A photovoltaic power station scheduling method and device based on electricity price fluctuation factor and medium

Abstract

This invention relates to a photovoltaic (PV) power plant scheduling method, equipment, and medium based on electricity price fluctuation factors, belonging to the field of PV power plant scheduling technology. The method includes the following steps: determining the solar declination angle, sequentially obtaining the solar altitude angle, optimal PV tilt angle, and azimuth angle, and then calculating the ideal power generation of the PV power plant. Based on historical time-of-use (TOU) electricity prices, the electricity price fluctuation factor and electricity price response intention are extracted and input into an LSTM model along with historical electricity prices to output a predicted TOU electricity price. Combining the energy storage cost coefficient and system capacity, a scheduling plan that maximizes PV scheduling revenue is constructed using the ideal power generation and predicted electricity price. This invention introduces fluctuation factors and response intentions into electricity price prediction, overcoming the limitations of traditional methods that rely solely on historical data.

Description

Technical Field

[0001] This invention relates to a photovoltaic power plant dispatching method, equipment, and medium based on electricity price fluctuation factors, belonging to the field of photovoltaic power plant dispatching technology. Background Technology

[0002] With the accelerated transformation of the global energy structure, photovoltaic power generation, as an important component of clean and renewable energy, continues to increase its penetration rate in the power system. However, photovoltaic power generation has significant intermittent and fluctuating characteristics, and its output is affected by natural factors such as solar radiation intensity and weather conditions, making it difficult to accurately predict power generation.

[0003] Against the backdrop of deepening power market reform, time-of-use pricing mechanisms have become an important means of guiding user-side demand response and optimizing resource allocation. The dispatch and operation of photovoltaic (PV) power plants no longer solely pursues maximizing power generation, but requires comprehensive consideration of electricity price fluctuations and the optimization of economic benefits through flexible charging and discharging strategies. However, existing PV power plant dispatch methods often suffer from the following shortcomings: in terms of electricity price forecasting and response strategies, there is a lack of in-depth analysis of electricity price fluctuation characteristics, and a failure to effectively establish a quantitative correlation between electricity price fluctuation factors and user response intentions. This results in insufficient sensitivity of dispatch decisions to market price signals, making it difficult to capture optimal trading opportunities within peak-valley price differences.

[0004] Therefore, there is an urgent need for a photovoltaic power plant scheduling method based on electricity price fluctuation factors to improve the overall operational efficiency of photovoltaic power generation systems. Summary of the Invention

[0005] To address the problems existing in the prior art, this invention proposes a photovoltaic power plant scheduling method, equipment, and medium based on electricity price fluctuation factors.

[0006] The technical solution of the present invention is as follows: On the one hand, this invention provides a photovoltaic power plant dispatching method based on electricity price fluctuation factors, comprising the following steps: Determine the solar declination angle, and obtain the solar altitude angle based on the solar declination angle; The optimal photovoltaic tilt angle is obtained based on the solar altitude angle, and the optimal photovoltaic azimuth angle is obtained based on the solar declination angle. The ideal power generation of the photovoltaic power station is obtained based on the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle. Obtain historical time-of-use electricity prices, and based on these historical time-of-use electricity prices, obtain the electricity price volatility factor and the willingness to respond to electricity prices; The historical time-of-use electricity price, electricity price volatility factor, and electricity price response intention are used as inputs to the LSTM model, and the output is the time-of-use electricity price prediction value. Set the energy storage cost coefficient, determine the energy storage system capacity, and obtain a photovoltaic dispatch plan with the goal of maximizing photovoltaic dispatch revenue based on the ideal power generation, energy storage cost coefficient, time-of-use electricity price forecast, and energy storage system capacity.

[0007] Preferably, the specific steps for obtaining the solar altitude angle based on the solar declination angle are as follows: Determine the time difference, and obtain true solar time based on the time difference; The hour angle is obtained based on the true solar time; The solar altitude angle is obtained based on the hour angle and the solar declination angle.

[0008] Preferably, the solar ray angle is set, and the optimal photovoltaic tilt angle is obtained by combining the solar ray angle and the solar altitude angle.

[0009] Preferably, the solar azimuth angle is obtained using a two-parameter arctangent function based on the hour angle and the solar declination angle; The solar azimuth angle is taken as the optimal photovoltaic azimuth angle.

[0010] Preferably, the specific steps for obtaining the ideal power generation of the photovoltaic power station based on the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle are as follows: The cosine of the incident angle is obtained based on the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle. The total radiation of the tilted surface of the photovoltaic module is obtained based on the cosine of the incident angle; Obtain the temperature of the photovoltaic cell and construct a temperature correction factor based on the photovoltaic cell temperature; The ideal power generation of the photovoltaic power station is obtained based on the temperature correction factor and the total radiation of the tilted surface.

[0011] Preferably, the historical standard deviation of historical time-of-use electricity prices is calculated as the electricity price volatility factor.

[0012] Preferably, the willingness to respond to electricity prices is quantified using the Sigmoid function based on the electricity price volatility factor.

[0013] Preferably, an electricity price information vector is constructed based on the historical time-of-use electricity price, electricity price fluctuation factor, and electricity price response intention. The electricity price information vector is used as the input of the LSTM model to output the historical electricity price hidden state vector. Time-of-use (TOU) electricity price predictions are obtained using a fully connected layer based on the hidden state vector of historical electricity prices.

[0014] In another aspect, the present invention also provides an electronic device having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the photovoltaic power plant scheduling method based on the electricity price fluctuation factor as described in any embodiment of the present invention.

[0015] In another aspect, the present invention also provides a computer-readable storage medium for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the photovoltaic power plant scheduling method based on electricity price fluctuation factor as described in any embodiment of the present invention.

[0016] The present invention has the following beneficial effects: 1. This invention determines the optimal photovoltaic tilt and azimuth angles by dynamically tracking changes in the sun's position, changing the traditional extensive mode of fixed installation or simple seasonal adjustment. Since the solar altitude and azimuth angles are constantly changing throughout the day and across different seasons, the hourly optimal tracking strategy ensures that the photovoltaic modules always maintain the best orientation for receiving sunlight. This dynamic adjustment mechanism significantly reduces the cosine loss of incident light, ensuring maximum capture of solar radiation energy at different times, thereby effectively improving the overall light energy conversion efficiency of the photovoltaic power station.

[0017] 2. This invention introduces two key variables—electricity price volatility factor and willingness to respond to electricity prices—in the electricity price forecasting process, overcoming the limitations of traditional methods that rely solely on simple extrapolation from historical electricity price data. By quantitatively correlating electricity price volatility characteristics with user response behavior, a more complete electricity price information vector is constructed as the model input. This multi-dimensional feature fusion approach enables the Long Short-Term Memory (LSTM) network to more profoundly capture the nonlinear fluctuation patterns and potential trend characteristics in the electricity price sequence, thereby outputting more reliable time-of-use (TOU) electricity price forecasts and laying a solid data foundation for subsequent dispatching decisions. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the implementation of the method in an embodiment of the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0021] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0022] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0023] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0024] Example 1: See Figure 1 This embodiment provides a photovoltaic power plant dispatching method based on electricity price fluctuation factors, including the following steps: S1. Obtain the solar declination angle, expressed by the formula: ; In the formula, Indicates the solar declination angle. It indicates the day of the year (January 1st is 1, December 31st is 365). S2. Obtain the solar altitude angle based on the solar declination angle. The specific steps are as follows: S201. When obtaining the true sun, the formula is as follows: ; In the formula, express True solar time for a given period is based on 12:00 noon. express The local standard time of the time period, such as Beijing time. This indicates the reference longitude for standard time, such as Beijing time corresponding to East longitude. , Indicates the geographical longitude of the photovoltaic power station. Indicates time difference; S202. Obtain the hour angle based on the true solar time, expressed by the formula: ; In the formula, express The hour angle of the time period; S203. Obtain the solar altitude angle based on the hour angle and solar declination angle, expressed by the formula: ; In the formula, express Solar altitude angle during the time period Indicates the geographical latitude of the photovoltaic power station; Transforming the above formula, we can express it as follows: ; In one embodiment, the time difference is expressed by the formula: ; In the formula, Indicates the sun angle parameter; The solar angle parameter is expressed by the formula: .

[0025] When performing calculations, angles in trigonometric functions must first be converted to radians.

[0026] S3. Obtain the optimal photovoltaic tilt angle based on the solar altitude angle, expressed by the formula: ; In the formula, express Optimal photovoltaic tilt angle for the time period This represents the angle of sunlight, set to 90°.

[0027] S4. Obtain the solar azimuth angle based on the solar declination angle and hour angle, and use the solar azimuth angle as the optimal photovoltaic azimuth angle, expressed by the formula: ; ; In the formula, express The optimal photovoltaic azimuth angle for the time period express Sun azimuth angle during the time period This represents the two-parameter arctangent function, which returns a value in radians and requires multiplication. Convert to degrees, with a range of (-180°, 180°), where 0° is due south, positive values ​​are west, and negative values ​​are east.

[0028] The tilt angle and azimuth angle of the photovoltaic modules in the photovoltaic power station are adjusted in real time according to the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle to maximize the power generation efficiency.

[0029] S5. Based on the optimal photovoltaic tilt angle and optimal photovoltaic azimuth angle, obtain the ideal power generation of the photovoltaic power station. The specific steps are as follows: S501. Based on the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle, obtain the cosine of the incident angle, expressed by the formula: ; In the formula, express The angle of solar incidence during the time period, Represents the cosine of the angle of incidence; S502. The total radiation of the tilted surface of the photovoltaic module is obtained based on the cosine of the incident angle, expressed by the formula: ; In the formula, Indicates that photovoltaic modules are in Total radiation from the inclined surface during the time period, Indicates that photovoltaic modules are in Normal direct radiation during the time period, Indicates that photovoltaic modules are in Horizontal diffuse radiation over a period of time This represents the ground reflectance; for example, 0.2 is used for grass and 0.8 for snow. express Total horizontal radiation over a given period; S503. Obtain the temperature of the photovoltaic cell, expressed by the formula: ; In the formula, express Photovoltaic cell temperature during the period express Ambient temperature during the period, Indicates the nominal operating battery temperature; S504. Construct a temperature correction factor based on the photovoltaic cell temperature, expressed by the formula: ; In the formula, express Temperature correction factor for the time period Indicates the power temperature coefficient; S505. Based on the aforementioned temperature correction factor and the total radiation of the tilted surface, the ideal power generation of the photovoltaic power station is obtained, expressed by the formula: ; In the formula, Indicates that the photovoltaic power station is Ideal power generation during a given period Indicates the area of ​​the photovoltaic module. This represents the photoelectric conversion efficiency coefficient.

[0030] S6. Obtain historical time-of-use electricity prices and calculate the historical standard deviation of historical time-of-use electricity prices as the electricity price volatility factor.

[0031] S7. Based on the electricity price volatility factor, the Sigmoid function is used to quantify the willingness to respond to electricity prices, expressed by the formula: ; In the formula, Indicates willingness to respond to electricity prices. Indicates the bias parameter. Represents the slope parameter. Indicates the historical standard deviation.

[0032] S8. Construct an electricity price information vector based on the historical time-of-use electricity price, electricity price fluctuation factor, and electricity price response intention. Use the electricity price information vector as the input of the LSTM model and output the historical electricity price hidden state vector.

[0033] S9. Based on the historical electricity price hidden state vector, a fully connected layer is used to obtain the time-of-use electricity price prediction value, which is expressed by the formula: ; In the formula, express Forecast values ​​of time-of-use electricity prices for different time periods. This represents the weight matrix of the fully connected layer. This represents the bias vector of the fully connected layer. express The hidden state vector of electricity price for a given time period.

[0034] S10. Set the energy storage cost coefficient and determine... The energy storage system capacity for a given time period is used to obtain a photovoltaic dispatch plan aimed at maximizing photovoltaic dispatch revenue, based on the ideal power generation, energy storage cost coefficient, time-of-use electricity price forecast, and energy storage system capacity.

[0035] The photovoltaic scheduling plan is as follows: like If the time-of-use electricity price is greater than or equal to the energy storage cost coefficient, the energy storage system will start discharging and sell the electricity discharged by the energy storage system and the ideal power generation of the photovoltaic power station to the grid. like If the time-of-use electricity price is less than the energy storage cost coefficient, the ideal power generation of the photovoltaic power station will be transferred to the energy storage system for storage first, until the energy storage system reaches its upper limit of energy storage capacity, and then the excess power (excess power = ideal power generation - energy storage power) will be sold to the grid.

[0036] If the energy storage system capacity is 0, it stops discharging; any excess electricity is only sold to the grid when it is positive.

[0037] Example 2: This embodiment provides an electronic device that stores a computer program. When the computer program is executed by a processor, it implements the photovoltaic power plant scheduling method based on electricity price fluctuation factor as described in any embodiment of the present invention.

[0038] Example 3: This embodiment provides a computer-readable storage medium for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the photovoltaic power plant scheduling method based on electricity price fluctuation factor as described in any embodiment of the present invention.

[0039] In this application embodiment, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, A and B simultaneously, or B alone. A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one of a, b, and c can represent: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, and c can be single or multiple.

[0040] Those skilled in the art will recognize that the units and algorithm steps described in the embodiments disclosed herein can be implemented using electronic hardware, computer software, or a combination of electronic hardware and software. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0041] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0042] In the several embodiments provided in this application, any function, if implemented as a software functional unit and sold or used as an independent product, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0043] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A photovoltaic power plant dispatching method based on electricity price fluctuation factors, characterized in that, Includes the following steps: To obtain the ideal power generation of a photovoltaic power plant; Obtain historical time-of-use electricity prices, and based on these historical time-of-use electricity prices, obtain the electricity price volatility factor and the willingness to respond to electricity prices; The historical time-of-use electricity price, electricity price volatility factor, and electricity price response intention are used as inputs to the LSTM model, and the output is the time-of-use electricity price prediction value. Set the energy storage cost coefficient, determine the energy storage system capacity, and obtain a photovoltaic dispatch plan with the goal of maximizing photovoltaic dispatch revenue based on the ideal power generation, energy storage cost coefficient, time-of-use electricity price forecast, and energy storage system capacity.

2. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 1, characterized in that, The method also includes determining the solar declination angle and obtaining the solar altitude angle based on the solar declination angle. The specific steps are as follows: Determine the time difference, and obtain true solar time based on the time difference; The hour angle is obtained based on the true solar time; The solar altitude angle is obtained based on the hour angle and the solar declination angle.

3. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 1, characterized in that, The method also includes setting the solar ray angle and obtaining the optimal photovoltaic tilt angle by using the solar ray angle and the solar altitude angle.

4. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 2, characterized in that, The method further includes obtaining the solar azimuth angle based on the hour angle and the solar declination angle using a two-parameter arctangent function; The solar azimuth angle is taken as the optimal photovoltaic azimuth angle.

5. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 1, characterized in that, The method also includes obtaining the ideal power generation of the photovoltaic power station based on the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle. The specific steps are as follows: The cosine of the incident angle is obtained based on the optimal photovoltaic tilt angle and the optimal photovoltaic azimuth angle. The total radiation of the tilted surface of the photovoltaic module is obtained based on the cosine of the incident angle; Obtain the temperature of the photovoltaic cell and construct a temperature correction factor based on the photovoltaic cell temperature; The ideal power generation of the photovoltaic power station is obtained based on the temperature correction factor and the total radiation of the tilted surface.

6. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 1, characterized in that, The historical standard deviation of historical time-of-use electricity prices is calculated as an electricity price volatility factor.

7. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 1, characterized in that, The willingness to respond to electricity prices is quantified using the Sigmoid function based on the electricity price volatility factor.

8. The photovoltaic power plant dispatching method based on electricity price fluctuation factor according to claim 1, characterized in that, Based on the historical time-of-use electricity price, electricity price fluctuation factor, and willingness to respond to electricity prices, an electricity price information vector is constructed. This electricity price information vector is used as the input of the LSTM model to output the historical electricity price hidden state vector. Time-of-use (TOU) electricity price predictions are obtained using a fully connected layer based on the hidden state vector of historical electricity prices.

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 processor executes the program, it implements the photovoltaic power plant scheduling method based on the electricity price fluctuation factor as described in any one of claims 1 to 8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the photovoltaic power plant scheduling method based on the electricity price fluctuation factor as described in any one of claims 1 to 8.

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