Cascade water-wind-light combined peak regulation method and system containing hybrid water pumping power station

Abstract

The invention relates to the technical field of power system optimization operation, and discloses a cascade water-wind-light combined peak regulation method and system containing a hybrid water pumping station, and the method comprises the steps: obtaining the historical data of a cascade watershed wind-light power station, and predicting the scheduling data of the cascade watershed wind-light power station; an optimization model is constructed, and solving is carried out; and based on the solution of the optimization model, generating a scheduling instruction of the cascade watershed wind-solar power station. By optimizing the model, the adjusting efficiency of the hybrid pumped storage power station is effectively improved, and the hybrid pumped storage power station can flexibly participate in peak regulation of a power system. And meanwhile, the consumption rate of new energy such as wind power and photovoltaic energy is remarkably improved, and the phenomenon of electricity abandoning is reduced. And by reasonably controlling the operation of the thermal power generating unit, the dependence on thermal power is reduced, so that carbon emission is reduced, and environmental protection and sustainable development are promoted. In addition, by smoothing the residual load of the system, the load peak-valley difference is reduced, the stability of the power grid is enhanced, and the economic burden of system operation is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of optimized operation of electric power systems, and specifically to a cascaded water-wind-solar combined peak-shaving method and system including a hybrid pumped power station. Background Art

[0002] In recent years, due to the vigorous development of wind power and photovoltaic power and the gradual retirement of thermal power units, pumped storage power stations have gradually become an important regulatory resource in the power system. Traditional pumped storage power stations mainly generate electricity during peak load periods of the power system and pump water for energy storage during low load periods. They do not undertake the power supply task of the base load. In the face of high uncertainty source and load fluctuations in the new power system, their low-frequency and relatively fixed dispatching and operation mode cannot effectively meet the requirements of efficient and flexible operation and regulation and deep peak regulation of the new power system. As one of the rapidly developing pumped storage technologies, the hybrid pumped storage power station combines the two functions of pumped storage and runoff power generation. It has the advantages of strong regulation flexibility, small project investment, small reservoir flooding losses, no resettlement of immigrants, small environmental impact, and short construction period. It is currently being put into practical engineering applications on a large scale. However, the low-frequency fixed peak regulation dispatching mode of the traditional pumped storage power station cannot effectively guide the hybrid pumped storage power station to participate in the peak regulation optimization of the power system.

[0003] In this context, how to design a cascade wind-solar-water-fired combined peak-shaving optimization method including a hybrid pumped-storage power station to improve the regulation efficiency of the hybrid pumped-storage power station and the system's new energy consumption rate, reduce thermal power carbon emissions and the peak-to-valley difference of the system's residual load has become an important issue. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problems solved by the present invention are: low regulation efficiency of hybrid pumped storage power stations in high-uncertainty power systems, insufficient system new energy absorption capacity, high carbon emissions from thermal power generation, and large peak-to-valley differences in system residual loads.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station, comprising:

[0007] Obtain historical data of wind and solar power stations in cascade basins and predict dispatching data of wind and solar power stations in cascade basins;

[0008] Build an optimization model and solve it;

[0009] Based on the solution of the optimization model, the dispatching instructions for the cascaded wind and solar power stations in the river basin are generated.

[0010] As a preferred solution of the cascade water-wind-solar joint peak-shaving method including a hybrid pumped hydropower station described in the present invention, the historical data includes historical output data, historical load data, historical water level and historical flow data of cascade basin reservoirs;

[0011] The dispatching data include predicted output data of cascade river basin wind and solar power stations, predicted load data, and predicted water level and predicted flow data of cascade river basin reservoirs.

[0012] As a preferred solution of the cascade water-wind-solar joint peak-shaving method containing a hybrid pumped power station described in the present invention, the optimization model includes an optimization objective function and constraint conditions.

[0013] As a preferred solution of the cascade water-wind-solar joint peak-shaving method containing a hybrid pumped hydropower station described in the present invention, the optimization objective function is obtained by the standard deviation of the residual load, and the formula is expressed as follows:

[0014]

[0015] Among them, A represents the optimization target, T represents the scheduling time period, represents the residual load at time t, represents the average value of the remaining load, represents the original load at time t, N represents the total number of cascade hydropower stations, represents the power generation of cascade hydropower station n at time t, represents the pumping power of the hybrid pumped storage power station at time t, represents the wind and solar power station output at time t, represents the output of thermal power unit i at time t, and G represents the total number of thermal power units.

[0016] As a preferred solution of the cascade water-wind-solar joint peak-shaving method including a hybrid pumped hydropower station described in the present invention, wherein: the constraint conditions include hydraulic constraints, power and ramp constraints, and grid power transmission constraints;

[0017] The hydraulic constraint formula is expressed as:

[0018]

[0019] in, represents the pumping flow of pumped storage in period t, represents the pumping flow of cascade hydropower station n in period t, h t represents the water head of the pumped storage power station during period t, h n,t represents the water head of cascade hydropower n in period t, It represents the water level of the upstream pumped storage power station during period t, It represents the water level of the downstream pumped storage power station during period t, It represents the average water level of cascade hydropower station n during period t, It represents the average tailwater level of cascade hydropower station n during period t.

[0020] As a preferred solution of the cascade water-wind-solar joint peak-shaving method including a hybrid pumped hydropower station described in the present invention, the power and ramp constraint formula is expressed as follows:

[0021]

[0022] in, represents the lower limit of the power generation capacity of cascade hydropower n, The upper limit of the power generation capacity of cascade hydropower n is P phs-min represents the lower limit of the pumped power of the pumped storage power station, P phs-max represents the upper limit of the pumping power of the pumped storage power station, represents the ramp limit of cascade hydropower n, P phs-ramp Indicates the climbing limit of the pumped storage power station. represents the lower limit of the output of thermal power unit i, represents the upper limit of the output of thermal power unit i, represents the ramp limit of thermal power unit i;

[0023] The formula of the power transmission constraint of the power grid is expressed as:

[0024]

[0025] in, represents the power transmitted from the wind and solar power station to the grid at time t, represents the power transmitted from the wind-solar power station to the pumped storage at time t, It represents the abandoned power of wind and solar power stations at time t, represents the power transmitted from cascade hydropower n to the grid at time t, represents the power transmitted from cascade hydropower n to pumped storage at time t, represents the power purchased from the grid by the pumped storage at time t, TC wp Indicates the wind and solar channel constraints, TC sd represents the hydropower channel constraint, TC f Represents thermal power channel constraints.

[0026] As a preferred solution of the cascade water-wind-solar joint peak-shaving method including a hybrid pumped hydropower station described in the present invention, wherein: generating a dispatching instruction for the cascade basin wind-solar power station includes constructing an optimization objective function and constraint conditions of the optimization model based on the historical data;

[0027] Linearizing the non-convex part of the optimization model to obtain a linearized optimization model and solving it to obtain the optimal solution of the parameter state of the thermal power unit and the optimal solution of the parameter state of the hybrid pumped storage power station;

[0028] The optimal solution of the thermal power unit parameter state includes the unit start and stop state and output power;

[0029] The optimal solution for the parameter state of the hybrid pumped-storage power station includes the pumping state, power generation state, pumping power and power generation power of the pumped-storage power station.

[0030] A cascaded hydro-wind-solar combined peak-shaving system including a hybrid pumped hydropower station, wherein:

[0031] Data acquisition module, which obtains historical data of wind and solar power stations in cascade basins and predicts the dispatching data of wind and solar power stations in cascade basins;

[0032] Model building module, builds optimization model and solves it;

[0033] The control and dispatch module generates dispatch instructions for cascaded wind and solar power stations based on the solution of the optimization model.

[0034] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0035] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of any one of the methods of the present invention.

[0036] Beneficial effects of the present invention: The cascade water-wind-solar joint peak-shaving method including a hybrid pumped-storage power station provided by the present invention effectively improves the regulation efficiency of the hybrid pumped-storage power station through the optimization model, so that it can flexibly participate in the peak-shaving of the power system. At the same time, the absorption rate of new energy such as wind power and photovoltaics is significantly improved, and the phenomenon of power abandonment is reduced. By reasonably controlling the operation of thermal power units, the dependence on thermal power is reduced, thereby reducing carbon emissions and promoting environmental protection and sustainable development. In addition, the present invention reduces the peak-to-valley difference in load by smoothing the residual load of the system, enhances the stability of the power grid, and reduces the economic burden of system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0038] Figure 1 An overall flow chart of a cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station provided in the first embodiment of the present invention;

[0039] Figure 2 A schematic structural diagram of a cascaded hydro-wind-solar combined peak-shaving method including a hybrid pumped power station provided for the second embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0041] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides a cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station, comprising:

[0042] S1: Obtain historical data of wind and solar power stations in cascade basins and predict the dispatching data of wind and solar power stations in cascade basins.

[0043] Historical data include historical output data, historical load data, historical water levels of cascade basin reservoirs, and historical flow data.

[0044] The dispatching data include predicted output data of cascade river basin wind and solar power stations, predicted load data, and predicted water level and predicted flow data of cascade river basin reservoirs.

[0045] Furthermore, by collecting historical output, load, water level and flow data, an accurate prediction model is established to provide accurate data support for dispatching decisions and enhance the stability of the system. At the same time, reasonable prediction data helps to optimize resource allocation, realize refined power dispatching, improve dispatching efficiency, reduce the impact of new energy fluctuations, improve the absorption capacity of new energy such as wind power and photovoltaics, and reduce power abandonment. In addition, dispatching data prediction helps the system to efficiently utilize new energy, reduce thermal power load and carbon emissions, and meet the goal of low-carbon environmental protection. Accurate prediction data reduces the peak-shaving cost of the power market, improves the economy of the power system, makes the power supply and demand more stable, provides reliable input for subsequent optimization models, and ensures the realization of the optimal dispatching plan.

[0046] S2: Build an optimization model and solve it.

[0047] The optimization model includes optimization objective function and constraints.

[0048] The optimization objective function is obtained from the residual load standard deviation, and the formula is expressed as:

[0049]

[0050] Among them, A represents the optimization target, T represents the scheduling time period, represents the residual load at time t,

[0051] represents the average value of the remaining load, represents the original load at time t, N represents the total number of cascade hydropower stations, represents the power generation of cascade hydropower station n at time t, represents the pumping power of the hybrid pumped storage power station at time t, represents the wind and solar power station output at time t, represents the output of thermal power unit i at time t, and G represents the total number of thermal power units.

[0052] Constraints include hydraulic constraints, power and ramp constraints, and grid power transmission constraints;

[0053] The hydraulic constraint formula is expressed as:

[0054]

[0055] in, represents the pumping flow of pumped storage in period t, represents the pumping flow of cascade hydropower station n in period t, h t represents the water head of the pumped storage power station during period t, h n,t represents the water head of cascade hydropower n in period t, It represents the water level of the upstream pumped storage power station during period t, It represents the water level of the downstream pumped storage power station during period t, It represents the average water level of cascade hydropower station n during period t, It represents the average tailwater level of cascade hydropower station n during period t.

[0056] The average water level and average tailwater level of the cascade hydropower station n in period t are obtained by fitting the average storage capacity and the average tailwater level discharge. The specific expression is:

[0057]

[0058] in, represents the water level storage capacity fitting coefficient, represents the tailwater level discharge fitting coefficient, They represent the average storage capacity and average tailwater level discharge respectively.

[0059] The reservoir capacity of cascade hydropower n at time t is obtained by the inflow, pumping flow, abandoned flow of the cascade hydropower and the inflow of cascade hydropower n-1 at time t. The upper and lower reservoir capacities of the pumped-storage power station at time t are obtained according to the inflow, pumping flow, power generation flow, abandoned flow of the upper and lower reservoirs and the upper and lower reservoir capacities of the pumped-storage power station at time t-1. The specific expression is as follows:

[0060]

[0061] Among them, ν n,t represents the reservoir capacity of the nth cascade hydropower station at time t, They represent the storage capacity of the upper and lower reservoirs of the pumped storage power station, respectively. n,t represents the inflow of the nth cascade hydropower station during period t, and They represent the inflow of the upper and lower reservoirs of the pumped storage power station, and They represent the power generation flow of the upper and lower reservoirs of the pumped storage power station at time t, qs n,t represents the water discharge of the nth cascade hydropower reservoir at time t, and They represent the water discharge from the upstream and downstream reservoirs of the pumped-storage power station respectively.

[0062] The inflow of the cascade hydropower station n at time t is obtained according to the natural inflow of the cascade reservoir at the current moment, the pumping flow and the abandoned water flow of the cascade hydropower station n-1 at time t; the inflow of the upper reservoir of the pumped storage power station is obtained according to the natural inflow of the upper reservoir, the power generation flow and the abandoned water flow of the cascade hydropower station n at time t; the inflow of the lower reservoir of the pumped storage power station is obtained according to the natural inflow of the lower reservoir, the power generation flow and the abandoned water flow of the upper reservoir. The specific expressions are as follows:

[0063]

[0064] Among them, qr n,t represents the natural water flow of cascade hydropower station n at time t, represents the power generation flow of cascade hydropower n-1 at time t, qs n-1,t represents the abandoned water flow of cascade hydropower n-1 at time t, It represents the natural water flow of the upper reservoir pumped for storage. represents the natural water flow of the pumped storage reservoir, qp n,t It represents the power generation flow of cascade reservoir n at time t.

[0065] The constraints on the storage capacity, pumping flow, and abandoned water flow of the cascade hydropower n at time t are as follows:

[0066]

[0067] in, and They represent the upper and lower limits of the storage capacity of cascade hydropower n, and They represent the upper and lower limits of the power generation flow of cascade hydropower station n, and They respectively represent the upper and lower limits of the abandoned water flow of cascade hydropower station n.

[0068] The power and climbing constraint formula is expressed as:

[0069]

[0070] in, represents the lower limit of the power generation capacity of cascade hydropower n, The upper limit of the power generation capacity of cascade hydropower n is P phs-min represents the lower limit of the pumped power of the pumped storage power station, P phs-max represents the upper limit of the pumping power of the pumped storage power station, represents the ramp limit of cascade hydropower n, P phs-ramp Indicates the climbing limit of the pumped storage power station. represents the lower limit of the output of thermal power unit i, represents the upper limit of the output of thermal power unit i, Represents the ramp limit of thermal power unit i.

[0071] The formula of the power transmission constraint of the power grid is expressed as:

[0072]

[0073] in, represents the power transmitted from the wind and solar power station to the grid at time t, represents the power transmitted from the wind-solar power station to the pumped storage at time t, It represents the abandoned power of wind and solar power stations at time t, represents the power transmitted from cascade hydropower n to the grid at time t, represents the power transmitted from cascade hydropower n to pumped storage at time t, represents the power purchased from the grid by the pumped storage at time t, TC wp Indicates the wind and solar channel constraints, TC sd represents the hydropower channel constraint, TC f Represents thermal power channel constraints.

[0074] Furthermore, the purpose of constructing and solving the optimization model is to achieve efficient peak load management in complex cascade water, wind, solar and pumped storage power systems. The supply and demand of the system are balanced by optimizing the objective function (with the goal of minimizing the standard deviation of the remaining load), and combining various constraints (such as hydraulic constraints, power and ramp constraints, and grid power transmission constraints) to ensure that each power generation mode can reasonably dispatch output under the premise of meeting physical and operational constraints. This step can not only effectively reduce the load fluctuation of the system, improve the stability and reliability of the system, but also maximize the use of renewable energy such as wind and solar, thereby reducing dependence on traditional thermal power, reducing carbon emissions, and achieving a win-win situation for economic and environmental protection goals. At the same time, linear processing and efficient solution methods also ensure the real-time and adaptability of dispatch instructions, making the operation of the entire system more flexible and efficient.

[0075] S3: Based on the solution of the optimization model, the dispatching instructions for the cascaded wind and solar power stations are generated.

[0076] Generating dispatch instructions for cascade basin wind and solar power stations includes constructing an optimization objective function and constraint conditions of the optimization model based on the historical data;

[0077] Linearizing the non-convex part of the optimization model to obtain a linearized optimization model and solving it to obtain the optimal solution of the parameter state of the thermal power unit and the optimal solution of the parameter state of the hybrid pumped storage power station;

[0078] The optimal solution of the thermal power unit parameter state includes the unit start and stop state and output power;

[0079] The optimal solution for the parameter state of the hybrid pumped-storage power station includes the pumping state, power generation state, pumping power and power generation power of the pumped-storage power station.

[0080] Furthermore, dispatching instructions for cascaded wind and solar power stations are generated based on the solution of the optimization model, aiming to achieve accurate and efficient power dispatching. The optimization model is constructed through historical data and the objective function and constraints are set to ensure that the dispatching process can take into account various restrictions in actual operation. The non-convex part of the model is linearized to make the optimization solution faster and more stable, ensuring the feasibility and optimality of the solution. By solving the optimal solution of the thermal power unit and the hybrid pumped storage power station, specific start and stop states and power dispatching instructions are generated, which can reasonably control the operation mode of the thermal power unit and the pumped storage power station in different time periods to achieve supply and demand balance. The significance of this step is to make various power sources work together through intelligent dispatching decisions, make full use of new energy such as wind and solar, reduce thermal power output, improve the operating efficiency and flexibility of the power system, and further reduce carbon emissions, effectively achieving the dual goals of environmental protection and economy.

[0081] Embodiment 2 is an embodiment of the present invention, which provides a cascaded water-wind-solar combined peak-shaving system including a hybrid pumped hydropower station, comprising:

[0082] Reference Figure 2 , is a structural schematic diagram of a cascade wind-solar-water-fire combined peak-shaving optimization system including a hybrid pumped-storage power station provided by an embodiment of the present invention. As shown in the figure, the cascade wind-solar-water-fire combined peak-shaving optimization system 10 including a hybrid pumped-storage power station includes a data acquisition module 101, a model building module 102, a processing and solving module 103, and a control and scheduling module 104. The specific units of each module are as follows:

[0083] The data acquisition module 101 is used to acquire the historical output data, historical load data, historical water level and historical flow data of the cascade basin wind and solar power stations, and predict the predicted output data, predicted load data, predicted water level and predicted flow data of the cascade basin wind and solar power stations within a future set scheduling time period based on the historical output data, historical load data, historical water level and historical flow data of the cascade basin reservoirs;

[0084] The model building module 102 is used to establish a cascade wind-solar-water-fire combined peak-shaving optimization model including a hybrid pumped-storage power station, wherein the cascade wind-solar-water-fire combined peak-shaving optimization model including a hybrid pumped-storage power station includes an optimization objective function and constraints, the optimization objective is obtained by the standard deviation of the residual load, and the constraints include hydraulic constraints, power and climbing constraints, and grid power transmission constraints.

[0085] The processing and solving module 103 is used to input the predicted output data, predicted load data, predicted water level and predicted flow data of the cascaded wind and solar power stations in the river basin into the cascaded wind, solar, water and fire combined peak-shaving optimization model of the hybrid pumped-storage power station, perform linear processing on the cascaded wind, solar, water and fire combined peak-shaving optimization model of the hybrid pumped-storage power station to obtain a linearized cascaded wind, solar, water and fire combined peak-shaving optimization model containing the hybrid pumped-storage power station, and solve the linearized cascaded wind, solar, water and fire combined peak-shaving optimization model containing the hybrid pumped-storage power station to obtain the optimal solution of the parameter state of the thermal power unit and the optimal solution of the parameter state of the hybrid pumped-storage power station.

[0086] The control and dispatching module 104 is used to generate an optimal dispatching instruction based on the optimal solution of the thermal power parameter state and the optimal solution of the hybrid pumped-storage power station parameter state to control the optimal operation of the thermal power unit, the hybrid pumped-storage power station and the wind-solar power station.

[0087] Optionally, the processing and solving module 103 includes a model processing unit 1031 and a model solving unit 1032, wherein:

[0088] The model processing unit 1031 is used to linearize the non-convex part of the cascade wind-solar-water-fire combined peak-shaving optimization model of the hybrid pumped-storage power station to obtain a linearized cascade wind-solar-water-fire combined peak-shaving optimization model of the hybrid pumped-storage power station;

[0089] The model solving unit 1032 is used to call the commercial solver Gurobi to solve the linearized hybrid pumped-storage power station cascade wind-solar-water-fire combined peak-shaving optimization model to obtain the optimal solution for the parameter state of the thermal power unit and the optimal solution for the parameter state of the hybrid pumped-storage power station.

[0090] Embodiment 3, an embodiment of the present invention, is different from the first two embodiments in that:

[0091] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0092] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0093] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0094] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0095] In Example 4, a dispatching system including wind power stations, photovoltaic power stations, cascade hydropower stations and thermal power units is set up in a simulation environment. The system collects the output data, load data, reservoir water level and flow data of each power station in the past two years to generate historical data. Based on these historical data, the time series prediction model is used to predict the output, load demand, reservoir water level and flow of wind and photovoltaic power stations in the next seven days to generate dispatching data.

[0096] Subsequently, a peak load optimization model was constructed, with the minimization of the standard deviation of the remaining load as the objective function, including hydraulic constraints, power and ramp constraints, and grid power transmission constraints. After the model was solved, dispatch instructions were generated according to the optimized solution. The instructions control the start and stop status and power output of the thermal power units, as well as the pumping, power generation status and power of the hybrid pumped storage power station, to ensure that the system can achieve efficient peak load regulation while meeting the demand. The experimental data are shown in Table 1.

[0097] Table 1 Experimental data table

[0098]

[0099] Through the analysis of the table data, it can be seen that the peak-shaving method of the present invention has significant innovation and advantages. First, with the fluctuation of the output power of the wind and solar power stations, the method of the present invention can dynamically adjust the output of the thermal power units and the hybrid pumped storage power station, so that the residual load of the system is gradually reduced and stabilized within a low fluctuation range. The "System Residual Load" column in the table shows that the fluctuation amplitude of the system residual load after peak-shaving control is small, which effectively achieves the goal of load balance.

[0100] Compared with the traditional peak-shaving method, the optimization model of the present invention fully considers the physical constraints of each generator set and hydropower station in the process of generating dispatch instructions, including hydraulic constraints, power and ramp constraints, power transmission constraints of the power grid, etc., to ensure the practical feasibility and stability of the peak-shaving operation. The changes in the power of each power station at different time points in the test data meet these constraints, indicating that this method can meet the multiple constraints of the system in practical applications.

[0101] In addition, the innovation of the present invention is reflected in the accurate prediction of future load and output, which reduces the phenomenon of power abandonment caused by fluctuations in new energy output and improves the system's new energy absorption capacity. At the same time, the dispatch instructions generated by the optimization model can accurately control the start and stop and output of thermal power units, significantly reducing the operating time of thermal power units and reducing carbon emissions. This is reflected in the data, where the output of thermal power units gradually decreases, thus achieving the goal of low-carbon and environmental protection.

[0102] In terms of algorithm performance, the optimization algorithm of the present invention has a short running time, high solution efficiency, and can provide the optimal scheduling solution in a short time, which is suitable for real-time application in the peak load regulation operation of the actual power system. This not only improves the peak load regulation response speed of the system, but also ensures the safety and reliability of the power system.

[0103] In summary, the tabular data clearly demonstrates the advantages of the peak-shaving method of the present invention in terms of innovation and practicality, and proves its remarkable effects in reducing system residual load fluctuations, improving the new energy consumption rate and reducing carbon emissions, making up for the shortcomings of traditional peak-shaving methods and having good application prospects.

[0104] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A cascade water, wind and solar combined peak-shaving method including a hybrid pumped hydropower station, characterized in that: include: Obtain historical data of wind and solar power stations in cascade basins and predict dispatching data of wind and solar power stations in cascade basins; Build an optimization model and solve it; Based on the solution of the optimization model, the dispatching instructions for the cascaded wind and solar power stations in the river basin are generated.

2. The cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station as claimed in claim 1, characterized in that: The historical data include historical output data, historical load data, historical water level and historical flow data of cascade basin reservoirs; The dispatching data include predicted output data of cascade river basin wind and solar power stations, predicted load data, and predicted water level and predicted flow data of cascade river basin reservoirs.

3. The cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station as claimed in claim 2, characterized in that: The optimization model includes an optimization objective function and constraint conditions.

4. The cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station as claimed in claim 3, characterized in that: The optimization objective function is obtained from the residual load standard deviation, and the formula is expressed as: Among them, A represents the optimization target, T represents the scheduling time period, represents the residual load at time t, represents the average value of the remaining load, represents the original load at time t, N represents the total number of cascade hydropower stations, represents the power generation of cascade hydropower station n at time t, represents the pumping power of the hybrid pumped storage power station at time t, represents the wind and solar power station output at time t, represents the output of thermal power unit i at time t, and G represents the total number of thermal power units.

5. The cascade water-wind-solar combined peak-shaving method including a hybrid pumped hydropower station as claimed in claim 4, characterized in that: The constraints include hydraulic constraints, power and ramp constraints, and grid power transmission constraints; The hydraulic constraint formula is expressed as: in, represents the pumping flow of pumped storage in period t, represents the pumping flow of cascade hydropower station n in period t, h t represents the water head of the pumped storage power station during period t, h n,t represents the water head of cascade hydropower n in period t, It represents the water level of the upstream pumped storage power station during period t, It represents the water level of the downstream pumped-storage power station during period t, It represents the average water level of cascade hydropower station n during period t, It represents the average tailwater level of cascade hydropower station n during period t.

6. The cascade water, wind and solar combined peak-shaving method including a hybrid pumped hydropower station as claimed in claim 5, characterized in that: The power and climbing constraint formula is expressed as: in, represents the lower limit of the power generation capacity of cascade hydropower n, The upper limit of the power generation capacity of cascade hydropower n is P phs-min represents the lower limit of the pumped power of the pumped storage power station, P phs-max represents the upper limit of the pumping power of the pumped storage power station, represents the ramp limit of cascade hydropower n, P phs-ramp Indicates the climbing limit of the pumped storage power station. represents the lower limit of the output of thermal power unit i, represents the upper limit of the output of thermal power unit i, represents the ramp limit of thermal power unit i; The formula of the power transmission constraint of the power grid is expressed as: in, represents the power transmitted from the wind and solar power station to the grid at time t, represents the power transmitted from the wind-solar power station to the pumped storage at time t, It represents the abandoned power of wind and solar power stations at time t, represents the power transmitted from cascade hydropower n to the grid at time t, represents the power transmitted from cascade hydropower n to pumped storage at time t, represents the power purchased from the grid by the pumped storage at time t, TC wp Indicates the wind and solar channel constraints, TC sd represents the hydropower channel constraint, TC f Represents thermal power channel constraints.

7. The cascade water, wind and solar combined peak-shaving method including a hybrid pumped hydropower station as claimed in claim 6, characterized in that: Generating dispatch instructions for cascade basin wind and solar power stations includes constructing an optimization objective function and constraint conditions of the optimization model based on the historical data; Linearizing the non-convex part of the optimization model to obtain a linearized optimization model and solving it to obtain the optimal solution of the parameter state of the thermal power unit and the optimal solution of the parameter state of the hybrid pumped storage power station; The optimal solution of the thermal power unit parameter state includes the unit start and stop state and output power; The optimal solution for the parameter state of the hybrid pumped-storage power station includes the pumping state, power generation state, pumping power and power generation power of the pumped-storage power station.

8. A cascaded water-wind-solar combined peak-shaving system including a hybrid pumped power station using the method according to any one of claims 1 to 7, characterized in that: Data acquisition module, which obtains historical data of wind and solar power stations in cascade basins and predicts the dispatching data of wind and solar power stations in cascade basins; Model building module, builds optimization model and solves it; The control and dispatch module generates dispatch instructions for cascaded wind and solar power stations based on the solution of the optimization model.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the cascade water-wind-solar combined peak-shaving method containing a hybrid pumped power station as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the cascade water-wind-solar combined peak-shaving method containing a hybrid pumped power station as described in any one of claims 1 to 7 are implemented.

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