Method and device for determining dip angle and azimuth angle of photovoltaic power station

Abstract

The embodiment of the invention provides a method and a device for determining an inclination angle and an azimuth angle of a photovoltaic power station. The method comprises the following steps: acquiring background data of the photovoltaic power station; based on the background data, calculating the daily total radiation quantity corresponding to any inclination angle assumed value in the inclination angle initial range, and determining the inclination angle assumed value corresponding to the maximum daily total radiation quantity as a reference inclination angle; determining a new inclination angle range by taking the reference inclination angle as a center, and dividing the azimuth angle initial range to obtain three azimuth angle subareas; for each azimuth subarea, performing multi-target optimization on the total income and the unit income by using a Monte Carlo-gradient descent hybrid algorithm, and outputting an optimal inclination angle and an optimal azimuth angle corresponding to the azimuth subarea; and respectively calculating an optimal inclination angle corresponding to each azimuth subarea and a yield rate corresponding to the optimal azimuth angle, and obtaining and outputting the inclination angle and the azimuth angle corresponding to the highest yield rate. The optimal inclination angle and azimuth angle are accurately determined for the photovoltaic power station, and the power generation income of the photovoltaic power station is effectively improved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of photovoltaic power generation, and particularly relates to a method and device for determining the inclination angle and azimuth angle of a photovoltaic power station. BACKGROUND

[0002] In the planning and construction of photovoltaic power stations, accurately setting the inclination angle and azimuth angle is extremely crucial for improving power generation efficiency and economic benefits. At present, the existing technologies for determining the inclination angle and azimuth angle of a photovoltaic power station present a diversified trend. For example, the radiation maximization principle uses NASA meteorological information to calculate the optimal inclination angle in the direction of maximizing the total annual solar radiation; the empirical formula method sets the inclination angle according to the simplified adjustment rule of ±5° to ±15° of the latitude; and the power generation optimization principle strives to achieve the optimal annual photovoltaic array power generation in consideration of the mutual shading between arrays. These methods have accumulated some experience in the application of large ground power stations, but with the development of the photovoltaic industry, the application scenarios are increasingly complex and diverse, including industrial and commercial projects and different types of roof power stations. This puts forward higher requirements for the determination of the inclination angle and azimuth angle, which not only needs to adapt to the diversified site conditions, but also needs to take into account the power consumption characteristics and revenue models of different projects.

[0003] The existing technologies have explored the optimization of the inclination angle and the prediction of the power generation, but in the face of complex and variable actual needs, the existing technologies still need to be further improved and innovated to better meet the needs of accurately determining the inclination angle and azimuth angle of a photovoltaic power station in different scenarios and promote the efficient and sustainable development of the photovoltaic industry. SUMMARY

[0004] Embodiments of the present disclosure provide a method and device for determining the inclination angle and azimuth angle of a photovoltaic power station to solve the related problems existing in the prior art.

[0005] Based on the above problems, in a first aspect, a method for determining the inclination angle and azimuth angle of a photovoltaic power station is provided, comprising:

[0006] obtaining background data of the photovoltaic power station; the background data includes an initial inclination angle range and an initial azimuth angle range;

[0007] based on the background data, calculating the daily total radiation corresponding to any inclination angle assumption value in the initial inclination angle range, and determining the inclination angle assumption value corresponding to the maximum daily total radiation as a reference inclination angle;

[0008] determining a new inclination angle range centered on the reference inclination angle, and dividing the initial azimuth angle range to obtain three azimuth angle partitions;

[0009] for each of the azimuth angle partitions, using a Monte Carlo-Gradient Descent hybrid algorithm to perform multi-objective optimization on the total revenue and unit revenue, and outputting the optimal inclination angle and optimal azimuth angle corresponding to the azimuth angle partition.

[0010] Calculate the yield corresponding to the optimal tilt angle and the optimal azimuth angle of each azimuth angle partition respectively, obtain the tilt angle and azimuth angle corresponding to the highest yield, and output.

[0011] In combination with the first aspect, in a possible implementation, the calculation of the daily total radiation corresponding to any tilt angle assumption value in the initial tilt angle range based on the background data, and the determination of the tilt angle assumption value corresponding to the maximum daily total radiation as the reference tilt angle, comprises:

[0012] In the initial tilt angle range, the tilt angle assumption value is set repeatedly according to a preset step size, and the daily total radiation corresponding to the tilt angle assumption value is calculated by using the radiation calculation model;

[0013] The tilt angle assumption value corresponding to the maximum daily total radiation is determined as the reference tilt angle.

[0014] In combination with the first aspect, in a possible implementation, the background data comprises meteorological information; the meteorological information comprises horizontal total radiation hourly data, normal direct radiation hourly data and horizontal scattering radiation hourly data;

[0015] The input of the radiation calculation model is the tilt angle assumption value, the horizontal total radiation hourly data, the normal direct radiation hourly data and the horizontal scattering radiation hourly data, and the corresponding daily total radiation is output after operation.

[0016] In combination with the first aspect, in a possible implementation, the background data comprises geographical coordinates;

[0017] The determination of the new tilt angle range with the reference tilt angle as the center, the division of the azimuth angle partition and the setting of the range of each partition, comprises:

[0018] The new tilt angle range is determined with the reference tilt angle as the center and the positive and negative preset degrees as the upper and lower limits;

[0019] The change of the power generation in a day based on different azimuth angles is determined based on the geographical coordinates;

[0020] Based on the change of the power generation in a day based on different azimuth angles, the azimuth angle is divided into three different partitions and the range of each partition is set;

[0021] The partitions comprise a morning power generation partition, an afternoon power generation partition and a balanced partition.

[0022] In combination with the first aspect, in a possible implementation, for each azimuth angle partition, a multi-objective optimization of total yield and unit yield is performed by using a Monte Carlo-gradient descent hybrid algorithm, and the optimal tilt angle and the optimal azimuth angle corresponding to the azimuth angle partition are output, which comprises:

[0023] A preset number of sets of the tilt angle and azimuth angle are generated within the specified tilt angle and azimuth angle partition range;

[0024] The hourly irradiance of the inclined plane corresponding to each set of tilt angles and azimuth angles is calculated using a radiation model, and the corresponding hourly power generation is obtained by combining the module efficiency and the total area of ​​the photovoltaic module.

[0025] The total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles are calculated based on the hourly power generation corresponding to each set of tilt angles and azimuth angles.

[0026] Using the total revenue and unit revenue as objective functions, multi-objective optimization is performed to obtain the optimal total revenue and unit revenue, and the tilt angle and azimuth angle corresponding to the optimal total revenue and unit revenue are obtained.

[0027] Using the gradient descent algorithm, the tilt angle and azimuth angle are updated to obtain the optimal tilt angle and optimal azimuth angle that satisfy the preset convergence conditions, and then output.

[0028] In conjunction with the first aspect, in one possible implementation, the step of calculating the hourly slope irradiance corresponding to each set of tilt angles and azimuth angles using a radiation model, and obtaining the corresponding hourly power generation by combining the module efficiency and the total area of ​​the photovoltaic modules, includes:

[0029] Input each set of tilt angles and azimuth angles into the radiation model to obtain the corresponding hourly slope irradiance;

[0030] The rated installed power is obtained by multiplying the component efficiency by the total area of ​​the photovoltaic module;

[0031] The hourly power generation is obtained by multiplying the rated installed power and the hourly slope irradiance.

[0032] In conjunction with the first aspect, in one possible implementation, the step of calculating the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles based on the hourly power generation corresponding to each set of tilt angles and azimuth angles includes:

[0033] Obtain the electricity price model and the hourly load power of the photovoltaic power station; the electricity price model includes: user-side electricity price, grid connection price and their corresponding time periods;

[0034] Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, calculate the smaller value between the hourly power generation and the hourly load power; multiply the smaller value by the duration of the first preset time period by the user-side electricity price corresponding to the first preset time period to obtain the self-consumption revenue per unit time; sum all the self-consumption revenues within the second preset time period to obtain the self-consumption revenue corresponding to the second preset time period.

[0035] Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, the difference between the hourly power generation and the hourly load power is calculated. The difference is multiplied by the grid-connected electricity price corresponding to the first preset time period to obtain the grid-connected revenue corresponding to the first preset time period. All grid-connected revenues in the second preset time period are summed to obtain the grid-connected revenue corresponding to the second preset time period. Wherein, if the difference is negative, the difference is 0.

[0036] Add the self-use income corresponding to the second preset period and the internet access income corresponding to the second preset period to obtain the total income corresponding to the second preset period;

[0037] Divide the total revenue corresponding to the second preset time period by the total area of ​​the photovoltaic modules to obtain the unit revenue corresponding to the second preset time period.

[0038] The length of the second preset time period is one day, one week, one month, or one year.

[0039] In conjunction with the first aspect, in one possible implementation, the step of calculating the optimal tilt angle and the rate of return corresponding to the optimal azimuth angle for each azimuth zone includes:

[0040] The rate of return is obtained by performing a pre-defined weighted calculation on the optimal tilt angle, total return, and unit return corresponding to the optimal azimuth angle for each azimuth zone.

[0041] In conjunction with the first aspect, in one possible implementation, the step of using a gradient descent algorithm to update the inclination and azimuth angles to obtain and output the optimal inclination and azimuth angles that satisfy a preset convergence condition includes:

[0042] Set the learning rate for the gradient descent algorithm;

[0043] Calculate the gradients of the tilt angle and azimuth angle;

[0044] Based on the gradient and learning rate, the tilt angle and azimuth angle are updated;

[0045] Determine whether the updated tilt and azimuth angles meet the preset convergence conditions;

[0046] If the preset convergence condition is not met, return to the step of calculating the gradients of the total benefit and the unit benefit with respect to the tilt angle and azimuth angle; until the preset convergence condition is met, output the corresponding tilt angle and azimuth angle;

[0047] If the preset convergence conditions are met, the corresponding tilt angle and azimuth angle will be output.

[0048] Secondly, a device for determining the tilt angle and azimuth angle of a photovoltaic power station is provided, comprising:

[0049] The data acquisition module is used to acquire background data of the photovoltaic power station; the background data includes: initial range of tilt angle and initial range of azimuth angle;

[0050] The reference tilt angle calculation module is used to calculate the daily total radiation corresponding to any assumed tilt angle value within the initial range of the tilt angle, and to determine the assumed tilt angle value with the largest daily total radiation as the reference tilt angle.

[0051] The range setting and partitioning module is used to determine a new tilt range centered on the reference tilt angle, and to divide the initial azimuth range to obtain three azimuth partitions;

[0052] The revenue calculation module is used to perform multi-objective optimization of total revenue and unit revenue for each azimuth partition using a Monte Carlo-gradient descent hybrid algorithm, and output the optimal tilt angle and optimal azimuth angle corresponding to that azimuth partition.

[0053] The optimization output module is used to calculate the optimal tilt angle and the corresponding rate of return for each azimuth partition, obtain the tilt angle and azimuth angle with the highest rate of return, and output them.

[0054] In conjunction with the second aspect, in one possible implementation, the reference tilt angle calculation module is used to repeatedly set the tilt angle assumption value according to a preset step size within the initial tilt angle range, calculate the daily total radiation corresponding to the tilt angle assumption value using a radiation calculation model, and determine the tilt angle assumption value corresponding to the largest daily total radiation among all daily total radiation values ​​as the reference tilt angle.

[0055] In conjunction with the second aspect, in one possible implementation, the background data includes: meteorological information; the meteorological information includes: hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal diffuse radiation; the input to the radiation calculation model is the assumed tilt angle value, the hourly data of total horizontal radiation, the hourly data of direct normal radiation, and the hourly data of horizontal diffuse radiation, and the corresponding daily total radiation is output after calculation.

[0056] In conjunction with the second aspect, in one possible implementation, the background data includes: geographic coordinates;

[0057] The range setting and partitioning module is used to determine the new tilt angle range with the reference tilt angle as the center and positive and negative preset degrees as the upper and lower limits; to determine the change in power generation at different azimuth angles within a day based on the geographical coordinates; and to divide the initial azimuth angle range into three azimuth angle partitions based on the change in power generation at different azimuth angles within a day.

[0058] The azimuth zoning includes: morning power generation zone, afternoon power generation zone, and balanced zone.

[0059] In conjunction with the second aspect, in one possible implementation, the revenue calculation module is configured to generate a preset number of sets of tilt angles and azimuth angles within the tilt angle and azimuth angle partitions; calculate the hourly slope irradiance corresponding to each set of tilt angles and azimuth angles using a radiation model, and obtain the corresponding hourly power generation by combining the module efficiency and the total area of ​​the photovoltaic module; calculate the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles based on the hourly power generation corresponding to each set of tilt angles and azimuth angles; perform multi-objective optimization with the total revenue and unit revenue as objective functions to obtain the optimal total revenue and unit revenue, and obtain the tilt angle and azimuth angle corresponding to the optimal total revenue and unit revenue; update the tilt angle and azimuth angle using a gradient descent algorithm to obtain the optimal tilt angle and optimal azimuth angle that satisfy the preset convergence conditions and output them.

[0060] In conjunction with the second aspect, in one possible implementation, the revenue calculation module is used to input each set of tilt angles and azimuth angles into the radiation model to obtain the corresponding hourly slope irradiance; multiply the component efficiency by the total area of ​​the photovoltaic components to obtain the rated installed power; and multiply the rated installed power by the hourly slope irradiance to obtain the hourly power generation.

[0061] In conjunction with the second aspect, in one possible implementation, the revenue calculation module is used to obtain the electricity price model and the hourly load power of the photovoltaic power station; the electricity price model includes: user-side electricity price, grid connection price and their corresponding time periods; based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, the smaller value between the hourly power generation and the hourly load power is calculated; the product of the smaller value and the duration of a first preset time period is multiplied by the user-side electricity price corresponding to the first preset time period to obtain the self-consumption revenue corresponding to the first preset time period; the self-consumption revenue within a second preset time period is summed to obtain the self-consumption revenue corresponding to the second preset time period; based on each set of tilt angles and azimuth angles, the revenue calculation module is used to obtain the hourly load power of the photovoltaic power station ... The hourly power generation corresponding to the angle and azimuth angle is calculated, and the difference between the hourly power generation and the hourly load power is calculated. The difference is multiplied by the grid-connected electricity price corresponding to the first preset time period to obtain the grid-connected revenue corresponding to the first preset time period. All grid-connected revenues in the second preset time period are summed to obtain the grid-connected revenue corresponding to the second preset time period. Wherein, if the difference is negative, the difference is taken as 0. The self-consumption revenue corresponding to the second preset time period and the grid-connected revenue corresponding to the second preset time period are added to obtain the total revenue corresponding to the second preset time period. The total revenue corresponding to the second preset time period is divided by the total area of ​​the photovoltaic modules to obtain the unit revenue corresponding to the second preset time period.

[0062] The length of the second preset time period is one day, one week, one month, or one year.

[0063] In conjunction with the second aspect, in one possible implementation, the optimization output module is used to perform a preset weighted calculation on the optimal tilt angle and the total revenue and unit revenue corresponding to each azimuth angle partition to obtain the rate of return.

[0064] In conjunction with the second aspect, in one possible implementation, the optimization output module is used to: set the learning rate of the gradient descent algorithm; calculate the gradients of the total reward and the unit reward with respect to the inclination angle and azimuth angle; update the inclination angle and azimuth angle based on the gradients and the learning rate; determine whether the updated inclination angle and azimuth angle satisfy a preset convergence condition; if the preset convergence condition is not satisfied, return to the step of calculating the gradients of the total reward and the unit reward with respect to the inclination angle and azimuth angle; until the preset convergence condition is satisfied, output the corresponding inclination angle and azimuth angle; if the preset convergence condition is satisfied, output the corresponding inclination angle and azimuth angle.

[0065] Thirdly, a computer device is provided, comprising: a processor, a memory, and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the computer device is running, the processor communicates with the memory via the bus, and when the machine-readable instructions are executed by the processor, the steps of a method for determining the tilt angle and azimuth angle of a photovoltaic power station as described in the first aspect, or in combination with any possible embodiment of the first aspect, are performed.

[0066] Fourthly, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, performs the steps of a method for determining the tilt angle and azimuth angle of a photovoltaic power station as described in the first aspect, or in conjunction with any possible embodiment of the first aspect.

[0067] The beneficial effects of the embodiments disclosed herein include:

[0068] This disclosure provides a method and apparatus for determining the tilt angle and azimuth angle of a photovoltaic power station. Applicable to both large-scale ground-mounted power stations and industrial / commercial distributed photovoltaic power stations, it maximizes power generation efficiency by accurately determining the tilt angle and azimuth angle. The method first obtains background data of the photovoltaic power station, where the initial tilt angle and azimuth angle ranges provide the foundation for subsequent calculations. This data originates from actual factors such as the geographical location and surrounding environment of the power station. Based on the background data, the daily total radiation corresponding to different assumed values ​​within the initial tilt angle range is calculated. By identifying the tilt angle assumption value with the largest daily total radiation, a benchmark tilt angle is determined. This step preliminarily filters out benchmark tilt angles that are beneficial to increasing daily total radiation, laying the foundation for subsequent optimization. A new tilt angle range is determined centered on the benchmark tilt angle, and the initial azimuth angle range is divided into three azimuth angle partitions, making subsequent optimization calculations more targeted and refined. For each azimuth angle partition, a Monte Carlo-gradient descent hybrid algorithm is used to perform multi-objective optimization of total revenue and unit revenue. This comprehensively considers multiple factors to find the optimal tilt angle and optimal azimuth angle for each partition, thereby further improving revenue. The yield rates of the optimal tilt angle and optimal azimuth angle for each azimuth zone are calculated separately, and the tilt angle and azimuth angle with the highest yield rate are output, thus realizing the comprehensive evaluation and selection of the overall scheme.

[0069] In summary, this method, through multi-step collaborative operation and comprehensive consideration of factors such as geography, time, radiation, and returns, can accurately determine the optimal tilt angle and azimuth angle for photovoltaic power plants, effectively improving the power generation revenue of photovoltaic power plants, enhancing their competitiveness in different scenarios, and promoting the efficient development of the photovoltaic industry. Attached Figure Description

[0070] Figure 1 A flowchart illustrating a method for determining the tilt angle and azimuth angle of a photovoltaic power station, provided in an embodiment of this disclosure;

[0071] Figure 2 A diagram illustrating the execution steps of a method for determining the tilt angle and azimuth angle of a photovoltaic power station, provided in an embodiment of this disclosure;

[0072] Figure 3 This is a schematic diagram of a device for determining the tilt angle and azimuth angle of a photovoltaic power station, provided in an embodiment of this disclosure. Detailed Implementation

[0073] This disclosure provides a method and apparatus for determining the tilt angle and azimuth angle of a photovoltaic power station. The preferred embodiments of this disclosure are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustrative and explanatory purposes only and are not intended to limit the scope of this disclosure. Furthermore, the embodiments and features described herein can be combined with each other unless otherwise specified.

[0074] This disclosure provides a method for determining the tilt angle and azimuth angle of a photovoltaic power station, such as... Figure 1 As shown, it includes:

[0075] S101. Obtain background data for the photovoltaic power station; background data includes: initial range of tilt angle and initial range of azimuth angle.

[0076] S102. Based on the background data, calculate the total daily radiation corresponding to any assumed tilt angle within the initial tilt angle range, and determine the assumed tilt angle with the largest corresponding total daily radiation as the reference tilt angle.

[0077] S103. Determine a new tilt range centered on the reference tilt angle, and divide the initial azimuth range to obtain three azimuth zones.

[0078] S104. For each azimuth partition, use the Monte Carlo-gradient descent hybrid algorithm to perform multi-objective optimization of total gain and unit gain, and output the optimal tilt angle and optimal azimuth angle corresponding to the azimuth partition.

[0079] S105. Calculate the optimal tilt angle and the corresponding rate of return for each azimuth zone, obtain the tilt angle and azimuth angle with the highest rate of return and output them.

[0080] The method for determining the tilt angle and azimuth angle of a photovoltaic power station disclosed herein is closely centered on improving the overall benefits of photovoltaic power stations. Its core lies in breaking through the traditional limitation of focusing solely on power generation and comprehensively considering the diverse factors affecting the profitability of photovoltaic power stations.

[0081] The method for determining the tilt angle and azimuth angle of a photovoltaic power station provided in this disclosure firstly considers that the operation of a photovoltaic power station is affected by a variety of factors, and obtains background data, namely the initial range of the tilt angle and the initial range of the azimuth angle, to lay the foundation for subsequent in-depth analysis.

[0082] Next, a new dip angle range was determined centered on the reference dip angle, and the initial azimuth angle range was divided into multiple zones. This concept is related to the invented azimuth angle economic zoning theory. Through joint analysis of irradiance and electricity price, it was found that there are differentiated revenue characteristics in different azimuth angle intervals, and dividing the area allows for a more detailed study of the situation under different azimuth angles.

[0083] Then, for each azimuth angle partition, a Monte Carlo-gradient descent hybrid algorithm is used to perform multi-objective optimization for total revenue and unit revenue, reflecting a dual-objective optimization architecture. This is because in photovoltaic systems, simply pursuing power generation (efficiency) is no longer sufficient; a trade-off between "efficiency" and "economy" must be addressed. By comprehensively considering both total revenue and unit revenue, this algorithm can find the optimal combination of tilt angle and azimuth angle in different azimuth angle partitions, achieving a balance between efficiency and economy.

[0084] Finally, the yield corresponding to the optimal tilt and azimuth angles for each zone is calculated, and the parameters corresponding to the highest yield are output. This is combined with the newly introduced electricity price time-series coupling mechanism. A power generation-electricity price matrix model is established to break through the limitation of simply pursuing power generation. The results obtained from the previous steps are comprehensively evaluated from the perspective of economic benefits, thereby determining the tilt and azimuth angles that will ultimately bring the highest yield.

[0085] In summary, this method comprehensively innovates the traditional determination method. By introducing a time-series coupling mechanism for electricity prices, inventing an economic zoning theory for azimuth angles, and proposing a dual-objective optimization framework, it comprehensively and systematically considers the operation of photovoltaic power plants from multiple dimensions. It realizes the transformation from simply focusing on power generation to comprehensively considering power generation efficiency and economic benefits, and provides a more scientific and innovative method for determining the tilt angle and azimuth angle of photovoltaic power plants.

[0086] In another embodiment provided in this disclosure, step S102 above can be implemented as follows:

[0087] 1. Within the initial range of the tilt angle, repeatedly set the assumed tilt angle value according to the preset step size, and use the radiation calculation model to calculate the daily total radiation corresponding to the assumed tilt angle value;

[0088] 2. Determine the inclination angle corresponding to the largest daily total radiation among all daily total radiation values ​​as the reference inclination angle.

[0089] In this embodiment, firstly, within a given initial tilt angle range, assumed tilt angle values ​​are repeatedly set cyclically according to a preset step size. This setting method aims to comprehensively and systematically cover the entire initial tilt angle range, obtaining relevant data at different angles by setting multiple different assumed values. For example, if the initial tilt angle range is 0° to 60°, and the preset step size is 5°, then assumed tilt angle values ​​of 0°, 5°, 10°, and so on up to 60° will be set sequentially. Next, a radiation calculation model is used to calculate the total daily radiation corresponding to each assumed tilt angle value. The radiation calculation model is constructed based on relevant physical principles and mathematical formulas, and can accurately calculate the total daily radiation received by the photovoltaic power station at different tilt angles. For example, the model may consider the influence of factors such as solar altitude angle and atmospheric transmittance on the radiation. Through this calculation process, a series of total daily radiation data corresponding to different assumed tilt angle values ​​are obtained.

[0090] Then, from these daily total radiation data, the tilt angle corresponding to the largest daily total radiation is determined as the baseline tilt angle. The baseline tilt angle represents the tilt angle that theoretically allows the photovoltaic power station to receive the maximum daily total radiation within a given initial tilt angle range. This provides crucial foundational data for subsequent, more refined optimization work. By first determining the baseline tilt angle and then using it as the center to determine a new tilt angle range, the optimization process becomes more targeted, improving the efficiency of finding the optimal combination of tilt angle and azimuth angle, thereby contributing to improving the overall performance and profitability of the photovoltaic power station.

[0091] In summary, step S102, by systematically setting assumed dip angle values ​​and calculating total daily radiation, determines the baseline dip angle, providing a crucial foundation for subsequent, more targeted determination of new dip angle ranges centered on this baseline dip angle.

[0092] In another embodiment provided in this disclosure, the background data includes: meteorological information; the meteorological information includes: hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal diffuse radiation;

[0093] The inputs to the radiation calculation model are the tilt angle assumption, hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal scattered radiation. After calculation, the corresponding daily total radiation is output.

[0094] In this embodiment of the disclosure, during the determination of the tilt angle and azimuth angle of the photovoltaic power station, the meteorological information includes hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal diffuse radiation. These hourly data record in detail various characteristics of solar radiation at different times.

[0095] The radiation calculation model takes the tilt angle assumption and three types of hourly radiation data as input. For example, when simulating a photovoltaic power plant, a specific tilt angle assumption, such as 30°, is set, and hourly data of total horizontal radiation, direct normal radiation, and diffuse horizontal radiation, recorded hourly from morning to night, are input. This radiation calculation model can be implemented as an improved Liu-Jordan model, which integrates these input data through a series of calculations based on physical principles. Furthermore, during implementation, the azimuth angle can be set to a preset angle according to the actual application scenario. For example, setting the azimuth angle to 0° and the input tilt angle assumption to 30° will calculate the total daily radiation for a photovoltaic power plant with an azimuth angle of 0° and a tilt angle of 30°. During the calculation process, the model will consider the impact of changes in the solar altitude angle at different times on various types of radiation, and how the tilt angle changes the radiation reception, based on its own algorithm. The final output is the total daily radiation corresponding to the tilt angle assumption.

[0096] This method, which combines hourly meteorological data with assumed tilt angle values ​​and inputs them into the radiation calculation model, can accurately simulate the actual daily total radiation received by a photovoltaic power station under different meteorological conditions and tilt angle assumptions. By obtaining a large number of daily total radiation values ​​corresponding to different tilt angle assumptions, it is helpful to screen out the benchmark tilt angle that allows the photovoltaic power station to receive the maximum daily total radiation, providing an important basis for subsequent optimization of the photovoltaic power station's performance.

[0097] In summary, by using hourly radiation data from meteorological information in conjunction with the assumed tilt angle value as input into the radiation calculation model, the total daily radiation can be accurately calculated. This provides data support for determining the optimal tilt angle of photovoltaic power plants and plays an indispensable role in improving the power generation efficiency and economic benefits of photovoltaic power plants.

[0098] In yet another embodiment provided in this disclosure, the background data includes: geographic coordinates;

[0099] Step 103 above can be implemented as follows:

[0100] 1. Using the reference tilt angle as the center and positive and negative preset degrees as the upper and lower limits, determine the new tilt angle range;

[0101] II. Determine the changes in power generation at different azimuth angles within a day based on geographical coordinates;

[0102] Third, based on the changes in power generation within a day at different azimuth angles, the initial range of the azimuth angle is divided into three azimuth angle zones.

[0103] The aforementioned azimuth zones include: morning power generation zone, afternoon power generation zone, and balanced zone.

[0104] In this embodiment of the disclosure, the steps of this embodiment first use a determined reference tilt angle as the center, and then sets positive and negative preset degrees to determine a new tilt angle range according to actual needs. For example, if the preset degree is 10° and the reference tilt angle is 30°, then the new tilt angle range is 20° to 40°. This range setting provides a boundary for subsequent research on the performance changes of photovoltaic power plants under different tilt angles, ensuring that the analysis is carried out within a reasonable and targeted angle range, avoiding unnecessary waste of computational resources, and also taking into account the feasibility and limitations of adjusting the tilt angle of photovoltaic panels in actual engineering.

[0105] Next, based on the geographical coordinates of the photovoltaic power station, the variation in power generation within a day at different azimuth angles is determined through relevant calculations or actual monitoring data. Different geographical coordinates imply different solar radiation angles and durations, which directly affect the power generation performance of the photovoltaic power station at different azimuth angles. For example, in the mid-latitude regions of the Northern Hemisphere, east-facing azimuth angles receive sunlight earlier in the morning, resulting in an initial increase in power generation; while west-facing azimuth angles show better power generation performance in the afternoon. By establishing a mathematical model that combines local latitude and longitude, the sun's trajectory, and the power generation characteristics of the photovoltaic power station, the power generation per hour or even shorter time intervals within a day at different azimuth angles can be accurately calculated, thus clearly presenting the curves of power generation variation with azimuth angle and time.

[0106] Then, based on the daily power generation variation patterns at different azimuth angles, the initial azimuth range was divided into three distinct zones, each with its own defined range. The morning power generation zone primarily covers azimuth angles where power generation is highest in the morning. In the example of the mid-latitude region in the Northern Hemisphere, this zone might include an angle from a certain angle north of east to a certain angle south of east, such as 30° north of east to 15° south of east. Within this zone, photovoltaic panels have higher power generation efficiency in the morning, fully utilizing the morning sunlight. The afternoon power generation zone encompasses azimuth angles where power generation is prominent in the afternoon, such as 20° north of west to 25° south of west. In this zone, photovoltaic panels receive sunlight better in the afternoon, achieving higher power generation. The balanced zone refers to azimuth angle ranges where power generation is relatively even between the morning and afternoon, such as a certain angle range near the south, such as 10° east of south to 10° west of south. Within this zone, photovoltaic panels generate power relatively steadily throughout the day, without any significant spikes in power generation during either the morning or afternoon.

[0107] A series of interconnected steps are employed, from determining the new tilt angle range to define the angle intervals for subsequent analysis, to clarifying the daily power generation variations at different azimuth angles, and then dividing the azimuth into zones based on these variations. Through this series of operations, a more detailed understanding of the power generation characteristics of photovoltaic power plants under different angle settings can be obtained. This provides a foundation for subsequently finding the optimal combination of tilt and azimuth angles for different zones, helping to improve the overall power generation efficiency of photovoltaic power plants, achieve more scientific and rational power plant layout and design, and improve the utilization efficiency of solar energy resources.

[0108] In another embodiment provided in this disclosure, step 104 above can be implemented as follows:

[0109] 1. Generate a preset number of tilt and azimuth angles within the tilt and azimuth angle partitions;

[0110] 2. Calculate the hourly slope irradiance corresponding to each set of tilt angles and azimuth angles using the radiation model, and obtain the corresponding hourly power generation by combining the module efficiency and the total area of ​​the photovoltaic module.

[0111] Third, the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles are calculated based on the hourly power generation corresponding to each set of tilt angles and azimuth angles.

[0112] IV. Using total revenue and unit revenue as objective functions, perform multi-objective optimization to obtain the optimal total revenue and unit revenue, and obtain the tilt angle and azimuth angle corresponding to the optimal total revenue and unit revenue.

[0113] 5. Using the gradient descent algorithm, update the tilt angle and azimuth angle to obtain the optimal tilt angle and optimal azimuth angle that meet the preset convergence conditions, and output them.

[0114] In this embodiment of the disclosure, firstly, a preset number of sets of inclination and azimuth angles are generated within the determined inclination and azimuth angle partitions. This operation is equivalent to sampling within a limited area, and the preset number can be determined according to actual needs and computing resources. For example, if the azimuth angle partition range is 0° to 30° and the inclination angle range is 15° to 35°, and 100 sets of data are preset to be generated, then 100 different combinations of inclination and azimuth angles will be randomly or uniformly generated within this area according to certain rules.

[0115] Next, the hourly slope irradiance corresponding to each set of tilt angles and azimuth angles is calculated using the Perez radiation model. The Perez radiation model comprehensively considers factors such as solar position and sky scattering characteristics, enabling it to calculate the hourly irradiance on the tilted surface at different tilt angles and azimuth angles with relatively high accuracy. For example, by inputting a set of data with a tilt angle of 20° and an azimuth angle of 10°, combined with meteorological information, the Perez radiation model can output the hourly slope irradiance corresponding to that set of data. Then, the corresponding hourly power generation is obtained by combining the module efficiency. Module efficiency is a parameter representing the photovoltaic module's ability to convert received radiant energy into electrical energy. The rated installed power is obtained by multiplying the module efficiency by the total area of ​​the photovoltaic module. Then, the actual hourly power generation is obtained by multiplying the rated installed power by the hourly slope irradiance.

[0116] Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, the total revenue and unit revenue corresponding to that set of tilt angles and azimuth angles are further calculated.

[0117] Multi-objective optimization, using total revenue and unit revenue as objective functions, aims to simultaneously optimize these two objectives and find solutions that maximize both. For example, a multi-objective optimization algorithm can select the best combination of total revenue and unit revenue from numerous sets of data to obtain the optimal total revenue and unit revenue, along with their corresponding inclination and azimuth angles.

[0118] Finally, the obtained inclination and azimuth angles are updated using the gradient descent algorithm. Gradient descent is an iterative optimization algorithm that adjusts parameters based on the gradient direction of the objective function, gradually decreasing the objective function value (in this case, adjusting towards better total and unit returns). The inclination and azimuth angles are iteratively updated until a preset convergence condition is met. The resulting optimal inclination and azimuth angles are then output. The preset convergence condition can be that the change in the objective function value over several consecutive iterations is less than a certain threshold, such as 0.001.

[0119] In summary, step 104 generates multiple sets of tilt and azimuth angle data, calculates hourly power generation and revenue using radiation models and component efficiency, and then continuously optimizes through multi-objective optimization and gradient descent algorithms to finally determine the optimal tilt and azimuth angle within each azimuth angle partition. This provides a key technical means to improve the economic benefits of photovoltaic power plants and is of great significance for achieving efficient and stable operation of photovoltaic power plants.

[0120] In another embodiment provided in this disclosure, step two above, calculating the hourly slope irradiance corresponding to each set of tilt angles and azimuth angles using a radiation model, and obtaining the corresponding hourly power generation by combining the component efficiency, can be implemented as follows:

[0121] 1. Input each set of tilt angles and azimuth angles into the radiation model to obtain the corresponding hourly slope irradiance;

[0122] 2. Multiply the module efficiency by the total area of ​​the photovoltaic modules to obtain the rated installed power;

[0123] 3. Multiply the rated installed power and the hourly slope irradiance to obtain the hourly power generation.

[0124] In this embodiment of the disclosure, for each set of tilt angle and azimuth angle data that has been generated, it is first input into the radiation model. Based on the principle of solar radiation, the radiation model comprehensively considers factors such as the sun's position, atmospheric conditions, and the tilt angle and orientation of the photovoltaic panel to accurately calculate the corresponding hourly slope irradiance. For example, at a specific moment, for a set of photovoltaic panels with a tilt angle of 30° and an azimuth angle of 20° east of south, the hourly slope irradiance is calculated to be 750 W / m² using the radiation model, combined with local meteorological information such as solar radiation intensity and atmospheric transparency. Different combinations of tilt angle and azimuth angle, due to different angles of sunlight reception, will cause changes in the parameters input into the radiation model, thus resulting in different hourly slope irradiance results.

[0125] Next, the rated installed capacity is obtained by multiplying the module efficiency by the total area of ​​the photovoltaic module. The module efficiency reflects the photovoltaic module's ability to convert light energy into electrical energy, while the total area of ​​the photovoltaic module determines the scale of solar radiation that can be received. The rated installed capacity obtained by multiplying the two reflects the upper limit of the photovoltaic system's power generation capacity under ideal conditions.

[0126] Finally, the hourly power generation is obtained by multiplying the installed rated power and the hourly slope irradiance. The hourly slope irradiance reflects the actual solar radiation at different times, while the installed rated power represents the system's power generation capacity. Multiplying the two allows for a relatively accurate calculation of the actual power generation of the photovoltaic system at each moment under different tilt and azimuth angles.

[0127] The above process can accurately simulate the power generation of photovoltaic systems under different combinations of tilt and azimuth angles, providing a basis for the design and optimization of photovoltaic systems. By calculating the hourly power generation of different combinations, the most suitable tilt and azimuth angles can be selected to improve the power generation efficiency of photovoltaic systems.

[0128] During implementation, the choice of radiation model can be based on the actual situation; for example, common models such as the Hay model and the Perez model can be selected. When calculating the rated installed power, if the degradation of the modules is taken into account, the degradation coefficient can be appropriately deducted from the module efficiency. For example, assuming a set of tilt angles and azimuth angles are input into the radiation model, the slope irradiance at a certain moment is 500 W / m. 2 The total area of ​​the photovoltaic modules is 100m². 2 If the component efficiency is 0.2, then the rated installed capacity is 0.2 × 100 = 20kW, and the hourly power generation at that moment is 20kW × 500W / m². 2 ÷1000=10kW (here W / m 2 (Convert to kW for unified calculation).

[0129] In summary, this calculation process allows for a systematic analysis of the impact of different tilt and azimuth angles on the power generation of photovoltaic (PV) systems, providing a scientific reference for the planning and implementation of PV projects. It accurately quantifies the power generation capacity of PV power plants at various times under different combinations of tilt and azimuth angles, providing fundamental data support for further evaluating the economic benefits of PV power plants with different angle settings. This facilitates a comprehensive and scientific analysis of the performance of PV power plants under different operating conditions, thus providing a strong basis for determining the optimal tilt and azimuth angles and optimizing the power generation efficiency and economic benefits of PV power plants.

[0130] In another embodiment provided in this disclosure, step three above, calculating the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, can be implemented as follows:

[0131] 1. Obtain the electricity price model and the hourly load power of the photovoltaic power station; wherein, the electricity price model includes: user-side electricity price, grid connection price and their corresponding time periods;

[0132] 2. Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, calculate the smaller value between the hourly power generation and the hourly load power; multiply the smaller value by the duration of the first preset time period by the user-side electricity price corresponding to the first preset time period to obtain the self-consumption revenue corresponding to the first preset time period; sum all the self-consumption revenues within the second preset time period to obtain the self-consumption revenue corresponding to the second preset time period.

[0133] 3. Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, calculate the difference between the hourly power generation and the hourly load power. Multiply the difference by the on-grid electricity price corresponding to the first preset time period to obtain the on-grid revenue corresponding to the first preset time period. Sum all the on-grid revenues in the second preset time period to obtain the on-grid revenue corresponding to the second preset time period. Where the difference is negative, the difference is taken as 0.

[0134] 4. Add the self-use income corresponding to the second preset period and the internet access income corresponding to the second preset period to obtain the total income corresponding to the second preset period;

[0135] 5. Divide the total revenue corresponding to the second preset time period by the total area of ​​the photovoltaic modules to obtain the unit revenue corresponding to the second preset time period;

[0136] The length of the second preset time period is one day, one week, one month, or one year.

[0137] In this embodiment of the disclosure, when calculating the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles, key data is first obtained, namely the electricity price model and the hourly load power of the photovoltaic power station. The electricity price model records in detail the user-side electricity price, the feed-in tariff, and their respective time periods. For example, in a certain region, the electricity price model shows that the peak period is from 10:00 to 18:00 on weekdays, with a user-side electricity price of RMB 1 / kWh and a feed-in tariff of RMB 0.8 / kWh; the off-peak period is from 22:00 to 6:00 the next day, with a user-side electricity price of RMB 0.5 / kWh and a feed-in tariff of RMB 0.4 / kWh, etc. The hourly load power of the photovoltaic power station reflects the electricity demand of the electrical equipment connected to the power station within one hour.

[0138] Based on the hourly power generation corresponding to each set of tilt and azimuth angles, the revenue for the first preset time period is calculated. First, the smaller of the hourly power generation and hourly load power is calculated, as this smaller value represents the actual electricity consumed by the user within the first preset time period. For example, if the hourly power generation is 50kW and the hourly load power is 30kW, then the smaller value is 30kW. Next, this smaller value is multiplied by the duration of the first preset time period, and then multiplied by the user-side electricity price corresponding to that first preset time period to obtain the self-consumption revenue for that first preset time period. Assuming the first preset time period in the above example is 4 hours long and falls within a period with a user-side electricity price of 1 yuan / kWh, then the self-consumption revenue for the first preset time period is 30 × 4 × 1 = 120 yuan. Summing up all such self-consumption revenues within the second preset time period yields the self-consumption revenue for the second preset time period.

[0139] For grid connection revenue, first calculate the difference between hourly power generation and hourly load power. If the difference is positive, it indicates that the power generation in the first preset time period exceeds the hourly load power, and the excess can be sold to the grid. If the difference is negative, it indicates that the hourly load power is greater than the power generation, and the difference is 0, meaning there is no surplus electricity to be sold to the grid. Multiply the difference by the grid connection price corresponding to the first preset time period to obtain the grid connection revenue for that first preset time period. For example, if a time period lasts 4 hours, the hourly power generation is 60kW, the hourly load power is 40kW, the difference is 20kW, and the grid connection price for that time period is 0.8 yuan / kWh, then the grid connection revenue for that time period is 20 × 4 × 0.8 = 64 yuan. Similarly, sum all the grid connection revenue for the second preset time period to obtain the grid connection revenue for the second preset time period.

[0140] Finally, the revenue from self-use and the revenue from grid connection corresponding to the second preset period are added together to obtain the total revenue for the second preset period. In the example above, the total revenue from self-use within one day is 200 yuan, and the total revenue from grid connection is 100 yuan, so the total revenue is 200 + 100 = 300 yuan. Then, the total revenue for the second preset period is divided by the total area of ​​the photovoltaic modules (assuming it is 1000m²). 2 The unit revenue for the second preset time period is calculated as 300 ÷ 1000 = 0.3 yuan / m. 2 In the example above, the second preset time period is one day. However, in actual applications, the length of the second preset time period can be set to one day, one week, one month, or one year, etc., depending on actual needs. There is no limitation here. The selection of different time period lengths can be used to analyze the revenue of photovoltaic power plants under different time scales.

[0141] The above steps, from acquiring basic data to calculating self-consumption revenue and grid connection revenue separately, then summing them to obtain total revenue, and finally calculating unit revenue, provide a comprehensive and accurate quantification of the economic benefits of photovoltaic power plants under different combinations of tilt and azimuth angles during the second preset time period. This provides detailed and accurate data for evaluating the impact of different angle settings on the revenue of photovoltaic power plants, helps determine the optimal tilt and azimuth angles, maximizes the economic benefits of photovoltaic power plants, and provides strong support for the planning, operation, and decision-making of power plants.

[0142] In another embodiment provided in this disclosure, step S105, calculating the optimal tilt angle and the rate of return corresponding to the optimal azimuth angle for each azimuth partition, can be implemented as follows:

[0143] The rate of return is obtained by performing a pre-defined weighted calculation on the optimal tilt angle, total return, and unit return corresponding to the optimal azimuth angle for each azimuth zone.

[0144] In this embodiment, the rate of return is derived by performing a preset weighted calculation on the total return and unit return. By comprehensively considering both total return and unit return, the return situation under different azimuth angle zones can be comprehensively and accurately measured. This avoids situations where judgment is made solely based on total return or unit return, which fails to fully reflect the investment benefits or project value.

[0145] In terms of implementation, the preset weighting calculation can be achieved through a weighted average method. Assuming the total return weight is 0.6 and the unit return weight is 0.4, for a certain azimuth zone, the total return is 100 and the unit return is 80 at the optimal tilt and azimuth angles. Then, the rate of return for that azimuth zone is calculated as: (100 × 0.6 + 80 × 0.4) = 60 + 32 = 92. In this way, the rate of return for different azimuth zones can comprehensively reflect the total return and unit return, providing a more valuable basis for decision-making. This allows decision-makers to make more reasonable assessments and selections of different azimuth zones based on a comprehensive consideration of multiple factors, optimizing resource allocation to achieve better return outcomes.

[0146] In another embodiment provided in this disclosure, step five above, which involves using a gradient descent algorithm to update the inclination and azimuth angles to obtain and output the optimal inclination and azimuth angles that satisfy the preset convergence conditions, can be implemented as follows:

[0147] 1. Set the learning rate for the gradient descent algorithm;

[0148] 2. Calculate the gradients of total revenue and unit revenue with respect to tilt and azimuth;

[0149] 3. Update the tilt and azimuth angles based on the gradient and learning rate;

[0150] 4. Determine whether the updated tilt and azimuth angles meet the preset convergence conditions;

[0151] If the preset convergence condition is not met, return to step 3 to calculate the gradients of the total gain and unit gain with respect to the tilt and azimuth angles; until the preset convergence condition is met, output the corresponding tilt and azimuth angles.

[0152] If the preset convergence conditions are met, the corresponding tilt angle and azimuth angle will be output.

[0153] In this embodiment of the disclosure, the gradient descent algorithm is used to output the optimal inclination and azimuth angles. First, the learning rate of the gradient descent algorithm must be set. The learning rate is a key parameter that determines the step size for updating the inclination and azimuth angles in each iteration. For example, setting the learning rate to 0.01 means that in each update, the change in inclination and azimuth angles is based on the calculated gradient multiplied by 0.01. The learning rate setting needs to be adjusted according to the actual situation. If the learning rate is too large, the algorithm may skip the optimal solution during the search process; if the learning rate is too small, the algorithm's convergence speed will be too slow, increasing computation time.

[0154] Next, the gradients of the total return and unit return with respect to the inclination and azimuth angles are calculated. The gradient is a vector whose direction represents the direction in which the total return and unit return change most rapidly in the inclination and azimuth angle spaces, and whose magnitude reflects the rate of change. The gradients are calculated using mathematical methods such as partial derivatives. For example, the partial derivatives of the total return and unit return with respect to the inclination angle and the partial derivatives with respect to the azimuth angle are calculated separately, thus obtaining the gradient vectors with respect to the inclination and azimuth angles. Suppose that at a certain moment, the partial derivative of the total return with respect to the inclination angle is 2, and the partial derivative with respect to the azimuth angle is -1; the partial derivative of the unit return with respect to the inclination angle is 1, and the partial derivative with respect to the azimuth angle is 3. Then, the gradient vector with respect to the inclination and azimuth angles at this moment is (2+1,-1+3)=(3,2).

[0155] Then, based on the calculated gradient and the set learning rate, the tilt and azimuth angles are updated. Specifically, the current tilt and azimuth angles are each added to the product of the corresponding element in the gradient vector and the learning rate. For example, if the current tilt angle is 30°, the azimuth angle is 40°, the learning rate is 0.01, and the gradient vector is (3,2), then the updated tilt angle is 30° + 3 × 0.01 = 30.03°, and the updated azimuth angle is 40° + 2 × 0.01 = 40.02°.

[0156] Next, it is determined whether the updated inclination and azimuth angles satisfy the preset convergence conditions. The preset convergence conditions can take various forms, such as the change in total revenue and unit revenue being less than a certain threshold, or the magnitude of the gradient vector being less than a certain value. If the preset convergence conditions are not met, the process returns to the step of calculating the gradients of total revenue and unit revenue with respect to the inclination and azimuth angles, continuing the next round of gradient calculation, inclination, and azimuth angle updates until the preset convergence conditions are met. At this point, the corresponding inclination and azimuth angles are output. If the preset convergence conditions are met, the corresponding inclination and azimuth angles are directly output. For example, if the preset convergence condition is that the change in total revenue is less than 0.01, and after a certain round of updates, the total revenue changes from 100 yuan to 100.005 yuan, a change of 0.005 yuan less than 0.01, satisfying the convergence condition, then the current inclination and azimuth angles are output as the optimal solution.

[0157] In this embodiment, the learning rate setting provides the step size basis for updates, the gradient calculation indicates the direction of updates, and the updates based on the gradient and learning rate continuously adjust the tilt angle and azimuth angle. The convergence condition determination decides when the algorithm stops and outputs the optimal solution. Through this process, the gradient descent algorithm can continuously search and approximate the angle combination that achieves the optimal total and unit benefits in the feasible solution space of tilt and azimuth angles. This provides important technical support for the precise design and efficient operation of photovoltaic power plants, and helps to maximize the utilization of solar energy resources and improve economic benefits.

[0158] To facilitate understanding, an embodiment of the method for determining the tilt angle and azimuth angle of a photovoltaic power station provided in this disclosure is provided:

[0159] Let's take a commercial and industrial rooftop project as an example:

[0160] 1. Obtain background data for the photovoltaic power station: latitude λ = 31.2°N, longitude Electricity price during peak hours (8:00-11:00, 13:00-15:00) is 1.2 yuan / kWh, during off-peak hours it is 0.7 yuan / kWh, and during off-peak hours it is 0.3 yuan / kWh.

[0161] 2. The calculated reference tilt angle β0 = 28°;

[0162] 3. Using the reference tilt angle β0 = 28° as the center, set the tilt angle range to 8°-48°, and divide the azimuth angle into zones:

[0163] Zone 1: γ∈[-90°,-20°] (Focusing on morning power generation)

[0164] Zone2: γ∈[-20°, 20°] (Balanced type)

[0165] Zone3: γ∈[20°,90°] (emphasis on afternoon power generation);

[0166] 4. Partition optimization results:

[0167] -Zone1 (γ = -45°): β = 32°, IRR = 15.2%

[0168] -Zone2 (γ=10°): β=28°, IRR = 14.8%

[0169] -Zone3 (γ=60°): β=24°, IRR = 16.1%

[0170] The Zone3 scheme was ultimately selected, with the afternoon peak power generation matching the peak electricity price period. β = 24° and γ = 60° were determined to be the optimal tilt angle and azimuth angle.

[0171] The annual returns for using the method of this invention and the traditional radiation optimization method are shown in Table 1:

[0172] Method Annual income (ten thousand yuan) Traditional radiation optimization method 86.5 The method of the present application 102.7(+16.1％)

[0173] Table 1 Comparison of Experimental Results

[0174] Based on the same disclosed concept, this disclosure also provides a device, equipment, and storage medium for determining the tilt angle and azimuth angle of a photovoltaic power station. Since the principle of solving the problem by these devices, equipment, and storage media is similar to that of the aforementioned method, the implementation of these devices, equipment, and storage media can refer to the implementation of the aforementioned method, and the repeated parts will not be described again.

[0175] With the above Figure 1 Correspondingly, this disclosure also provides a device for determining the tilt angle and azimuth angle of a photovoltaic power station, such as... Figure 3 As shown, it includes:

[0176] Data acquisition module 301 is used to acquire background data of photovoltaic power station; the background data includes: initial range of tilt angle and initial range of azimuth angle;

[0177] The reference tilt angle calculation module 302 is used to calculate the daily total radiation corresponding to any tilt angle assumption value within the initial range of the tilt angle, and determine the tilt angle assumption value with the largest daily total radiation as the reference tilt angle;

[0178] The range setting and partitioning module 303 is used to determine a new tilt range with the reference tilt angle as the center, divide the azimuth angle partitions and set the range of each partition.

[0179] The revenue calculation module 304 is used to perform multi-objective optimization of total revenue and unit revenue for each azimuth partition using a Monte Carlo-gradient descent hybrid algorithm, and output the optimal tilt angle and optimal azimuth angle corresponding to the azimuth partition.

[0180] The optimization output module 305 is used to calculate the optimal tilt angle and the rate of return corresponding to the optimal azimuth angle for each azimuth angle partition, and to obtain and output the tilt angle and azimuth angle with the highest rate of return.

[0181] In another embodiment provided in this disclosure, the reference tilt angle calculation module 302 is used to repeatedly set the tilt angle assumption value according to a preset step size within the initial tilt angle range, calculate the daily total radiation corresponding to the tilt angle assumption value using a radiation calculation model, and determine the tilt angle assumption value corresponding to the largest daily total radiation among all daily total radiation values ​​as the reference tilt angle.

[0182] In another embodiment provided in this disclosure, the background data includes: meteorological information; the meteorological information includes: hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal diffuse radiation;

[0183] The inputs to the radiation calculation model are the tilt angle assumption, hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal scattered radiation. After calculation, the corresponding daily total radiation is output.

[0184] In yet another embodiment provided in this disclosure, the background data includes: geographic coordinates;

[0185] The range setting and partitioning module 303 is used to determine a new tilt angle range with the reference tilt angle as the center and positive and negative preset degrees as the upper and lower limits; to determine the change in power generation at different azimuth angles within a day based on geographical coordinates; and to divide the initial azimuth angle range into three azimuth angle partitions based on the change in power generation at different azimuth angles within a day.

[0186] The azimuth zones include: morning power generation zone, afternoon power generation zone, and balanced zone.

[0187] In another embodiment provided in this disclosure, the revenue calculation module 304 is used to generate a preset number of sets of tilt angles and azimuth angles within the tilt angle and azimuth angle partition range; calculate the hourly slope irradiance corresponding to each set of tilt angles and azimuth angles using a radiation model, and obtain the corresponding hourly power generation by combining the component efficiency; calculate the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles based on the hourly power generation corresponding to each set of tilt angles and azimuth angles; perform multi-objective optimization with the total revenue and unit revenue as objective functions to obtain the optimal total revenue and unit revenue, and obtain the tilt angle and azimuth angle corresponding to the optimal total revenue and unit revenue; update the tilt angle and azimuth angle using a gradient descent algorithm to obtain the optimal tilt angle and optimal azimuth angle that meet the preset convergence conditions and output them.

[0188] In another embodiment provided in this disclosure, the revenue calculation module 304 is used to input each set of tilt angle and azimuth angle into the radiation model to obtain the corresponding hourly slope irradiance; multiply the module efficiency and the total area of ​​the photovoltaic module to obtain the installed rated power; and multiply the installed rated power and the hourly slope irradiance to obtain the hourly power generation.

[0189] In another embodiment provided in this disclosure, the revenue calculation module 304 is used to obtain the electricity price model and the hourly load power of the photovoltaic power station; the electricity price model includes: user-side electricity price, grid connection price and their corresponding time periods; based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, the smaller value between the hourly power generation and the hourly load power is calculated; the product of the smaller value and the duration of a first preset time period is multiplied by the user-side electricity price corresponding to the first preset time period to obtain the self-consumption revenue corresponding to the first preset time period; all self-consumption revenues within a second preset time period are summed to obtain the self-consumption revenue corresponding to the second preset time period; based on each set of tilt angles and azimuth angles, the revenue calculation module 304 is used to obtain the hourly load power of the photovoltaic power station ... The hourly power generation corresponding to the azimuth angle is calculated. The difference between the hourly power generation and the hourly load power is calculated. The difference is multiplied by the grid-connected electricity price corresponding to the first preset time period to obtain the grid-connected revenue corresponding to the first preset time period. All grid-connected revenues in the second preset time period are summed to obtain the grid-connected revenue corresponding to the second preset time period. Where the difference is negative, the difference is taken as 0. The self-consumption revenue corresponding to the second preset time period and the grid-connected revenue corresponding to the second preset time period are added to obtain the total revenue corresponding to the second preset time period. The total revenue corresponding to the second preset time period is divided by the total area of ​​the photovoltaic modules to obtain the unit revenue corresponding to the second preset time period.

[0190] The length of the second preset time period is one day, one week, one month, or one year.

[0191] In another embodiment provided in this disclosure, the optimization output module 305 is used to perform preset weight calculations on the optimal tilt angle and the total revenue and unit revenue corresponding to the optimal azimuth angle for each azimuth angle partition to obtain the rate of return.

[0192] In another embodiment provided in this disclosure, the optimization output module 305 is used to set the learning rate of the gradient descent algorithm; calculate the gradients of the total reward and the unit reward with respect to the inclination angle and the azimuth angle; update the inclination angle and the azimuth angle based on the gradients and the learning rate; determine whether the updated inclination angle and the azimuth angle meet the preset convergence conditions; if the preset convergence conditions are not met, return to the step of calculating the gradients of the total reward and the unit reward with respect to the inclination angle and the azimuth angle; until the preset convergence conditions are met, output the corresponding inclination angle and the azimuth angle; if the preset convergence conditions are met, output the corresponding inclination angle and the azimuth angle.

[0193] This disclosure provides a computer device, including a processor, a memory, and a bus. The memory stores machine-readable instructions executable by the processor. When the computer device is running, the processor communicates with the memory via the bus. When the machine-readable instructions are executed by the processor, they perform the steps of a method for determining the tilt angle and azimuth angle of a photovoltaic power station provided in any embodiment of this disclosure.

[0194] The computer device provided in this disclosure includes a processor, a memory, and a bus. The memory, also known as internal memory, stores execution instructions and includes main memory and external memory. The main memory temporarily stores data processed by the processor, as well as data exchanged with external storage devices such as hard disks. The processor exchanges data with external storage devices through main memory. When the electronic device is running, the processor and memory communicate via the bus, enabling the processor to execute the following instructions:

[0195] Obtain background data for the photovoltaic power plant; background data includes: initial range of tilt angle and initial range of azimuth angle.

[0196] Based on the background data, calculate the daily total radiation corresponding to any assumed tilt angle within the initial tilt angle range, and determine the tilt angle with the largest daily total radiation as the reference tilt angle;

[0197] A new tilt range is determined with the reference tilt angle as the center, and the initial azimuth range is divided to obtain three azimuth zones;

[0198] For each azimuth partition, a Monte Carlo-gradient descent hybrid algorithm is used to perform multi-objective optimization of total gain and unit gain, and output the optimal tilt angle and optimal azimuth angle corresponding to the azimuth partition.

[0199] Calculate the optimal tilt angle and the corresponding rate of return for each azimuth zone, obtain the tilt angle and azimuth angle with the highest rate of return, and output them.

[0200] This disclosure provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program performs the steps of a method for determining the tilt angle and azimuth angle of a photovoltaic power station according to any embodiment of this disclosure. The storage medium can be volatile or non-volatile computer-readable storage.

[0201] Through the above description of the embodiments, those skilled in the art can clearly understand that the embodiments of this disclosure can be implemented in hardware or by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solutions of the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) and includes several instructions to cause a computer device (such as a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments of this disclosure.

[0202] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of a preferred embodiment, and the modules or processes in the drawings are not necessarily essential for implementing this disclosure.

[0203] Those skilled in the art will understand that the modules in the apparatus of the embodiments can be distributed in the apparatus of the embodiments as described in the embodiments, or they can be located in one or more devices different from this embodiment with corresponding changes. The modules of the above embodiments can be combined into one module, or they can be further divided into multiple sub-modules.

[0204] The sequence numbers of the embodiments disclosed above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0205] Obviously, those skilled in the art can make various modifications and variations to this disclosure without departing from its spirit and scope. Therefore, if such modifications and variations fall within the scope of the claims of this disclosure and their equivalents, this disclosure is also intended to include such modifications and variations.

Claims

1. A method for determining the tilt angle and azimuth angle of a photovoltaic power station, characterized in that, include: Obtain background data for photovoltaic power plants; The background data includes: initial range of tilt angle and initial range of azimuth angle; Based on the background data, calculate the total daily radiation corresponding to any assumed tilt angle within the initial tilt angle range, and determine the assumed tilt angle with the largest corresponding total daily radiation as the reference tilt angle; A new tilt angle range is determined with the reference tilt angle as the center, and the initial azimuth angle range is divided to obtain three azimuth angle partitions; For each azimuth partition, a Monte Carlo-gradient descent hybrid algorithm is used to perform multi-objective optimization of total gain and unit gain, and output the optimal tilt angle and optimal azimuth angle corresponding to the azimuth partition. Calculate the optimal tilt angle and the corresponding rate of return for each azimuth zone, obtain the tilt angle and azimuth angle with the highest rate of return, and output them.

2. The method as described in claim 1, characterized in that, The step of calculating the daily total radiation corresponding to any assumed tilt angle within the initial tilt angle range based on the background data, and determining the assumed tilt angle with the largest daily total radiation as the reference tilt angle, includes: Within the initial range of the tilt angle, the tilt angle assumption value is set repeatedly according to a preset step size, and the daily total radiation corresponding to the tilt angle assumption value is calculated using a radiation calculation model. The inclination angle corresponding to the largest daily total radiation among all daily total radiations is assumed to be the reference inclination angle.

3. The method as described in claim 2, characterized in that, The background data includes: meteorological information; the meteorological information includes: hourly data of total horizontal radiation, hourly data of direct normal radiation, and hourly data of horizontal diffuse radiation; The inputs to the radiation calculation model are the assumed tilt angle, the hourly data of total horizontal radiation, the hourly data of direct normal radiation, and the hourly data of horizontal scattered radiation. After calculation, the corresponding daily total radiation is output.

4. The method as described in claim 1, characterized in that, The background data includes: geographic coordinates; The process involves determining a new tilt range centered on the reference tilt angle, and dividing the initial azimuth range into three azimuth zones, including: With the reference tilt angle as the center and positive and negative preset degrees as the upper and lower limits, the new tilt angle range is determined; Based on the geographical coordinates, determine the changes in power generation within a day at different azimuth angles; Based on the changes in power generation within a day at different azimuth angles, the initial range of the azimuth angle is divided into three azimuth angle zones. The azimuth zoning includes: morning power generation zone, afternoon power generation zone, and balanced zone.

5. The method as described in claim 1, characterized in that, For each azimuth partition, a Monte Carlo-gradient descent hybrid algorithm is used to perform multi-objective optimization of total gain and unit gain, outputting the optimal tilt angle and optimal azimuth angle corresponding to that azimuth partition, including: A preset number of sets of the tilt angle and azimuth angle are generated within the specified tilt angle and azimuth angle partition range; The hourly irradiance of the inclined plane corresponding to each set of tilt angles and azimuth angles is calculated using a radiation model, and the corresponding hourly power generation is obtained by combining the module efficiency and the total area of ​​the photovoltaic module. The total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles are calculated based on the hourly power generation corresponding to each set of tilt angles and azimuth angles. Using the total revenue and unit revenue as objective functions, multi-objective optimization is performed to obtain the optimal total revenue and unit revenue, and the tilt angle and azimuth angle corresponding to the optimal total revenue and unit revenue are obtained. Using the gradient descent algorithm, the tilt angle and azimuth angle are updated to obtain the optimal tilt angle and optimal azimuth angle that satisfy the preset convergence conditions, and then output.

6. The method as described in claim 5, characterized in that, The calculation of hourly slope irradiance corresponding to each set of tilt angles and azimuth angles using a radiation model, and the resulting hourly power generation based on module efficiency and total photovoltaic module area, includes: Input each set of tilt angles and azimuth angles into the radiation model to obtain the corresponding hourly slope irradiance; The rated installed power is obtained by multiplying the component efficiency by the total area of ​​the photovoltaic module; The hourly power generation is obtained by multiplying the rated installed power and the hourly slope irradiance.

7. The method as described in claim 5, characterized in that, The calculation of the total revenue and unit revenue corresponding to each set of tilt angles and azimuth angles based on the hourly power generation corresponding to each set of tilt angles and azimuth angles includes: Obtain the electricity price model and the hourly load power of the photovoltaic power station; the electricity price model includes: user-side electricity price, grid connection price and their corresponding time periods; Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, calculate the smaller value between the hourly power generation and the hourly load power; multiply the smaller value by the duration of the first preset time period by the user-side electricity price corresponding to the first preset time period to obtain the self-consumption revenue corresponding to the first preset time period; sum all the self-consumption revenues within the second preset time period to obtain the self-consumption revenue corresponding to the second preset time period. Based on the hourly power generation corresponding to each set of tilt angles and azimuth angles, the difference between the hourly power generation and the hourly load power is calculated. The difference is multiplied by the grid-connected electricity price corresponding to the first preset time period to obtain the grid-connected revenue corresponding to the first preset time period. All grid-connected revenues in the second preset time period are summed to obtain the grid-connected revenue corresponding to the second preset time period. Wherein, if the difference is negative, the difference is 0. Add the self-use income corresponding to the second preset period and the internet access income corresponding to the second preset period to obtain the total income corresponding to the second preset period; Divide the total revenue corresponding to the second preset time period by the total area of ​​the photovoltaic modules to obtain the unit revenue corresponding to the second preset time period. The length of the second preset time period is one day, one week, one month, or one year.

8. The method as described in claim 1, characterized in that, The calculation of the optimal tilt angle and the rate of return corresponding to the optimal azimuth angle for each azimuth zone includes: The rate of return is obtained by performing a pre-defined weighted calculation on the optimal tilt angle, total return, and unit return corresponding to the optimal azimuth angle for each azimuth zone.

9. The method as described in claim 5, characterized in that, The step of using the gradient descent algorithm to update the inclination and azimuth angles to obtain and output the optimal inclination and azimuth angles that satisfy the preset convergence conditions includes: Set the learning rate for the gradient descent algorithm; Calculate the gradients of the tilt angle and azimuth angle; Based on the gradient and learning rate, the tilt angle and azimuth angle are updated; Determine whether the updated tilt and azimuth angles meet the preset convergence conditions; If the preset convergence condition is not met, return to the step of calculating the gradients of the total benefit and the unit benefit with respect to the tilt angle and azimuth angle; until the preset convergence condition is met, output the corresponding tilt angle and azimuth angle; If the preset convergence conditions are met, the corresponding tilt angle and azimuth angle will be output.

10. A device for determining the tilt angle and azimuth angle of a photovoltaic power station, characterized in that, include: The data acquisition module is used to acquire background data of the photovoltaic power station; The background data includes: initial range of tilt angle and initial range of azimuth angle; The reference tilt angle calculation module is used to calculate the daily total radiation corresponding to any assumed tilt angle value within the initial range of the tilt angle, and to determine the assumed tilt angle value with the largest daily total radiation as the reference tilt angle. The range setting and partitioning module is used to determine a new tilt range centered on the reference tilt angle, divide the azimuth angle into partitions and set the range of each partition. The revenue calculation module is used to perform multi-objective optimization of total revenue and unit revenue for each azimuth partition using a Monte Carlo-gradient descent hybrid algorithm, and output the optimal tilt angle and optimal azimuth angle corresponding to that azimuth partition. The optimization output module is used to calculate the optimal tilt angle and the corresponding rate of return for each azimuth partition, obtain the tilt angle and azimuth angle with the highest rate of return, and output them.

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