strategy optimization method based on a large-scale water-wind-solar cluster, including:

[0053] Generalized optimization object module: used to generalize the optimization object of the hydro-wind-solar complementary power system of a large-scale hydro-wind-solar cluster through the grid aggregation model and power cluster division to obtain the generalized optimization object;

[0054] Establish a constraint condition module to establish the constraint conditions for optimizing the complementary strategy of the hydro-wind-solar complementary power system based on a large-scale hydro-wind-solar cluster, including channel constraints, hydropower constraints, and wind-solar output constraints;

[0055] Constructing optimization model module: It is used to construct a complementary strategy optimization model for the water-wind-solar complementary power system, taking the maximization of the dry season supply capacity of the cascaded water-wind-solar system and the maximization of the annual power generation of water-wind-solar as the objective function, and combining the constraints;

[0056] Optimization model solving module: used to solve the optimization model of the complementary strategy of the hydro-wind-solar complementary power system, obtain the complementary strategy of the hydro-wind-solar complementary power system, and realize the optimization of the hydro-wind-solar complementary strategy based on large-scale hydro-wind-solar clusters.

[0057] An electronic device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the computer program is loaded into the processor, the method for optimizing a water-wind-solar complementary strategy based on a large-scale water-wind-solar cluster is implemented.

[0058] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements a method for optimizing a water-wind-solar complementary strategy based on a large-scale water-wind-solar cluster.

[0059] The beneficial effect of the present invention is that, compared with the prior art, the present invention relates to a large-scale hydro-wind-solar cluster, and based on the object generalization technology of the hydro-wind-solar complementary power system, the grid power is aggregated and generalized, and a large-scale hydro-wind-solar cluster grid power aggregate generalization model is established, which reduces the difficulty of optimization modeling and solution;

[0060] Taking the maximization of the dry season supply capacity of the cascaded hydro-wind-solar system and the maximization of the annual power generation of hydro-wind-solar as the objective function, based on the channel constraints, hydropower constraints and wind-solar output constraints, an optimization model of the complementary strategy of the hydro-wind-solar complementary power system based on a large-scale hydro-wind-solar cluster is established. The maximum power generation and the dry season supply capacity are taken as the objective functions, that is, the power generation benefits are taken into account while the impact of the dry season hydro-wind-solar output fluctuations on the power grid is fully considered;

[0061] The PSO algorithm using the Sigmoid function is used to gradually optimize the algorithm to quickly and accurately solve the complementary strategy optimization model of the water-wind-solar complementary power system, including the medium- and long-term water level application mode of the reservoir, the medium- and long-term power generation output plan of the reservoir, and the system wind power and photovoltaic output plan. The medium- and long-term water level application mode of the reservoir includes the water level control intervals before the flood season, at the end of the flood season and at the end of the year. Solving the model can obtain the complementary optimization strategy of the water-wind-solar complementary power system, and can give a power generation plan for the hydropower-wind-photovoltaic complementary power system that meets the constraints. It also includes the operation control interval of the reservoir water level, which is more conducive to the optimization of the complementary control strategy of hydropower in the large-scale cluster water-wind-solar complementary system, improve the system's power supply capacity and clean energy utilization rate during the dry season, reduce wind and light abandonment, realize the resource integration of the new energy power generation system, ensure the smooth power supply and safe and stable operation of the power grid, and improve the accuracy and calculation efficiency of the large-scale system optimization modeling by clustering large-scale new energy power stations, while realizing multi-objective optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a flow chart of the present invention;

[0063] Figure 2 It is a system diagram of the present invention. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0065] like Figure 1 As shown, Embodiment 1 of the present invention provides a method for optimizing a complementary strategy of a water-wind-solar complementary power system based on a large-scale water-wind-solar cluster, comprising the following steps:

[0066] Step 1: Generalize the optimization object of the hydro-wind-solar complementary power system based on a large-scale hydro-wind-solar cluster to obtain the generalized optimization object. The generalization includes grid aggregation and power cluster division.

[0067] In order to reduce the modeling complexity and calculation difficulty of the optimization model, the hydro-wind-solar complementary power system is generalized, including two parts: grid aggregation and power cluster division.

[0068] A grid aggregation model is established, and the wind power stations, photovoltaic power stations and thermal power stations in the aggregated grid are merged into the total wind power output, the total photovoltaic power output and the total thermal power output respectively, and the loads in the aggregated grid are merged into the total load.

[0069] Principles for establishing power grid aggregation model:

[0070] 1) The power balance analysis of the power grid will not be affected before and after the establishment of the power grid aggregation model;

[0071] 2) The detailed grid topology is not considered in the grid aggregation model, and each power source and load is no longer affected by its physical location;

[0072] 3) Grid aggregation model describes the generation constraints;

[0073] 4) The grid aggregation model is the basis for subsequent research, and the target grid for calculation includes one or more aggregated grids;

[0074] 5) The logical relationship between aggregated power grids is consistent with the actual power grid operation;

[0075] 6) When the aggregated grid contains multiple wind power stations, they shall be combined into the total wind power output; when the aggregated grid contains multiple photovoltaic power stations, they shall be combined into the total photovoltaic power output; when the aggregated grid contains multiple thermal power stations, they shall be combined into the total thermal power output. The loads in the aggregated grid should be combined into the total load.

[0076] Power cluster division:

[0077] Hydropower units: Hydropower units of 100MW and above are modeled separately, and small hydropower units below 100MW are modeled as one unit.

[0078] Wind power: The centralized wind power in the aggregated power grid is modeled as one unit; the distributed wind power is modeled as one power station.

[0079] Photovoltaic: The centralized photovoltaic system in the aggregated power grid is modeled as one unit; the distributed photovoltaic system is modeled as one power station.

[0080] Step 2: Establish the constraints of the hydropower-wind-solar hybrid power system, including transmission channel constraints, hydropower constraints, and wind-solar output constraints;

[0081] The transmission channel constraint is expressed as follows:

[0082]

[0083] Where:

[0084] L is the number of wind power stations,

[0085] K is the number of photovoltaic power stations,

[0086] J is the number of hydropower stations,

[0087] is the transmission capacity of the dth transmission section;

[0088] w l,t is the output of the lth wind power station in the tth period;

[0089] sN k,t is the output of the k-th photovoltaic power station in the t-th period;

[0090] HkD j,t is the output of the j-th hydropower station in the t-th period.

[0091] Wind power output constraint is expressed as follows:

[0092]

[0093] Where:

[0094] T is the total number of time periods,

[0095] is the installed capacity of the lth wind power station;

[0096] g l,t is the output coefficient of the lth wind power station in period t;

[0097] is the minimum output of the lth wind power station in period t;

[0098] is the maximum output of the lth wind power station in period t;

[0099] The meanings of other parameters are the same as above.

[0100] The photovoltaic output constraint is expressed as follows:

[0101]

[0102] Where:

[0103] sN k,t The output of the k-th photovoltaic power station during period t;

[0104] is the installed capacity of the kth photovoltaic power station;

[0105] f k,t is the output coefficient of the kth photovoltaic power station in period t;

[0106] is the minimum output of the k-th photovoltaic power station during period t;

[0107] is the maximum output of the k-th photovoltaic power station during period t;

[0108] The meanings of other parameters are the same as above.

[0109] Hydropower constraints include unit output constraints, reservoir water level daily fluctuation constraints, discharge flow constraints, power generation flow constraints and unit daily power generation constraints.

[0110] The unit output constraint is expressed as follows:

[0111] P h,min ≤P h (t)≤P h,max (4)

[0112] Where:

[0113] P h (t) output of hydroelectric generating units;

[0114] P h,min and P h,max Provide the minimum and maximum technical output for the unit.

[0115] The daily fluctuation constraint of reservoir water level is expressed by the following formula:

[0116]

[0117] Where:

[0118] J0 is the number of reservoirs,

[0119] Z j0,end is the end-of-day water level of the j0th reservoir,

[0120] Z j0,begin is the initial water level of the j0th reservoir at the beginning of the day,

[0121] Z j0,allow is the daily water level variation allowed for the j0th reservoir;

[0122] The downstream flow constraint is expressed as follows:

[0123]

[0124] Where:

[0125] Q j,t is the discharge flow of the j-th hydropower station in the t-th period;

[0126] is the maximum discharge flow of the jth hydropower station in the tth period;

[0127] is the minimum discharge flow of the j-th hydropower station in the t-th period.

[0128] The power generation flow constraint is expressed as follows:

[0129]

[0130] Where:

[0131] is the maximum power generation flow of the jth hydropower station in the tth period;

[0132] is the minimum power generation flow of the jth hydropower station in the tth period;

[0133] The meanings of other parameters are the same as above.

[0134] The daily power generation constraint of the unit is expressed as follows:

[0135]

[0136] Where:

[0137] P h (t) is the output of the hydropower unit at time t0,

[0138] ΔT is the step length,

[0139] Q h The daily power generation of the unit.

[0140] Step 3: Taking the maximization of the dry season supply capacity of the cascaded hydro-wind-solar system and the maximization of the annual power generation of hydro-wind-solar as the objective function, combined with the constraints of step 2, a complementary optimization model of the hydro-wind-solar complementary power system is constructed;

[0141] The complementary optimization model of the hydro-wind-solar complementary power system includes an objective function that aims to maximize the dry season supply capacity of the cascade hydro-wind-solar system, which is expressed as the following formula:

[0142]

[0143] in,

[0144] F is the output fluctuation index of the cascade water, wind and solar power system during the dry season,

[0145] The average output of cascade water and wind power during the dry season, which is from November to May of the following year.

[0146] T 1 is the total number of time periods, the time period is from November to May of the next year, T 1 =7,

[0147] pv, w, h are the numbers of the photovoltaic, wind and hydropower stations respectively.

[0148] PV, W, and H are the total number of solar, wind, and hydropower stations, respectively.

[0149] For the tth 1 The photovoltaic output of the time period,

[0150] For the tth 1 Wind power output during the period,

[0151] k h is the output coefficient of the hth hydropower station,

[0152] Q h,t1 The hth hydropower station is located at the tth 1 The power generation flow during the period,

[0153] H t,t1 The hth hydropower station is located at the tth 1 Output head during the period.

[0154] The complementary optimization model of the hydro-wind-solar complementary power system includes an objective function with the goal of maximizing the annual power generation of hydro-wind-solar, which is expressed as the following formula:

[0155]

[0156] In the formula,

[0157] E is the total power generation of cascade hydropower, wind and solar power during the period,

[0158] T is the total number of time periods,

[0159] pv, w, h are the numbers of the photovoltaic, wind and hydropower stations respectively.

[0160] PV, W, and H are the total number of solar, wind, and hydropower stations, respectively.

[0161] N pv,t is the photovoltaic output in period t,

[0162] N w,t is the wind power output in period t,

[0163] k h is the output coefficient of the hth hydropower station,

[0164] Q h,t is the power generation flow of the h-th hydropower station in the t-th period,

[0165] H h,t is the output water head of the h-th hydropower station in the t-th period,

[0166] m t is the number of hours in the tth period.

[0167] Step 4: Use the PSO algorithm with Sigmoid function to solve the coordinated optimization problem of the water-wind-solar complementary strategy, including the two goals of maximizing the supply capacity during the dry season and maximizing the annual power generation of water, wind and solar, and obtain the optimization strategy results.

[0168] The PSO algorithm with Sigmoid function is used to solve the coordinated optimization problem of the complementary strategy of the water-wind-solar complementary power system, including the two goals of maximizing the supply capacity during the dry season and maximizing the annual power generation of water, wind and solar. The optimization strategy results are obtained, including the medium- and long-term water level utilization mode of the reservoir, especially the water level control range before the flood season, at the end of the flood season and at the end of the year, the medium- and long-term power generation output plan of the reservoir, and the system wind power and photovoltaic output plan.

[0169] The beneficial effect of the present invention is that, compared with the prior art, the present invention relates to a large-scale hydro-wind-solar cluster, and based on the object generalization technology of the hydro-wind-solar complementary power system, the grid power is aggregated and generalized, and a large-scale hydro-wind-solar cluster grid power aggregate generalization model is established, which reduces the difficulty of optimization modeling and solution;

[0170] Taking the maximization of the dry season supply capacity of the cascaded hydro-wind-solar system and the maximization of the annual power generation of hydro-wind-solar as the objective function, based on the channel constraints, hydropower constraints and wind-solar output constraints, an optimization model of the complementary strategy of the hydro-wind-solar complementary power system based on a large-scale hydro-wind-solar cluster is established. The maximum power generation and the dry season supply capacity are taken as the objective functions, that is, the power generation benefits are taken into account while the impact of the dry season hydro-wind-solar output fluctuations on the power grid is fully considered;

[0171] The PSO algorithm using the Sigmoid function is used to gradually optimize the algorithm to quickly and accurately solve the complementary strategy optimization model of the water-wind-solar complementary power system, including the medium- and long-term water level application mode of the reservoir, the medium- and long-term power generation output plan of the reservoir, and the system wind power and photovoltaic output plan. The medium- and long-term water level application mode of the reservoir includes the water level control intervals before the flood season, at the end of the flood season and at the end of the year. Solving the model can obtain the complementary optimization strategy of the water-wind-solar complementary power system, and can give a power generation plan for the hydropower-wind-photovoltaic complementary power system that meets the constraints. It also includes the operation control interval of the reservoir water level, which is more conducive to the optimization of the complementary control strategy of hydropower in the large-scale cluster water-wind-solar complementary system, improve the system's power supply capacity and clean energy utilization rate during the dry season, reduce wind and light abandonment, realize the resource integration of the new energy power generation system, ensure the smooth power supply and safe and stable operation of the power grid, and improve the accuracy and calculation efficiency of the large-scale system optimization modeling by clustering large-scale new energy power stations, while realizing multi-objective optimization.

[0172] like Figure 2 As shown, in Example 2 of the present invention, a water-wind-solar complementary power system complementary strategy optimization system based on a large-scale water-wind-solar cluster is proposed, which is used to run the water-wind-solar complementary power system complementary strategy optimization method based on a large-scale water-wind-solar cluster described in Example 1, including:

[0173] The generalized optimization object module generalizes the hydro-wind-solar hybrid power system to reduce the modeling complexity and calculation difficulty of the optimization model, including grid aggregation and power cluster division;

[0174] Establish a constraint condition module to establish the constraint conditions for optimizing the complementary strategy of the hydro-wind-solar complementary power system based on a large-scale hydro-wind-solar cluster, including channel constraints, hydropower constraints, and wind-solar output constraints;

[0175] Construct an optimization model module, and according to the constraints, build an optimization model for the complementary strategy of the water-wind-solar complementary power system with the objective function of maximizing the supply capacity of the cascade water-wind-solar system during the dry season and maximizing the annual power generation of the water-wind-solar system;

[0176] Solve the optimization model module and use the PSO algorithm of Sigmoid function to solve the coordinated optimization problem of the complementary strategy of the water-wind-solar complementary power system, including the two goals of maximizing the supply capacity during the dry season and maximizing the annual power generation of water, wind and solar. The optimization strategy results are obtained, including the medium- and long-term water level application mode of the reservoir, especially the water level control range before the flood season, at the end of the flood season and at the end of the year, the medium- and long-term power generation output plan of the reservoir, and the system wind power and photovoltaic output plan.

[0177] Embodiment 3 of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when loaded into the processor, implements a method for optimizing a water-wind-solar complementary strategy based on a large-scale water-wind-solar cluster as described in Embodiment 1.

[0178] Embodiment 4 of the present invention provides a computer-readable storage medium, which stores a computer program, and is characterized in that when the computer program is executed by a processor, it implements the method for optimizing the water-wind-solar complementary strategy based on a large-scale water-wind-solar cluster as described in Embodiment 1.

[0179] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A water-wind-solar complementary strategy optimization method based on a large-scale water-wind-solar cluster, characterized in that: include: Through the grid aggregation model and power cluster division, the optimization object of the hydro-wind-solar complementary power system of the large-scale hydro-wind-solar cluster is generalized to obtain the generalized optimization object; According to the generalized optimization object, the objective function is constructed with the goal of maximizing the dry season supply capacity of the cascade hydro-wind-solar system and maximizing the annual power generation of hydro-wind-solar. Combined with the constraints of the hydro-wind-solar complementary power system, the complementary strategy optimization model of the hydro-wind-solar complementary power system is constructed. Solve the constructed complementary strategy optimization model of the hydro-wind-solar complementary power system, obtain the complementary strategy of the hydro-wind-solar complementary power system, and realize the optimization of the hydro-wind-solar complementary strategy based on large-scale hydro-wind-solar clusters.

2. The method for optimizing water-wind-solar complementary strategy based on large-scale water-wind-solar cluster according to claim 1 is characterized by: Establish a grid aggregation model, including: Considering the power balance of the power grid: The power balance analysis of the power grid is not affected before and after the establishment of the power grid aggregation model; Omit the topology and geographical location in the grid aggregation model: The detailed grid topology is not considered, and each power source and load is no longer affected by its physical location; Describe the generation constraints of the grid aggregation model; Set the number of grid aggregation models included in the target grid: Calculate whether the target grid contains one or more aggregated grids; Describe logical relationships: Describe the logical relationships between aggregated power grids according to the actual power grid operation status; Aggregate power generation equipment and compliant equipment: When the aggregated grid contains one or more wind power stations, they are combined into the total wind power output; when the aggregated grid contains one or more photovoltaic power stations, they are combined into the total photovoltaic power output; when the aggregated grid contains one or more thermal power stations, they are combined into the total thermal power output; the loads within the aggregated grid are combined into the total load.

3. The method for optimizing water-wind-solar complementary strategy based on large-scale water-wind-solar cluster according to claim 1 is characterized by: Power cluster division, including: Hydropower units: Hydropower units of 100MW and above are modeled separately, and small hydropower units below 100MW are modeled as one unit; For wind power, centralized wind power in the aggregated power grid is modeled as one unit, and distributed wind power is modeled as one power station; Photovoltaic: centralized photovoltaic in the aggregated power grid is modeled as one unit, and distributed photovoltaic is modeled as one power station.

4. The method for optimizing water-wind-solar complementary strategy based on large-scale water-wind-solar cluster according to claim 1 is characterized by: The constraints of the hydro-wind-solar complementary power system include transmission channel constraints, wind-solar output constraints and hydropower constraints. Among them, wind-solar output constraints include wind power output constraints and photovoltaic output constraints; hydropower constraints include unit output constraints, reservoir water level daily fluctuation constraints, downstream flow constraints, power generation flow constraints and unit daily power generation constraints.

5. The method for optimizing water-wind-solar complementary strategy based on large-scale water-wind-solar cluster according to claim 1 is characterized by: The complementary optimization model of the hydro-wind-solar complementary power system includes an objective function that aims to maximize the dry season supply capacity of the cascade hydro-wind-solar system, which is expressed as the following formula: in, F is the output fluctuation index of the cascade water, wind and solar power system during the dry season, The average output of cascade water and wind power during the dry season, which is from November to May of the following year. T1 is the total number of time periods, the time period is from November to May of the next year, T1 = 7, pv, w, h are the numbers of the photovoltaic, wind and hydropower stations respectively. PV, W, and H are the total number of solar, wind, and hydropower stations, respectively. is the photovoltaic output in period t1, is the wind power output in period t1, k h is the output coefficient of the hth hydropower station, Q h,t1 is the power generation flow of the hth hydropower station in the t1th period, H h,t1 is the output water head of the hth hydropower station at the t1th period.

6. The method for optimizing water-wind-solar complementary strategy based on large-scale water-wind-solar cluster according to claim 1 is characterized by: The complementary optimization model of the hydro-wind-solar complementary power system includes an objective function with the goal of maximizing the annual power generation of hydro-wind-solar, which is expressed as the following formula: In the formula, E is the total power generation of cascade hydropower, wind and solar power during the period, T is the total number of time periods, pv, w, h are the numbers of the photovoltaic, wind and hydropower stations respectively. PV, W, and H are the total number of solar, wind, and hydropower stations, respectively. N pv,t is the photovoltaic output in period t, N w,t is the wind power output in period t, k h is the output coefficient of the hth hydropower station, Q h,t is the power generation flow of the h-th hydropower station in the t-th period, H h,t is the output water head of the h-th hydropower station in the t-th period, m t is the number of hours in the tth period.

7. The method for optimizing water-wind-solar complementary strategy based on large-scale water-wind-solar cluster according to claim 1 is characterized by: The PSO algorithm with Sigmoid function is used to solve the complementary strategy optimization model of the water-wind-solar complementary power system, and the optimization strategy results are obtained, including the medium- and long-term water level utilization mode of the reservoir, the medium- and long-term power generation output plan of the reservoir, and the system wind power and photovoltaic output plan. Among them, the medium- and long-term water level utilization mode of the reservoir includes the water level control intervals before the flood season, at the end of the flood season and at the end of the year.

8. A water-wind-solar complementary strategy optimization system based on a large-scale water-wind-solar cluster, used to run a water-wind-solar complementary strategy optimization method based on a large-scale water-wind-solar cluster according to any one of claims 1 to 7, characterized in that: Generalized optimization object module: used to generalize the optimization object of the hydro-wind-solar complementary power system of a large-scale hydro-wind-solar cluster through the grid aggregation model and power cluster division to obtain the generalized optimization object; Establish a constraint condition module to establish the constraint conditions for optimizing the complementary strategy of the hydro-wind-solar complementary power system based on a large-scale hydro-wind-solar cluster, including channel constraints, hydropower constraints, and wind-solar output constraints; Constructing optimization model module: It is used to construct a complementary strategy optimization model for the water-wind-solar complementary power system, taking the maximization of the dry season supply capacity of the cascaded water-wind-solar system and the maximization of the annual power generation of water-wind-solar as the objective function, and combining the constraints; Optimization model solving module: used to solve the optimization model of the complementary strategy of the hydro-wind-solar complementary power system, obtain the complementary strategy of the hydro-wind-solar complementary power system, and realize the optimization of the hydro-wind-solar complementary strategy based on large-scale hydro-wind-solar clusters.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the computer program is loaded into the processor, it implements the method for optimizing the water-wind-solar complementary strategy based on a large-scale water-wind-solar cluster according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, it implements a water-wind-solar complementary strategy optimization method based on a large-scale water-wind-solar cluster according to any one of claims 1 to 7.

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