A photovoltaic power generation consumption method, device, equipment and readable storage medium

Abstract

The application discloses a photovoltaic power generation consumption method, device, equipment and readable storage medium, which can reduce the uncertainty of photovoltaic power generation prediction through preset confidence parameters, comprehensively consider the demand of multiple types of composite resources and the operation data of a power system when scheduling a photovoltaic power station, and determine the scheduling amount of the photovoltaic power station that brings the maximum economic benefit, so as to improve the photovoltaic power generation consumption capacity of the power system, and further greatly improve the effectiveness of the power system scheduling strategy.

Description

Technical Field

[0001] This application relates to the field of renewable energy consumption technology, and more specifically, to a photovoltaic power generation consumption method, apparatus, equipment, and readable storage medium. Background Technology

[0002] To achieve clean and low-carbon energy, the proportion of renewable energy sources such as photovoltaics integrated into the power system is rapidly increasing. However, the large-scale integration of photovoltaic power generation also presents challenges to power system dispatch. On the one hand, due to the uncertainty of photovoltaic power generation, its forecasts often contain errors, hindering the power system from effectively implementing dispatch strategies. On the other hand, as the proportion of renewable energy increases, the power system's flexibility in generation decreases, and the lack of flexible generation resources makes photovoltaic integration difficult. Therefore, how to improve the power system's photovoltaic power generation integration capacity has become an urgent problem to be solved. Summary of the Invention

[0003] This application provides a photovoltaic power generation absorption method, apparatus, equipment, and readable storage medium, which can improve the photovoltaic power generation absorption capacity of the power system and thus greatly enhance the effectiveness of the power system dispatch strategy.

[0004] In view of this, this application provides a method for photovoltaic power generation consumption, including:

[0005] To obtain the initial predicted power generation of photovoltaic power plants, the capacity parameters of various types of load resources, and the operating data of the power system;

[0006] The optimized predicted power generation of the photovoltaic power station is calculated based on the initial predicted power generation and the preset confidence parameters.

[0007] Calculate the demand for the various types of load resources based on their capacity parameters.

[0008] The cost function of the power system is constructed based on the optimized predicted power generation, the demand of the various types of load resources, and the operating data.

[0009] Based on the cost function and constraints, the scheduling quantity of the photovoltaic power station is determined, wherein the constraints include the cost function taking the minimum value;

[0010] The photovoltaic power station is scheduled according to the specified scheduling amount.

[0011] Optionally, the step of calculating the optimized predicted power generation of the photovoltaic power station based on the initial predicted power generation and preset confidence parameters includes:

[0012] The membership parameter set is calculated based on the initial predicted power generation and the proportionality coefficient, wherein the proportionality coefficient is calculated based on the historical power generation of the photovoltaic power station.

[0013] The optimized predicted power generation of the photovoltaic power station is calculated based on the membership parameter set and the confidence parameter.

[0014] Optionally, the membership parameter set includes a first membership parameter, a second membership parameter, a third membership parameter, and a fourth membership parameter; the step of calculating the optimized predicted power generation of the photovoltaic power station based on the membership parameter set and the confidence parameter specifically includes:

[0015]

[0016] in, For the optimized predicted power generation, σ is a confidence parameter. For the first membership parameter, For the second membership parameter, For the third membership parameter and This refers to the fourth membership parameter.

[0017] Optionally, the step of constructing the cost function of the power system based on the optimized predicted power generation, the demand of the various types of load resources, and the operating data specifically includes:

[0018]

[0019] in, For the cost function of conventional generator sets, It is the cost function of the curtailment penalty for the photovoltaic power station. It is the demand cost function of the aforementioned multi-type load resources. and These represent the power generation of the conventional generator set and the photovoltaic power station during time period t, respectively. Ψ represents the response power of various types of load resources during time period t. EG and Ψ PV Ψ represents the collection of conventional generator sets and photovoltaic power plants, respectively. TL,SL,IL It represents a collection of multiple types of load resources.

[0020] This application also provides a photovoltaic power generation consumption device, including:

[0021] The acquisition unit is used to acquire the initial predicted power generation of the photovoltaic power plant, the capacity parameters of various types of load resources, and the operating data of the power system.

[0022] The first calculation unit is used to calculate the optimized predicted power generation of the photovoltaic power station based on the initial predicted power generation and the preset confidence parameters.

[0023] The second calculation unit is used to calculate the demand of the multi-type load resources based on the capacity parameters of the multi-type load resources.

[0024] A construction unit is used to construct the cost function of the power system based on the optimized predicted power generation, the demand of the multi-type load resources, and the operating data.

[0025] The determining unit is used to determine the dispatch quantity of the photovoltaic power station based on the cost function and constraints, wherein the constraints include the cost function taking the minimum value;

[0026] The scheduling unit is used to schedule the photovoltaic power station according to the scheduling quantity.

[0027] Optionally, the first computing unit includes:

[0028] The first calculation subunit is used to calculate a set of membership parameters based on the initial predicted power generation and the proportional coefficient, wherein the proportional coefficient is calculated based on the historical power generation of the photovoltaic power station.

[0029] The second calculation subunit calculates the optimized predicted power generation of the photovoltaic power station based on the membership parameter set and the confidence parameter.

[0030] Optionally, the second calculation subunit is specifically used to perform calculations according to the following formula:

[0031]

[0032] in, For the optimized predicted power generation, σ is a confidence parameter. For the first membership parameter, For the second membership parameter, For the third membership parameter and This refers to the fourth membership parameter.

[0033] Optionally, the construction unit is specifically used to construct the cost function of the power system according to the following formula:

[0034]

[0035] in, Let g be the cost function of a conventional generator set. It is the curtailment penalty cost function of the photovoltaic power station v. It is the demand cost function of the aforementioned multi-type load resources. and Let g represent the power generation of the conventional generator unit and v of the photovoltaic power station during time period t, respectively. Ψ represents the response power of various types of load resources during time period t. EG and Ψ PV Ψ represents the collection of conventional generator sets and photovoltaic power plants, respectively. TL,SL,IL It represents a collection of multiple types of load resources.

[0036] This application also provides a computer device, characterized in that it includes: a memory, a processor, and a bus system;

[0037] The memory is used to store programs;

[0038] The processor is used to execute programs in the memory to implement the various methods described above;

[0039] The bus system is used to connect the memory and the processor to enable communication between the memory and the processor.

[0040] This application also provides a computer-readable storage medium, characterized in that it stores instructions that, when executed on a computer, cause the computer to perform the various methods described above.

[0041] This application provides a method for photovoltaic (PV) power generation absorption, comprising: acquiring the initial predicted power generation of a PV power plant, capacity parameters of multiple types of load resources, and power system operation data; calculating the optimized predicted power generation of the PV power plant based on the initial predicted power generation and preset confidence parameters; calculating the demand of the multiple types of load resources based on the capacity parameters of the multiple types of load resources; constructing a cost function of the power system based on the optimized predicted power generation, the demand of the multiple types of load resources, and the operation data; determining the dispatch quantity of the PV power plant based on the cost function and constraints, wherein the constraints include minimizing the cost function; and dispatching the PV power plant based on the dispatch quantity. It is evident that this application can reduce the uncertainty of PV power generation prediction through preset confidence parameters, and by comprehensively considering the demand of multiple types of composite resources and the operation data of the power system when dispatching the PV power plant, it can determine the dispatch quantity of the PV power plant that brings the greatest economic benefits, thereby improving the PV power generation absorption capacity of the power system and significantly enhancing the effectiveness of the power system dispatch strategy. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0043] Figure 1 A schematic flowchart illustrating a photovoltaic power generation consumption method provided in this application embodiment;

[0044] Figure 2 This is a schematic diagram of a photovoltaic power generation consumption method provided in an embodiment of this application. Detailed Implementation

[0045] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0046] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments described herein can be implemented in a sequence other than that illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0047] First, let's explain some of the terms that may be used in this application:

[0048] Photovoltaic power generation consumption: This refers to the absorption and utilization of photovoltaic power. Because after power plants (whether hydropower, thermal power, nuclear power, or wind power) generate electricity and send it to the grid, the electrical energy cannot be easily stored. If it is not used, it is a waste. Therefore, the surplus electrical energy must be dispatched to the load points with electricity demand through dispatch. This process is called consumption.

[0049] Photovoltaic power station: refers to a power generation system that utilizes solar energy, uses special materials such as crystalline silicon panels, inverters and other electronic components, and is connected to the power grid to transmit electricity to the grid.

[0050] To achieve clean and low-carbon energy, the proportion of renewable energy sources such as photovoltaics integrated into the power system is rapidly increasing. However, the large-scale integration of photovoltaic power generation also presents challenges to power system dispatch. On the one hand, due to the uncertainty of photovoltaic power generation, its forecasts often contain errors, hindering the power system from effectively implementing dispatch strategies. On the other hand, as the proportion of renewable energy increases, the power system's flexibility in generation decreases, and the lack of flexible generation resources makes photovoltaic integration difficult. Therefore, how to improve the power system's photovoltaic power generation integration capacity has become an urgent problem to be solved.

[0051] Therefore, in view of the above problems, the embodiments of this application provide a photovoltaic power generation absorption method, apparatus, equipment and readable storage medium, which can improve the photovoltaic power generation absorption capacity of the power system, and thus greatly improve the effectiveness of the power system dispatch strategy.

[0052] Please see Figure 1 The photovoltaic power generation consumption method provided in this application includes the following steps.

[0053] S101. Obtain the initial predicted power generation of the photovoltaic power plant, the capacity parameters of various types of load resources, and the operation data of the power system.

[0054] In this embodiment, the initial predicted power generation of the photovoltaic power plant, the capacity parameters of various types of load resources, and the operating data of the power system can be obtained from the existing power grid. Specifically, the initial predicted power generation of the photovoltaic power plant is the time-varying predicted power output of the photovoltaic power plant. Multi-type load resources include shiftable loads, transferable loads, and interruptible loads. The capacity parameters of multi-type load resources include the shiftable time interval (Δt) for shiftable loads. SL- , Δt SL+ Minimum transferable load and maximum transfer amount The maximum number of interruptible load interruptions N IL Power system operating data includes system power load. Upper limit of transmission line capacity generator set capacity Uphill gradient of generator set and downhill slope

[0055] S102. Calculate the optimized predicted power generation of the photovoltaic power station based on the initial predicted power generation and the preset confidence parameters.

[0056] In this embodiment, after obtaining the initial predicted power generation of the photovoltaic power station, the optimized predicted power generation of the photovoltaic power station can be calculated based on the initial predicted power generation and a preset confidence parameter. It is understood that because the initial predicted power generation of the photovoltaic power station obtained directly from the power grid is highly uncertain, it is impossible to effectively arrange the power system dispatch strategy. Therefore, the initial predicted power generation can be optimized by pre-setting a confidence parameter, thereby reducing the uncertainty of the initial predicted power generation.

[0057] In one possible implementation, a set of membership parameters can be calculated based on the initial predicted power generation and the proportionality coefficient, where the proportionality parameter is calculated based on the historical power generation of the photovoltaic power plant; the optimized predicted power generation of the photovoltaic power plant can then be calculated based on the set of membership parameters and the confidence parameter.

[0058] Specifically, firstly, a trapezoidal fuzzy number equivalent model of the initial predicted power generation of a photovoltaic power plant can be constructed as follows:

[0059]

[0060] in, and It is the membership parameter of the trapezoidal fuzzy number. For the first membership parameter, For the second membership parameter, For the third membership parameter and This is the fourth membership parameter. and This represents the minimum and maximum values ​​of the photovoltaic power output that may occur at time t. and This represents the boundary of the range where the photovoltaic power output is most likely to occur at time t;

[0061] The aforementioned fuzzy membership parameters can be calculated from the predicted values ​​of photovoltaic power output:

[0062]

[0063] Among them, w s (s=1,2,3,4) represents The corresponding proportionality coefficient is calculated based on the historical power generation of the photovoltaic power station. This represents the initial predicted power generation capacity of the photovoltaic power plant.

[0064] The membership function is used to represent the degree to which a variable belongs to the fuzzy set. The membership function of the trapezoidal fuzzy number of the initial predicted power generation of a photovoltaic power station is shown below:

[0065]

[0066] Among them, u v (x) is expressed in fuzzy numbers The membership degree of variable x in the middle.

[0067] Secondly, a confidence parameter σ can be preset to determine the initial predicted power generation of the photovoltaic power plant. Optimized predicted power generation of photovoltaic power plants As shown below:

[0068]

[0069] in, This represents the optimized predicted power generation of a photovoltaic power plant. The confidence parameter σ can be adjusted according to the risk preference of the system dispatching agency.

[0070] S103. Calculate the demand for the multi-type load resources based on the capacity parameters of the multi-type load resources.

[0071] In this embodiment, after obtaining the capacity parameters of multiple types of load resources, the demand for these resources can be calculated based on these parameters. It is understood that by calculating the demand for multiple types of load resources, the flexibility of these resources can be utilized to improve the photovoltaic absorption capacity of the power system, thereby enhancing the effectiveness and robustness of the power system dispatch strategy.

[0072] Specifically, the various types of load resources include movable loads, transferable loads, and interruptible loads, and their demand response models are as follows:

[0073] 1) Sliding load demand response model

[0074]

[0075] Δt SL- ≤Δt SL ≤Δt SL+ ;

[0076] in, This represents the magnitude of the movable load SL after it has been moved in time period t. Δt represents the original load size of the movable load SL before it is moved in time period t. SL This represents the time interval for the overall shift of the SL load curve. A positive value indicates that the load curve shifts forward, while a negative value indicates that the load curve shifts backward.

[0077] 2) Transferable load demand response model

[0078]

[0079]

[0080]

[0081] in, This represents the magnitude of load transfer (TL) during time period t. A positive value indicates that load is transferred from other time periods to this time period, while a negative value indicates that load is transferred from this time period to other time periods. This represents the load size of the transferable load TL after it has been transferred in time period t. This represents the original load size of the transferable load TL before it is transferred in time period t. and This represents the minimum and maximum load values ​​of the transferable load TL, where T is the total number of time periods in the scheduling cycle;

[0082] 3) Interruptible load demand response model

[0083]

[0084]

[0085]

[0086] in, This represents the interruptible load IL value during time period t. This represents the load size of the interruptible load IL after the interruption during time period t. a represents the original load size of the interruptible load IL before the interruption in time period t. IL (t) represents the binary state variable of the interruptible load IL during time period t, a IL (t) = 1 indicates that the load IL is not interrupted during time period t, a IL (t) = 0 indicates that the load IL is interrupted during the time period t.

[0087] It is understandable that the demand for various types of load resources can be calculated based on the capacity parameters of various types of load resources obtained from the power grid and the demand response models of various types of load resources.

[0088] S104. Construct the cost function of the power system based on the optimized predicted power generation, the demand of the multi-type load resources, and the operating data.

[0089] In this embodiment, a cost function for the power system can be constructed based on the obtained optimized predicted power generation of the photovoltaic power plant, the demand for various types of load resources, and the operating data of the power system. It is understood that by constructing the cost function of the power system, the dispatch quantity of the photovoltaic power plant that can bring the greatest economic benefits can be determined, thereby improving the photovoltaic power generation absorption capacity of the power system and significantly enhancing the effectiveness of the power system dispatch strategy.

[0090] In one possible implementation, the cost function of the constructed power system can include generator generation costs, solar curtailment penalty costs, load demand costs, etc., as shown below:

[0091]

[0092] in, For the cost function of conventional generator sets, It is the cost function of the curtailment penalty for the photovoltaic power station. It is the demand cost function of the aforementioned multi-type load resources. and These represent the power generation of the conventional generator set and the photovoltaic power station during time period t, respectively. Ψ represents the response power of various types of load resources during time period t. EG and Ψ PV Ψ represents the collection of conventional generator sets and photovoltaic power plants, respectively. TL,SL,IL It represents a collection of multiple types of load resources, including movable loads, transferable loads, and interruptible loads.

[0093] S105. Determine the scheduling amount of the photovoltaic power station based on the cost function and constraints, wherein the constraints include the cost function taking the minimum value.

[0094] In this embodiment, after constructing the cost function of the power system, in order to determine the dispatch quantity of the photovoltaic power station that can bring the maximum economic benefits, the actual power generation of the photovoltaic power station when the cost function of the power system reaches its minimum value can be calculated. This is taken as the optimal power generation capacity. It is understandable that when the actual power generation capacity of the photovoltaic power station is the optimal power generation capacity, the cost function of the power system is minimized, which ensures that the dispatch strategy of the power system can bring the greatest economic benefits. Therefore, the dispatch capacity of the photovoltaic power station can be determined as the optimal power generation capacity of the photovoltaic power station.

[0095] In one possible implementation, the cost function should also satisfy the following two constraints:

[0096] 1) Unit constraints

[0097]

[0098]

[0099]

[0100] 2) System operation constraints

[0101]

[0102]

[0103] in, This represents the transmission power of transmission line l during time period t.

[0104] S106. The photovoltaic power station is scheduled according to the scheduling amount.

[0105] In this embodiment, after determining the dispatch amount of the photovoltaic power station, the photovoltaic power station can be dispatched according to the dispatch amount. Specifically, the corresponding power generation from the photovoltaic power station can be directly dispatched into the grid according to the dispatch amount, or the curtailment power of the photovoltaic power station can be obtained by subtracting the dispatch amount of the photovoltaic power station from the optimized predicted power generation of the photovoltaic power station, and then the corresponding power generation in the photovoltaic power station can be abandoned according to the curtailment power, and the remaining power generation can be dispatched into the grid.

[0106] This application provides a photovoltaic power generation absorption method that reduces the uncertainty of photovoltaic power generation forecasting by using preset confidence parameters. When scheduling photovoltaic power plants, it comprehensively considers the demand of multiple types of composite resources and the operation data of the power system, and can determine the scheduling quantity of photovoltaic power plants that bring the greatest economic benefits, thereby improving the photovoltaic power generation absorption capacity of the power system and greatly enhancing the effectiveness of the power system scheduling strategy.

[0107] Please see Figure 2 This application provides a photovoltaic power generation consumption device, comprising:

[0108] The acquisition unit 201 is used to acquire the initial predicted power generation of the photovoltaic power plant, the capacity parameters of various types of load resources, and the operating data of the power system.

[0109] The first calculation unit 202 is used to calculate the optimized predicted power generation of the photovoltaic power station based on the initial predicted power generation and the preset confidence parameters.

[0110] The second calculation unit 203 is used to calculate the demand of the multi-type load resources based on the capacity parameters of the multi-type load resources.

[0111] Construction unit 204 is used to construct the cost function of the power system based on the optimized predicted power generation, the demand of the multi-type load resources, and the operating data;

[0112] The determining unit 205 is used to determine the dispatch quantity of the photovoltaic power station according to the cost function and the constraints, wherein the constraints include the cost function taking the minimum value;

[0113] The scheduling unit 206 is used to schedule the photovoltaic power station according to the scheduling amount.

[0114] Optionally, the first computing unit 202 includes:

[0115] The first calculation subunit is used to calculate a set of membership parameters based on the initial predicted power generation and the proportional coefficient, wherein the proportional coefficient is calculated based on the historical power generation of the photovoltaic power station.

[0116] The second calculation subunit calculates the optimized predicted power generation of the photovoltaic power station based on the membership parameter set and the confidence parameter.

[0117] Optionally, the second calculation subunit is specifically used to perform calculations according to the following formula:

[0118]

[0119] in, For the optimized predicted power generation, σ is a confidence parameter. For the first membership parameter, For the second membership parameter, For the third membership parameter and This refers to the fourth membership parameter.

[0120] Optionally, the construction unit is specifically used to construct the cost function of the power system according to the following formula:

[0121]

[0122] in, Let g be the cost function of a conventional generator set. It is the curtailment penalty cost function of the photovoltaic power station v. It is the demand cost function of the aforementioned multi-type load resources. and Let g represent the power generation of the conventional generator unit and v of the photovoltaic power station during time period t, respectively. Ψ represents the response power of various types of load resources during time period t. EG and Ψ PVΨ represents the collection of conventional generator sets and photovoltaic power plants, respectively. TL,SL,IL It represents a collection of multiple types of load resources.

[0123] This application provides a photovoltaic power generation absorption device that reduces the uncertainty of photovoltaic power generation forecasting by using preset confidence parameters. When scheduling photovoltaic power plants, it comprehensively considers the demand of multiple types of composite resources and the operation data of the power system, and can determine the scheduling quantity of photovoltaic power plants that bring the greatest economic benefits, thereby improving the photovoltaic power generation absorption capacity of the power system and greatly enhancing the effectiveness of the power system scheduling strategy.

[0124] This application also provides a computer device, including: a memory, a processor, and a bus system;

[0125] The memory is used to store programs;

[0126] The processor is used to execute the program in the memory to implement any of the photovoltaic power generation consumption methods described above;

[0127] The bus system is used to connect the memory and the processor to enable communication between the memory and the processor.

[0128] This application also provides a computer-readable storage medium storing instructions that, when run on a computer, cause the computer to execute any of the photovoltaic power generation consumption methods described above.

[0129] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0130] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for absorbing photovoltaic power generation, characterized in that, include: To obtain the initial predicted power generation of photovoltaic power plants, the capacity parameters of various types of load resources, and the operating data of the power system; The optimized predicted power generation of the photovoltaic power station is calculated based on the initial predicted power generation and preset confidence parameters; wherein, the calculation of the optimized predicted power generation of the photovoltaic power station based on the initial predicted power generation and preset confidence parameters includes: calculating a membership parameter set based on the initial predicted power generation and a proportionality coefficient, wherein the proportionality coefficient is calculated based on the historical power generation of the photovoltaic power station; calculating the optimized predicted power generation of the photovoltaic power station based on the membership parameter set and the confidence parameters; the membership parameter set includes a first membership parameter, a second membership parameter, a third membership parameter, and a fourth membership parameter; the calculation of the optimized predicted power generation of the photovoltaic power station based on the membership parameter set and the confidence parameters specifically includes: ； in, To optimize the predicted power generation, As a confidence parameter, For the first membership parameter, For the second membership parameter, For the third membership parameter and This refers to the fourth membership parameter; Calculate the demand for the various types of load resources based on their capacity parameters. The cost function of the power system is constructed based on the optimized predicted power generation, the demand for various types of load resources, and the operating data; wherein, the construction of the cost function of the power system based on the optimized predicted power generation, the demand for various types of load resources, and the operating data specifically includes: ； in, For the cost function of conventional generator sets, It is the cost function of the curtailment penalty for the photovoltaic power station. It is the demand cost function of the aforementioned multi-type load resources. and These represent the power generation of the conventional generator set and the photovoltaic power station during time period t, respectively. This represents the response power of various types of load resources during time period t. and These represent collections of conventional generator sets and photovoltaic power plants, respectively. Represents a collection of multiple types of load resources; Based on the cost function and constraints, the scheduling quantity of the photovoltaic power station is determined, wherein the constraints include the cost function taking the minimum value; The photovoltaic power station is scheduled according to the specified scheduling amount.

2. A photovoltaic power generation absorption device, characterized in that, include: The acquisition unit is used to acquire the initial predicted power generation of the photovoltaic power plant, the capacity parameters of various types of load resources, and the operating data of the power system. The first calculation unit is used to calculate the optimized predicted power generation of the photovoltaic power station based on the initial predicted power generation and the preset confidence parameters. The first calculation unit includes: a first calculation subunit, used to calculate a membership parameter set based on the initial predicted power generation and the proportional coefficient, wherein the proportional coefficient is calculated based on the historical power generation of the photovoltaic power station; and a second calculation subunit, used to calculate the optimized predicted power generation of the photovoltaic power station based on the membership parameter set and the confidence parameter. The membership parameter set includes a first membership parameter, a second membership parameter, a third membership parameter, and a fourth membership parameter; the second calculation subunit is specifically used to perform calculations according to the following formula: ； in, To optimize the predicted power generation, As a confidence parameter, For the first membership parameter, For the second membership parameter, For the third membership parameter and This refers to the fourth membership parameter; The second calculation unit is used to calculate the demand of the multi-type load resources based on the capacity parameters of the multi-type load resources. A construction unit is used to construct the cost function of the power system based on the optimized predicted power generation, the demand of the multi-type load resources, and the operating data. The construction unit is specifically used to construct the cost function of the power system according to the following formula: ； in, Let g be the cost function of a conventional generator set. It is the curtailment penalty cost function of the photovoltaic power station v. It is the demand cost function of the aforementioned multi-type load resources. and Let g represent the power generation of the conventional generator unit and v of the photovoltaic power station during time period t, respectively. This represents the response power of various types of load resources during time period t. and These represent collections of conventional generator sets and photovoltaic power plants, respectively. Represents a collection of multiple types of load resources; The determining unit is used to determine the dispatch quantity of the photovoltaic power station based on the cost function and constraints, wherein the constraints include the cost function taking the minimum value; The scheduling unit is used to schedule the photovoltaic power station according to the scheduling quantity.

3. A computer device, characterized in that, include: Memory, processor, and bus system; The memory is used to store programs; The processor is used to execute the program in the memory to implement the method of claim 1; The bus system is used to connect the memory and the processor to enable communication between the memory and the processor.

4. A computer-readable storage medium, characterized in that, The device stores instructions that, when run on a computer, cause the computer to perform the method as described in claim 1.

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