Photovoltaic access strategy determination method, device, equipment and storage medium

Abstract

The embodiment of the present application discloses a method, device, equipment and storage medium for determining a photovoltaic access strategy, and relates to the field of photovoltaic power generation technology. The method includes: constructing a regional digital model based on the spatial information of the area to be planned, analyzing the regional digital model to obtain the total assembly area for configuring photovoltaic equipment for the area to be planned; predicting the target photovoltaic load of the area to be planned based on the total assembly area and the power generation and electricity consumption attribute information of the area to be planned; determining the number of equipment to configure transformer equipment for the area to be planned based on the target photovoltaic load; determining the photovoltaic access strategy of the area to be planned based on the planning constraints and the number of equipment in the area to be planned. In the technical solution provided in the embodiment of the present application, the automatic determination function of the photovoltaic access strategy is realized, without relying on manual experience, avoiding the deviation that may exist by relying on experience, thereby improving the efficiency and accuracy of photovoltaic access, thereby improving the user experience.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of photovoltaic power generation technology, and in particular to a method, device, equipment and storage medium for determining a photovoltaic access strategy. Background Art

[0002] New energy represented by photovoltaics will usher in a blowout development. Rooftops are an important carrier of photovoltaic power generation. Using rooftops to build photovoltaic power generation projects does not occupy land and reduces the waste of electricity and energy, which can comprehensively improve and optimize electricity production efficiency.

[0003] The current PV access strategy is mainly determined by manual field surveys of rooftops, followed by manual calculation of the installed capacity of PV, followed by distribution and transformation planning, that is, determining the location and quantity of transformer equipment to achieve PV access.

[0004] However, relying on manual determination of photovoltaic access strategies poses risks such as falling from heights, grabbing dangerous objects and electric shock. It is also limited by the knowledge and experience of the staff, and is subjective and experience-dependent, making it difficult to adapt to a dynamically changing environment, which in turn leads to low efficiency and accuracy of photovoltaic access. Summary of the invention

[0005] The embodiments of the present application provide a method, device, equipment and storage medium for determining a photovoltaic access strategy, which realizes the photovoltaic access strategy determination function, improves the efficiency and accuracy of photovoltaic access, and solves the problem of low efficiency and accuracy of photovoltaic access in the prior art due to reliance on manual determination.

[0006] In a first aspect, an embodiment of the present application provides a method for determining a photovoltaic access strategy, the method comprising:

[0007] Building a regional digital model based on the spatial information of the area to be planned, and analyzing the regional digital model to obtain a total assembly area for configuring photovoltaic equipment in the area to be planned;

[0008] Predict the target photovoltaic load of the area to be planned based on the power generation and electricity consumption attribute information of the total assembly area and the area to be planned;

[0009] Determine the number of transformers to be configured in the planned area based on the target photovoltaic load;

[0010] The photovoltaic access strategy for the area to be planned is determined based on the planning constraints and the number of equipment in the area to be planned.

[0011] In a second aspect, an embodiment of the present application provides a device for determining a photovoltaic access strategy, the device comprising:

[0012] An analysis module is used to construct a regional digital model according to the spatial information of the area to be planned, and analyze the regional digital model to obtain a total assembly area for configuring photovoltaic equipment for the area to be planned;

[0013] A prediction module, used to predict the target photovoltaic load of the area to be planned based on the power generation and electricity consumption attribute information of the total assembly area and the area to be planned;

[0014] A quantity determination module is used to determine the number of transformers to be configured for the planned area according to the target photovoltaic load;

[0015] The strategy determination module is used to determine the photovoltaic access strategy of the area to be planned based on the planning constraints and the number of equipment in the area to be planned.

[0016] In a third aspect, an embodiment of the present application provides an electronic device, the electronic device comprising:

[0017] at least one processor; and a memory communicatively coupled to the at least one processor;

[0018] The memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor so that the at least one processor can execute the method for determining the photovoltaic access strategy of any embodiment of the present application.

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements, for example, a method for determining a photovoltaic access strategy according to any embodiment of the present application.

[0020] In the technical solution of the embodiment of the present application, a regional digital model can be constructed according to the spatial information of the area to be planned (such as geographic building data, geographic environment data, digital elevation data, etc.), and the regional digital model is analyzed to obtain the total assembly area for configuring photovoltaic equipment for the area to be planned, and then the target photovoltaic load of the area to be planned is predicted according to the total assembly area and the power generation and electricity consumption attribute information of the area to be planned, and then the number of equipment to configure transformer equipment for the area to be planned is determined according to the target photovoltaic load, and then the photovoltaic access strategy of the area to be planned is determined based on the planning constraints and the number of equipment in the area to be planned, so as to realize the automatic determination function of the photovoltaic access strategy, and automatically construct the regional digital model through spatial information, thereby avoiding the process of field investigation, measurement and calculation that requires a lot of time and manpower in the prior art, thereby reducing the risk of accidents and improving the efficiency of determining the photovoltaic access strategy; by predicting the target photovoltaic load of the area to be planned, the number of equipment can be determined more accurately, and the photovoltaic access strategy can be determined in combination with the planning constraints, thereby avoiding the deviation that may exist by relying on experience, thereby improving the accuracy of determining the photovoltaic access strategy, thereby improving the efficiency and accuracy of photovoltaic access, and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 It is a flow chart of a method for determining a photovoltaic access strategy provided in an embodiment of the present application;

[0023] Figure 2 is another flow chart of a method for determining a photovoltaic access strategy provided in an embodiment of the present application;

[0024] Figure 3 is an example diagram of an assembly sub-area provided in an embodiment of the present application;

[0025] Figure 4 is an example diagram of determining a minimum spanning tree provided in an embodiment of the present application;

[0026] Figure 5 is an example diagram of a photovoltaic access strategy provided by an embodiment of the present application;

[0027] Figure 6 It is a structural schematic diagram of a device for determining a photovoltaic access strategy provided in an embodiment of the present application;

[0028] Figure 7 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0030] It should be noted that the terms "first", "second", "target", and "original" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including", "having", and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0031] Figure 1 It is a flow chart of the method for determining the photovoltaic access strategy provided in the embodiment of the present application. The present embodiment can be applied to the situation where it is necessary to determine the photovoltaic access strategy of the area to be planned in the photovoltaic access scenario. The method for determining the photovoltaic access strategy provided in the present embodiment can be executed by the photovoltaic access strategy determination device provided in the embodiment of the present application, and the device can be implemented by software and / or hardware. In a specific embodiment, the photovoltaic access strategy determination device can be integrated in an electronic device, for example, the electronic device can be a computer, etc. The execution subject of this method can be an electronic device, see Figure 1 The method for determining the photovoltaic access strategy of this embodiment includes but is not limited to the following steps:

[0032] S110 , constructing a regional digital model according to the spatial information of the area to be planned, and analyzing the regional digital model to obtain a total assembly area for configuring photovoltaic equipment for the area to be planned.

[0033] The area to be planned is a three-dimensional space area where photovoltaic access is required to provide renewable energy power; the area to be planned can be an urban area, an industrial area, a rural area, or any other location suitable for installing photovoltaic equipment. This embodiment takes the installation of photovoltaic equipment on the roof of a house in a rural area as an example to explain the method for determining the photovoltaic access strategy of this application.

[0034] Spatial information refers to the data and information on the spatial position, attributes and their mutual relationships of objects in the area to be planned. For example, spatial information may include geographic building data, geographic environment data and digital elevation data of the area to be planned; geographic building data may include data such as the position, height and shape of buildings in the area to be planned; geographic environment data may include data such as terrain, vegetation and water system information in the area to be planned; digital elevation data may include data such as the three-dimensional coordinate information of each point in the area to be planned.

[0035] The regional digital model is a virtual representation constructed based on the spatial information of the area to be planned, integrating various spatial information of the area to be planned, and is used to simulate and display the area to be planned. Exemplarily, the regional digital model can be a three-dimensional digital model.

[0036] Photovoltaic devices are devices that use the photovoltaic effect to convert solar energy directly into electrical energy, such as photovoltaic panels.

[0037] The total assembly area is the total area suitable for installing photovoltaic equipment within the area to be planned, which is determined after comprehensive analysis and evaluation.

[0038] Specifically, when photovoltaic access is required in the area to be planned, a video image of the area to be planned that is collected in advance by a visible light camera carried by a drone can be obtained, and then the video image can be preprocessed, such as radiation correction, geometric correction, and noise removal. Image processing technology is used to extract features from each frame of the video image to extract spatial information of the area to be planned, such as geographic building data, geographic environment data, and digital elevation data of the area to be planned.

[0039] After that, a regional digital model can be constructed based on the spatial information of the area to be planned, that is, a digital elevation model (DEM) of the area to be planned can be created based on digital elevation data, and then the geographic building data and geographic environment data can be integrated into the digital elevation model to obtain a digital surface model (DSM) of the area to be planned. Then, based on the video image of the area to be planned, the digital surface model can be further optimized using texture mapping and color processing to make it closer to the real scene, thereby obtaining a regional digital model. Among them, texture mapping is to map the texture information of the actual surface (such as the material and color of the roof, etc.) to the digital surface model to increase the realism of the model; color processing is to adjust the color of the digital surface model to better reflect the color changes in the actual scene.

[0040] Afterwards, the regional digital model can be analyzed to obtain the total assembly area for configuring photovoltaic equipment for the area to be planned. For example, based on the meteorological data and solar radiation data in the regional digital model, the distribution of solar energy resources in the area to be planned can be determined to determine the area with higher solar radiation intensity and longer sunshine time; then, based on the regional digital model, the terrain and shadow analysis of the area to be planned is performed to determine the influence of parameters such as slope and slope direction on the installation of photovoltaic equipment, as well as the influence of obstacles such as buildings and trees on the lighting of photovoltaic equipment, so as to determine the area without shadow or with less shadow; then, based on the regional digital model, the current land use status and future planning of the area to be planned are analyzed to ensure that the installation of photovoltaic equipment complies with relevant laws and regulations and planning requirements, so as to determine the idle land and roof areas that can be used to install photovoltaic equipment; then, based on the above analysis results, the total assembly area suitable for installing photovoltaic equipment in the area to be planned is calculated.

[0041] S120, predicting the target photovoltaic load of the area to be planned based on the power generation and electricity consumption attribute information of the total assembly area and the area to be planned.

[0042] The power generation and electricity consumption attribute information is various data and information related to photovoltaic power generation and electricity consumption in the area to be planned. For example, the power generation and electricity consumption attribute information may include illumination information of the area to be planned, power generation characteristics of photovoltaic equipment, and electricity consumption information of the area to be planned.

[0043] The target photovoltaic load is the total installed capacity or power generation of photovoltaic equipment planned to be installed in the planned area to meet the power load demand within a certain period of time.

[0044] Specifically, after obtaining the total assembly area, the power generation and electricity consumption attribute information of the area to be planned can be obtained, such as the illumination information of the area to be planned, the power generation characteristics of the photovoltaic equipment, and the electricity consumption information of the area to be planned; then, the target photovoltaic load of the area to be planned is predicted based on the total assembly area and the power generation and electricity consumption attribute information of the area to be planned. For example, a pre-trained photovoltaic load prediction model can be obtained, and then the power generation and electricity consumption attribute information of the area to be planned is input into the photovoltaic load prediction model. After being processed by the photovoltaic load prediction model, the load amount that needs to be generated by photovoltaic equipment in the area to be planned can be predicted, that is, the output value of the photovoltaic load prediction model is determined as the target photovoltaic load of the area to be planned. Among them, the photovoltaic load prediction model is a pre-trained model used to predict the target photovoltaic load of the area to be planned; the input of the photovoltaic load prediction model is the power generation and electricity consumption attribute information, and the output is the target photovoltaic load.

[0045] S130. Determine the number of transformers to be configured for the area to be planned according to the target photovoltaic load.

[0046] The transformer is a type of electrical equipment used to change AC voltage, such as a transformer, which is mainly used to convert low-voltage DC power generated by photovoltaic equipment into high-voltage AC power for incorporation into the power grid or for use by local users. The number of equipment is the number of transformers that need to be installed in the planned area.

[0047] Specifically, after obtaining the target photovoltaic load, the number of transformer devices to be configured for the area to be planned can be determined based on the target photovoltaic load. For example, the type and specification of the appropriate transformer device can be selected based on the access voltage level of the photovoltaic device and the grid requirements, such as a dynamic combination transformer or a static transformer. Then, the product of the target photovoltaic load and the preset safety factor is calculated to obtain the total capacity required for the area to be planned, and the rated capacity of a single transformer device is determined based on the type and specification of the selected transformer device. Then, the ratio between the total capacity required for the area to be planned and the rated capacity of a single transformer device is calculated, and the ratio is rounded up to obtain the number of transformer devices to be configured for the area to be planned.

[0048] The preset safety factor is a preset value used to ensure that the transformer equipment can still provide stable power output when running at full load. The user can adjust and set the preset safety factor according to actual use requirements, and the embodiment of the present application does not specifically limit this. For example, the preset safety factor can be 1.1.

[0049] S140: Determine a photovoltaic access strategy for the area to be planned based on planning constraints and the number of devices in the area to be planned.

[0050] The planning constraints are a series of limiting factors that must be considered and met when formulating a photovoltaic access strategy. For example, the planning constraints may include constraints such as land use, environmental impact, cost, and distance.

[0051] The photovoltaic access strategy is an overall plan and specific measures formulated to achieve safe, efficient and reliable access to the power grid for photovoltaic equipment, aiming to optimize resource allocation, improve energy efficiency and promote sustainable development. Optionally, the photovoltaic access strategy may include the assembly location of the transformer equipment and the wiring path of the photovoltaic equipment; the assembly location is the specific installation location of the transformer equipment; the wiring path is the path of the power transmission line from the photovoltaic equipment to the transformer equipment.

[0052] Specifically, after obtaining the number of devices configured for the transformer equipment in the area to be planned, the photovoltaic access strategy for the area to be planned can be determined based on the planning constraints and the number of equipment in the area to be planned, that is, the assembly position of the transformer equipment in the area to be planned can be determined based on the planning constraints and the number of equipment in the area to be planned, and the wiring path of the photovoltaic equipment can be determined based on the assembly position of the transformer equipment.

[0053] Specifically, the planning constraints pre-set for the area to be planned can be obtained, such as land use, environmental impact, cost, distance and other constraints, and then the assembly location of the transformer equipment can be preliminarily screened based on the planning constraints. Based on the preliminary screening, the optimal assembly location of the transformer equipment can be determined through an optimization algorithm to ensure the efficiency and safety of power transmission.

[0054] Afterwards, the wiring path can be preliminarily planned based on the assembly location of the transformer equipment and the location of the photovoltaic equipment. Then, the wiring path can be optimized considering the impact of factors such as topography, obstacles and underground pipelines on the wiring path, reducing line length and loss to ensure that the wiring path meets the requirements of safety, reliability and economy, thereby obtaining the photovoltaic access strategy for the area to be planned.

[0055] The technical solution of the embodiment of the present application can construct a regional digital model according to the spatial information of the area to be planned (such as geographic building data, geographic environment data, digital elevation data, etc.), and analyze the regional digital model to obtain the total assembly area for configuring photovoltaic equipment for the area to be planned, then predict the target photovoltaic load of the area to be planned according to the total assembly area and the power generation and electricity consumption attribute information of the area to be planned, and then determine the number of equipment to configure transformer equipment for the area to be planned according to the target photovoltaic load, and then determine the photovoltaic access strategy of the area to be planned based on the planning constraints and the number of equipment in the area to be planned, thereby realizing the automatic determination function of the photovoltaic access strategy, automatically constructing the regional digital model through spatial information, avoiding the process of field investigation, measurement and calculation that requires a lot of time and manpower in the prior art, thereby reducing the risk of accidents and improving the efficiency of determining the photovoltaic access strategy; by predicting the target photovoltaic load of the area to be planned, the number of equipment can be determined more accurately, and the photovoltaic access strategy can be determined in combination with the planning constraints, avoiding the deviation that may exist based on experience, thereby improving the accuracy of determining the photovoltaic access strategy, thereby improving the efficiency and accuracy of photovoltaic access, and improving the user experience.

[0056] The following further describes a method for determining a photovoltaic access strategy provided by an embodiment of the present application. Figure 2 is another flow chart of the method for determining the photovoltaic access strategy provided by the embodiment of the present application. The embodiment of the present application is optimized based on the above embodiments. Figure 2 The method of this embodiment includes but is not limited to the following steps:

[0057] S201. Construct a regional digital model according to the spatial information of the area to be planned.

[0058] S202: Perform image recognition on the regional digital model to obtain a plurality of initial assembly sub-regions for installing photovoltaic equipment.

[0059] The initial assembly sub-area is an area that is initially divided by image recognition technology and may be suitable for installing photovoltaic equipment; the initial assembly sub-area may contain some noise or inaccurate parts, which need to be further corrected. For example, the initial assembly sub-area may be a roof area.

[0060] Specifically, after constructing the regional digital model, the images in the regional digital model can be preprocessed, such as denoising and contrast enhancement, to improve image quality; then, semantic segmentation technology can be used to perform image recognition on the images in the regional digital model to identify potential areas suitable for installing photovoltaic equipment, namely, multiple initial assembly sub-areas, which should meet conditions such as sufficient light and no obstruction.

[0061] S203: Correct the contours of the multiple initial assembly sub-regions to obtain multiple assembly sub-regions.

[0062] The assembly sub-area is obtained after contour correction and can accurately represent the vector polygon suitable for installing photovoltaic equipment.

[0063] Specifically, after obtaining multiple initial assembly sub-regions, contour tracking algorithms (such as edge detection and contour tracking, etc.) can be used to extract the contour of each of the multiple initial assembly sub-regions, and based on the contour of each initial assembly sub-region, each initial assembly sub-region can be displayed in the regional digital model; then, the contours of the multiple initial assembly sub-regions can be corrected. For example, the staff can use a two-dimensional annotation tool to manually correct the contour of each of the multiple initial assembly sub-regions to remove unnecessary details and noise, so that the contour of each initial assembly sub-region is smoother and more accurate, thereby obtaining multiple assembly sub-regions.

[0064] Among them, the two-dimensional annotation tool has a built-in auxiliary error correction function based on a linear detection algorithm. Compared with the traditional two-dimensional map marking method, this two-dimensional annotation tool has a higher edge marking efficiency of building roof blocks, and supports the simultaneous display of more than 10,000 rooftop photovoltaic annotations.

[0065] For example, when the initial assembly sub-area is a roof area, semantic segmentation technology can be used to perform image recognition on images in the regional digital model to identify roof areas suitable for installing photovoltaic equipment, and then extract the contours of these roof areas and display them in the regional digital model; then the staff uses two-dimensional annotation tools to manually correct the contours of these roof areas to make the contours of each roof area smoother and more accurate.

[0066] S204, performing vector measurement on the area of ​​multiple assembly sub-areas to obtain a total assembly area.

[0067] Specifically, after obtaining multiple assembly sub-areas, vector measurement can be performed on the area of ​​the multiple assembly sub-areas, that is, Geographic Information System (GIS) software or other vector processing tools can be used to construct a vector polygon for each assembly sub-area, and the area of ​​the vector polygon of each assembly sub-area is calculated separately to obtain the area of ​​each assembly sub-area, and then the sum of the areas of each assembly sub-area is calculated to obtain the total assembly area.

[0068] Optionally, the area of ​​each assembly sub-region can be displayed in the regional digital model. Figure 3 The figure shows an example diagram of an assembly sub-area provided in an embodiment of the present application. Figure 3 The red area in is the assembly sub-area, i.e. Figure 3 Two assembly sub-regions are shown in FIG, and the area of ​​each assembly sub-region is shown.

[0069] Optionally, the power generation and electricity consumption attribute information may include power generation attribute information and electricity consumption attribute information; the power generation attribute information may include geographical environment information such as historical sunshine duration and historical solar radiation of the planned area, and performance parameters such as rated power and power generation efficiency of photovoltaic equipment; the electricity consumption attribute information may include historical electricity load, historical climate data, historical population size, historical population ratio and historical age distribution, and other factors that affect the electricity load.

[0070] S205 , determining a photovoltaic power generation load curve of the area to be planned according to the power generation attribute information of the total assembly area and the area to be planned.

[0071] Among them, the photovoltaic power generation load curve is used to characterize the changes in the power generation load of photovoltaic equipment in the planned area over a specific time period (such as day, month and year, etc.); the vertical axis of the photovoltaic power generation load curve represents the photovoltaic power generation load, and the horizontal axis represents the corresponding time, reflecting the changes in the power generation capacity of the photovoltaic equipment.

[0072] Specifically, after obtaining the total assembly area, the power generation attribute information of the area to be planned can be obtained, such as the geographical environment information of the area to be planned (such as historical sunshine duration and historical solar radiation, etc.), and the performance parameters of the photovoltaic equipment (such as rated power and power generation efficiency, etc.), where the performance parameters of the photovoltaic equipment can be determined according to the type and specifications of the photovoltaic equipment; then, based on the total assembly area, the geographical environment information of the area to be planned and the performance parameters of the photovoltaic equipment, and taking into account the daily and seasonal changes of factors such as light intensity and temperature, a model of the change of photovoltaic power generation load over time can be established, and then the model is used to calculate the photovoltaic power generation load of the photovoltaic equipment in the area to be planned in different time periods, and the calculated photovoltaic power generation load is plotted into a curve in chronological order to obtain the photovoltaic power generation load curve of the area to be planned. At this time, the photovoltaic power generation load curve can be the photovoltaic power generation load of the photovoltaic equipment in the area to be planned in the next year.

[0073] S206: predicting a power load prediction curve of the area to be planned based on the power consumption attribute information of the area to be planned.

[0074] Among them, the electricity load forecast curve is used to characterize the change of electricity load over time in the area to be planned in a specific time period (such as day, month and year, etc.); the ordinate of the electricity load forecast curve represents the electricity load, and the abscissa represents the corresponding time, reflecting the change of electricity demand in the area to be planned in a specific time period.

[0075] Specifically, after obtaining the photovoltaic power generation load curve of the area to be planned, the electricity consumption attribute information of the area to be planned can be obtained, such as the historical electricity load, historical climate data, historical population size, historical population ratio and historical age distribution data of the area to be planned in the past year; then a pre-trained electricity load prediction model can be obtained, and the electricity consumption attribute information of the area to be planned can be input into the electricity load prediction model. After being processed by the electricity load prediction model, the electricity load of the area to be planned in different time periods in the next year can be predicted, and then the predicted electricity load can be plotted into a curve in chronological order to obtain the electricity load prediction curve of the area to be planned.

[0076] Optionally, the training process of the power load forecasting model can be: the power attribute information of the area to be planned can be used as training sample data, and the power attribute information at this time can be the power attribute information of the area to be planned in the past few years, and then the training sample data is used as a training data set to input the initial power load forecasting model, and the training output of the initial power load forecasting model is guided by the historical power load, and the initial power load forecasting model is trained to obtain the power load forecasting model. Exemplarily, the initial power load forecasting model can be a long short-term memory network (Long Short-Term Memory, LSTM).

[0077] S207: Process the photovoltaic power generation load curve and the power load forecast curve to obtain a target photovoltaic load.

[0078] Specifically, after obtaining the photovoltaic power generation load curve and the electricity load forecast curve, data processing can be performed on the photovoltaic power generation load curve and the electricity load forecast curve. For example, the minimum value of the photovoltaic power generation load in the photovoltaic power generation load curve can be determined, and the maximum value of the electricity load in the electricity load forecast curve can be determined. Then, the minimum value of the photovoltaic power generation load is compared with the maximum value of the electricity load to determine the smaller value of the two, and the smaller value is determined as the target photovoltaic load.

[0079] S208. Determine the load density according to the target photovoltaic load and the total installation area.

[0080] Among them, load density is a quantitative parameter that characterizes the density of load distribution and is used to describe the concentration of electricity demand in the area to be planned.

[0081] Specifically, after the target photovoltaic load is obtained, the load density can be determined according to the target photovoltaic load and the total installation area, that is, the ratio between the target photovoltaic load and the total installation area can be calculated to obtain the load density of the area to be planned.

[0082] S209. Calculate the number of devices according to the preset capacity-load ratio and load density.

[0083] Among them, the preset capacity-load ratio is a pre-set value used to reflect the capacity reserve situation of the power grid to ensure the safe and stable operation of the power grid during peak load periods. Users can adjust and set the preset capacity-load ratio according to actual usage needs, and the embodiments of the present application do not make specific limitations on this.

[0084] Specifically, after the load density is obtained, the number of transformer equipment can be calculated according to the preset capacity-load ratio and the load density, which is recorded as N. That is, the calculation formula for the number of equipment N is:

[0085]

[0086]

[0087]

[0088] in, Indicates load density; Indicates the preset capacity ratio; It represents the input-output ratio under unit load; It represents the cost-effectiveness coefficient under unit load; It represents the part of the investment that is not related to the substation capacity; It indicates the ratio coefficient of operating cost to investment; Indicates the effective year of investment; represents the terrain correction factor; The coefficient that represents the part of the investment that is not related to the cross-sectional area of ​​the conductor; Indicates the average power factor of the line; Indicates the average load of each circuit; The coefficient that represents the linear relationship between the investment and the cross-sectional area of ​​the conductor; Indicates the rated voltage of the distribution network; Indicates the economic current density of the conductor; Indicates resistivity, unit Ω / (km·mm 2 ); Indicates the maximum load loss time in hours; Indicates the unit price of lost electric energy; represents pi. It should be noted that the calculation and The required data are known data.

[0089] S210, clustering multiple assembly sub-areas in the total assembly area to obtain multiple photovoltaic distribution centers equal to the number of equipment.

[0090] The photovoltaic distribution center is obtained by clustering multiple assembly sub-areas; each photovoltaic distribution center includes at least one assembly sub-area, and the number of photovoltaic distribution centers is equal to the number of transformer equipment.

[0091] Specifically, after obtaining the number of equipment, the number of photovoltaic distribution centers can be determined based on the number of transformer equipment, that is, the number of photovoltaic distribution centers is equal to the number of transformer equipment, and then based on the number of photovoltaic distribution centers, a clustering algorithm (such as k-means clustering algorithm or hierarchical clustering, etc.) is used to cluster multiple assembly sub-areas in the total assembly area, and the assembly sub-areas with a relatively close distance are divided into a photovoltaic distribution center, so as to obtain multiple photovoltaic distribution centers equal to the number of equipment.

[0092] S211 . For each of the plurality of photovoltaic distribution centers, determine an assembly position of a transformer device from at least one assembly sub-area included in each photovoltaic distribution center based on planning constraints.

[0093] Specifically, after obtaining multiple photovoltaic distribution centers, any photovoltaic distribution center can be selected as the current photovoltaic distribution center, and based on the planning constraints, the most suitable assembly sub-area for installing the transformer equipment is determined from at least one assembly sub-area contained in the current photovoltaic distribution center, and the assembly sub-area is determined as the assembly position of the transformer equipment. At this time, the assembly position should be able to maximize the use of solar energy resources while reducing the loss and cost during power transmission; after that, other photovoltaic distribution centers can be selected as the current photovoltaic distribution center, and the above process is repeated to obtain the assembly position of the transformer equipment corresponding to each photovoltaic distribution center. It should be noted that one transformer equipment can be installed in one photovoltaic distribution center.

[0094] Furthermore, based on the planning constraints, the installation location of the transformer equipment is determined from at least one installation sub-area contained in each photovoltaic distribution center, including Sa1-Sa3:

[0095] Sa1. Create an undirected graph for at least one assembly sub-area.

[0096] The vertex of the undirected graph is at least one assembly sub-region, and the edge of the undirected graph is a connection line between adjacent assembly sub-regions in at least one assembly sub-region.

[0097] Specifically, an undirected graph may be created based on at least one assembly sub-region included in the current photovoltaic distribution center, that is, each assembly sub-region is defined as a vertex, and the connection between adjacent assembly sub-regions in at least one assembly sub-region is defined as an edge, thereby creating an undirected graph.

[0098] Sa2. Determine the weight corresponding to each edge in the undirected graph.

[0099] Specifically, after obtaining the undirected graph, the weight corresponding to each edge in the undirected graph can be determined. For example, the weight corresponding to each edge can be determined based on the distance between adjacent assembly sub-areas or other cost factors (for example, if the terrain between two assembly sub-areas is complex, the weight corresponding to the edge between them is higher).

[0100] Exemplarily, if the photovoltaic distribution center 1 includes assembly sub-area 1, assembly sub-area 2, assembly sub-area 3, assembly sub-area 4, assembly sub-area 5 and assembly sub-area 6, then the undirected graph corresponding to the photovoltaic distribution center 1 is Figure 4 In Figure a shown, the number next to each edge is the weight corresponding to each edge.

[0101] Sa3. Determine the optimal vertex of the undirected graph according to the planning constraints and the weight corresponding to each edge, and determine the assembly sub-area corresponding to the optimal vertex as the assembly position.

[0102] Among them, the optimal vertex is the vertex in the undirected graph that is most suitable for installing the transformer equipment.

[0103] Specifically, after determining the weight corresponding to each edge in the undirected graph, the optimal vertex can be determined from multiple vertices of the undirected graph using a graph theory algorithm based on the planning constraints and the weight corresponding to each edge.

[0104] Furthermore, the optimal vertices of the undirected graph are determined according to the planning constraints and the weights corresponding to each edge, including Sb1-Sb2:

[0105] Sb1. Determine the minimum spanning tree of the undirected graph based on the weight corresponding to each edge.

[0106] Specifically, the Prim algorithm can be used to process the undirected graph based on the weight corresponding to each edge to determine the minimum spanning tree of the undirected graph. That is, starting from any vertex, select the edge connecting the vertex with the smallest weight, and then update the set of vertices connected to the edge. Repeat this process until all vertices are included. After the execution is completed, a tree containing all vertices and with the smallest sum of edge weights can be obtained, which is the minimum spanning tree.

[0107] For example, Figure 4 As shown, Figure a is the undirected graph corresponding to the photovoltaic distribution center 1, Figure f is the minimum spanning tree corresponding to the photovoltaic distribution center 1, and Figures b, c, d, e and f are the process of determining the minimum spanning tree.

[0108] Sb2. Based on the minimum spanning tree, the vertex that meets the planning constraints is determined as the optimal vertex.

[0109] Optionally, planning constraints may include minimum cost and shortest distance.

[0110] Specifically, after obtaining the minimum spanning tree, the vertex that meets the planning constraints can be determined as the optimal vertex, that is, any vertex can be selected from multiple vertices of the minimum spanning tree as the current vertex, and the current vertex can be used as the starting point. Then, based on the minimum spanning tree, the length of the shortest path from the current vertex to each of the other vertices (that is, the sum of the weights) is calculated, and the sum of the lengths of these shortest paths is calculated to obtain the total path length corresponding to the current vertex. After that, other vertices can be selected as the current vertex, and the above process can be repeated to obtain the total path length corresponding to each vertex.

[0111] Afterwards, the total path lengths corresponding to each vertex can be compared, the minimum value of the total path length can be selected, and the vertex corresponding to the minimum value can be determined as the optimal vertex. Afterwards, the assembly sub-area corresponding to the optimal vertex can be determined as the assembly position of the transformer device.

[0112] In the embodiment of the present application, the accuracy of the optimal vertex can be ensured through the minimum spanning tree and planning constraints, thereby minimizing the photovoltaic access cost; and the process of determining the assembly position is simplified, thereby improving the efficiency of determining the assembly position, and providing a basis for determining the subsequent wiring path.

[0113] For example, Figure 4 As shown, Figure f is the minimum spanning tree of the photovoltaic distribution center 1. The process of determining the assembly position can be as follows: the assembly sub-area 1 can be selected as the starting point, and the length of the shortest path from the assembly sub-area 1 to the assembly sub-area 3 is calculated to be 1, the length of the shortest path from the assembly sub-area 1 to the assembly sub-area 2 is 6 (i.e., 1+5), the length of the shortest path from the assembly sub-area 1 to the assembly sub-area 5 is 9 (i.e., 1+5+3), the length of the shortest path from the assembly sub-area 1 to the assembly sub-area 6 is 5 (i.e., 1+4), and the length of the shortest path from the assembly sub-area 1 to the assembly sub-area 4 is 7 (i.e., 1+4+2). Then, the sum of the lengths of these shortest paths is calculated, and the total path length of the assembly sub-area 1 is 28 (i.e., 1+6+9+5+ 7); then other assembly sub-areas can be selected as starting points, and the calculation process of the total path length of assembly sub-area 1 can be repeated, and the total path length of assembly sub-area 2 is 34 (i.e. 5+6+3+9+11), the total path length of assembly sub-area 3 is 24 (i.e. 1+5+8+4+6), the total path length of assembly sub-area 4 is 40 (i.e. 2+6+7+11+14), the total path length of assembly sub-area 5 is 46 (i.e. 3+8+9+12+14), and the total path length of assembly sub-area 6 is 32 (i.e. 2+4+5+9+12). At this time, assembly sub-area 3 can be determined as the optimal vertex, that is, assembly sub-area 3 is determined as the assembly position of the substation equipment corresponding to the photovoltaic distribution center 1.

[0114] In the embodiment of the present application, the spatial positions and mutual connections between the various assembly sub-areas can be intuitively displayed in the form of an undirected graph; by comprehensively considering the weights and planning constraints corresponding to each edge, the optimal assembly position can be accurately located, thereby ensuring the power generation efficiency and operational stability of the photovoltaic equipment, thereby improving the accuracy of determining the photovoltaic access strategy.

[0115] S212: Based on the assembly position of the transformer device, the photovoltaic devices in at least one assembly sub-area are wired to obtain a wiring path for each photovoltaic distribution center.

[0116] Specifically, after obtaining the assembly position of the transformer equipment corresponding to each photovoltaic distribution center, any photovoltaic distribution center can be selected as the current photovoltaic distribution center, and the assembly position of the transformer equipment corresponding to the current photovoltaic distribution center can be obtained. Then, the shortest path of the vertices corresponding to the assembly position is determined as the wiring path of the current photovoltaic distribution center, that is, according to the shortest path of the vertices corresponding to the assembly position, the photovoltaic equipment in at least one assembly sub-area included in the current photovoltaic distribution center is wired; thereafter, other photovoltaic distribution centers can be selected as the current photovoltaic distribution center, and the above process can be repeated to obtain the wiring path of each photovoltaic distribution center.

[0117] For example, Figure 4 As shown, Figure f is the minimum spanning tree of the photovoltaic distribution center 1. The optimal vertex in Figure f is the assembly sub-area 3, that is, the assembly position of the transformer equipment corresponding to the photovoltaic distribution center 1 is the assembly sub-area 3. At this time, the shortest path corresponding to the assembly sub-area 3 can be determined as the wiring path of the photovoltaic distribution center 1.

[0118] S213. Determine a photovoltaic access strategy according to the assembly position and wiring path.

[0119] Specifically, after obtaining the assembly position of the transformer equipment and the wiring path of the photovoltaic equipment, the assembly position of the transformer equipment and the wiring path of the photovoltaic equipment can be determined as the photovoltaic access strategy of the area to be planned, and the photovoltaic access strategy can be displayed in the regional digital model.

[0120] Optionally, information such as the longitude and latitude of the assembly locations of the towers and transformer equipment in the area to be planned, wiring paths, and load rates of the transformer equipment can be imported into the regional digital model to display the photovoltaic access strategy of the area to be planned in the regional digital model, thereby assisting staff in visual intelligent planning.

[0121] For example, Figure 5 The figure shows an example of a photovoltaic access strategy provided by an embodiment of the present application. Figure 5 The assembly location of the transformer equipment and the wiring path of the photovoltaic equipment are shown in the figure. Figure 5The photovoltaic distribution center 1 corresponding to the transformer device 1 includes three transformer devices, namely, transformer device 1, transformer device 2 and transformer device 3, wherein the photovoltaic distribution center 1 corresponding to the transformer device 1 includes three assembly sub-areas, namely, assembly sub-area 1, assembly sub-area 2 and assembly sub-area 3, and each assembly sub-area is installed with a photovoltaic device, and the connection between the assembly sub-area 1, the assembly sub-area 2, the assembly sub-area 3 and the transformer device 1 is the wiring path of the photovoltaic device in the photovoltaic distribution center 1; the photovoltaic distribution center 2 corresponding to the transformer device 2 includes four assembly sub-areas, namely, assembly sub-areas 4, Assembly sub-area 5, assembly sub-area 6 and assembly sub-area 7, and the connection between assembly sub-area 4, assembly sub-area 5, assembly sub-area 6, assembly sub-area 7 and transformer equipment 2 is the wiring path of the photovoltaic equipment in the photovoltaic distribution center 2; the photovoltaic distribution center 3 corresponding to the transformer equipment 3 includes 3 assembly sub-areas, namely, assembly sub-area 8, assembly sub-area 9 and assembly sub-area 10, and the connection between assembly sub-area 8, assembly sub-area 9, assembly sub-area 10 and transformer equipment 3 is the wiring path of the photovoltaic equipment in the photovoltaic distribution center 3.

[0122] The technical solution of the embodiment of the present application can construct a regional digital model according to the spatial information of the area to be planned, and perform image recognition on the regional digital model to obtain multiple initial assembly sub-areas for installing photovoltaic equipment, then correct the contours of the multiple initial assembly sub-areas to obtain multiple assembly sub-areas, and perform vector measurement on the regional areas of the multiple assembly sub-areas to obtain the total assembly area, thereby realizing the function of determining the total assembly area. By using image recognition technology, the area suitable for installing photovoltaic equipment can be accurately identified, thereby avoiding misjudgment or omission that may occur in traditional planning, and ensuring the accuracy and reliability of the assembly sub-areas through contour correction and vector measurement, thereby improving the accuracy and reliability of determining the total assembly area. The efficiency is determined, which provides data support for the subsequent determination of the number of equipment; after that, the photovoltaic power generation load curve of the area to be planned can be determined according to the power generation attribute information of the total assembly area and the area to be planned, and the power load prediction curve of the area to be planned can be predicted according to the power consumption attribute information of the area to be planned, and then the photovoltaic power generation load curve and the power load prediction curve are processed to obtain the target photovoltaic load, thus realizing the function of determining the target photovoltaic load. By accurately predicting the photovoltaic power generation load curve and the power load prediction curve, it can be ensured that the photovoltaic equipment can meet the power demand during the peak power consumption period, avoid the occurrence of power shortage, improve the matching degree of power supply and demand, and thus improve the accuracy of determining the photovoltaic access strategy.

[0123] Afterwards, the load density can be determined according to the target photovoltaic load and the total assembly area, and the number of devices can be calculated according to the preset capacity-load ratio and load density, thus realizing the function of determining the number of devices. By determining the load density, the distribution of power demand in the area to be planned can be clarified, providing a scientific basis for determining the subsequent photovoltaic access strategy; by setting the preset capacity-load ratio, the capacity reserve of the power grid is taken into account, which helps to maintain the stable operation of the power grid during peak power consumption, thereby improving the accuracy of determining the number of devices, thereby improving the accuracy of photovoltaic access; afterward, multiple assembly sub-areas in the total assembly area can be clustered to obtain multiple photovoltaic distribution centers equal to the number of devices, and then for each photovoltaic distribution center in the multiple photovoltaic distribution centers, based on the planning constraints, a total of 10 photovoltaic distribution centers are selected from each photovoltaic distribution center. The assembly position of the transformer equipment is determined in at least one assembly sub-area contained in a photovoltaic distribution center, and then the photovoltaic equipment in at least one assembly sub-area is wired based on the assembly position of the transformer equipment to obtain a wiring path for each photovoltaic distribution center. Then, the photovoltaic access strategy is determined according to the assembly position and the wiring path, and the photovoltaic access strategy determination function is realized. The photovoltaic distribution center is formed by clustering, and the assembly position of the transformer equipment and the wiring path of the photovoltaic equipment are determined based on the photovoltaic distribution center, which improves the determination accuracy and efficiency of the assembly position and the wiring path, thereby improving the determination accuracy and efficiency of the photovoltaic access strategy, reducing the photovoltaic access cost, and improving the economic benefits, thereby providing a strong guarantee for the sustainable development of renewable energy.

[0124] Figure 6 is a schematic diagram of a photovoltaic access strategy determination device provided in an embodiment of the present application, referring to Figure 6 , the photovoltaic access strategy determination device may include:

[0125] An analysis module 610 is used to construct a regional digital model according to the spatial information of the area to be planned, and analyze the regional digital model to obtain a total assembly area for configuring photovoltaic equipment for the area to be planned;

[0126] Prediction module 620, used to predict the target photovoltaic load of the area to be planned according to the power generation and power consumption attribute information of the total assembly area and the area to be planned;

[0127] A quantity determination module 630 is used to determine the number of transformers to be configured for the planned area according to the target photovoltaic load;

[0128] The strategy determination module 640 is used to determine the photovoltaic access strategy of the area to be planned based on the planning constraints and the number of equipment in the area to be planned.

[0129] In one embodiment, the photovoltaic access strategy includes the assembly position of the transformer equipment and the wiring path of the photovoltaic equipment. The strategy determination module 640 is specifically used to: cluster multiple assembly sub-areas in the total assembly area to obtain multiple photovoltaic distribution centers equal to the number of equipment, each photovoltaic distribution center includes at least one assembly sub-area; for each photovoltaic distribution center in the multiple photovoltaic distribution centers, determine the assembly position of the transformer equipment from at least one assembly sub-area contained in each photovoltaic distribution center based on planning constraints; based on the assembly position of the transformer equipment, wire the photovoltaic equipment in at least one assembly sub-area to obtain the wiring path of each photovoltaic distribution center; determine the photovoltaic access strategy according to the assembly position and the wiring path.

[0130] In one embodiment, the strategy determination module 640 determines the assembly position of the transformer equipment from at least one assembly sub-area contained in each photovoltaic distribution center based on the planning constraints, including: creating an undirected graph for at least one assembly sub-area, the vertices of the undirected graph are at least one assembly sub-area, and the edges of the undirected graph are the lines between adjacent assembly sub-areas in at least one assembly sub-area; determining the weight corresponding to each edge in the undirected graph; determining the optimal vertex of the undirected graph according to the planning constraints and the weight corresponding to each edge, and determining the assembly sub-area corresponding to the optimal vertex as the assembly position.

[0131] In one embodiment, the strategy determination module 640 determines the optimal vertex of the undirected graph according to the planning constraints and the weight corresponding to each edge, including: determining the minimum spanning tree of the undirected graph according to the weight corresponding to each edge; based on the minimum spanning tree, determining the vertex that meets the planning constraints as the optimal vertex.

[0132] In one embodiment, the analysis module 610 analyzes the regional digital model to obtain the total assembly area for configuring the photovoltaic equipment for the area to be planned, including: performing image recognition on the regional digital model to obtain multiple initial assembly sub-areas for installing photovoltaic equipment; correcting the contours of the multiple initial assembly sub-areas to obtain multiple assembly sub-areas; performing vector measurement on the area of ​​the multiple assembly sub-areas to obtain the total assembly area.

[0133] In one embodiment, the power generation and electricity consumption attribute information includes power generation attribute information and electricity consumption attribute information, and the prediction module 620 is specifically used to: determine the photovoltaic power generation load curve of the area to be planned based on the power generation attribute information of the total assembly area and the area to be planned; predict the electricity consumption load prediction curve of the area to be planned based on the electricity consumption attribute information of the area to be planned; and perform data processing on the photovoltaic power generation load curve and the electricity consumption load prediction curve to obtain the target photovoltaic load.

[0134] In one embodiment, the quantity determination module 630 is specifically used to: determine the load density according to the target photovoltaic load and the total installation area; and calculate the number of devices according to the preset capacity-load ratio and the load density.

[0135] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the functional modules described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0136] The photovoltaic access strategy determination device provided in this embodiment can be applied to the photovoltaic access strategy determination method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0137] Figure 7 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application. Figure 7 A block diagram of an exemplary electronic device 11 suitable for implementing the embodiments of the present application is shown. Figure 7 The electronic device 11 shown is only an example and should not bring any limitation to the function and scope of use of the present embodiment.

[0138] like Figure 7 As shown, the electronic device 11 is in the form of a general purpose computing electronic device. The components of the electronic device 11 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 connecting different system components (including the system memory 28 and the processing unit 16).

[0139] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures. By way of example, these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0140] The electronic device 11 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 11, including volatile and non-volatile media, removable and non-removable media.

[0141] The system memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The electronic device 11 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be used to read and write non-removable, non-volatile magnetic media ( Figure 7 not shown, usually called a "hard drive"). Although Figure 7 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 18 via one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of the various embodiments of the present application.

[0142] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 42 generally perform the functions and / or methods of the embodiments described herein.

[0143] The electronic device 11 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 11, and / or any device that enables the electronic device 11 to communicate with one or more other computing devices (e.g., network card, modem, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the electronic device 11 may also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN) and / or public network, such as the Internet) through a network adapter 20.

[0144] like Figure 7 As shown, the network adapter 20 communicates with other modules of the electronic device 11 via the bus 18. It should be understood that although Figure 7 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 11, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0145] The processing unit 16 executes various functional applications and page displays by running the programs stored in the system memory 28, for example, implementing a method for determining a photovoltaic access strategy provided in any embodiment of the present application.

[0146] An embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a method for determining a photovoltaic access strategy, for example, provided in any embodiment of the present application, is implemented.

[0147] It should be understood by those skilled in the art that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, optionally, they can be implemented by a program code executable by a computer device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0148] In addition, the acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0149] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the inventive concept of the present application, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for determining a photovoltaic access strategy, characterized in that: The method comprises: Constructing a regional digital model according to the spatial information of the area to be planned, and analyzing the regional digital model to obtain a total assembly area for configuring photovoltaic equipment for the area to be planned; Predicting the target photovoltaic load of the area to be planned according to the power generation and electricity consumption attribute information of the total assembly area and the area to be planned; Determine the number of transformers to be configured for the area to be planned according to the target photovoltaic load; Determining a photovoltaic access strategy for the area to be planned based on the planning constraints of the area to be planned and the number of devices; Among them, the photovoltaic access strategy includes the assembly position of the transformer equipment and the wiring path of the photovoltaic equipment, and the photovoltaic access strategy of the area to be planned is determined based on the planning constraints of the area to be planned and the number of equipment, including: clustering multiple assembly sub-areas in the total assembly area to obtain multiple photovoltaic distribution centers equal to the number of equipment, each photovoltaic distribution center includes at least one assembly sub-area; for each photovoltaic distribution center in the multiple photovoltaic distribution centers, based on the planning constraints, determining the assembly position of the transformer equipment from at least one assembly sub-area contained in each photovoltaic distribution center; based on the assembly position of the transformer equipment, wiring the photovoltaic equipment in the at least one assembly sub-area to obtain the wiring path of each photovoltaic distribution center; determining the photovoltaic access strategy according to the assembly position and the wiring path.

2. The method for determining a photovoltaic access strategy according to claim 1, characterized in that: The step of determining the installation position of the transformer device from at least one installation sub-area contained in each photovoltaic distribution center based on the planning constraint condition includes: Creating an undirected graph for the at least one assembly sub-region, wherein the vertices of the undirected graph are the at least one assembly sub-region, and the edges of the undirected graph are the connecting lines between adjacent assembly sub-regions in the at least one assembly sub-region; Determine the weight corresponding to each edge in the undirected graph; The optimal vertex of the undirected graph is determined according to the planning constraint condition and the weight corresponding to each edge, and the assembly sub-area corresponding to the optimal vertex is determined as the assembly position.

3. The method for determining a photovoltaic access strategy according to claim 2, characterized in that: The determining the optimal vertex of the undirected graph according to the planning constraint and the weight corresponding to each edge includes: Determine a minimum spanning tree of the undirected graph according to the weight corresponding to each edge; Based on the minimum spanning tree, a vertex that satisfies the planning constraint condition is determined as the optimal vertex.

4. The method for determining a photovoltaic access strategy according to claim 1, characterized in that: The step of analyzing the regional digital model to obtain a total assembly area for configuring photovoltaic equipment for the area to be planned includes: Performing image recognition on the regional digital model to obtain a plurality of initial assembly sub-regions for installing the photovoltaic device; Modifying the contours of the multiple initial assembly sub-regions to obtain multiple assembly sub-regions; Vector measurement is performed on the area of ​​the multiple assembly sub-areas to obtain the total assembly area.

5. The method for determining a photovoltaic access strategy according to claim 1, characterized in that: The power generation and electricity consumption attribute information includes power generation attribute information and electricity consumption attribute information, and the target photovoltaic load of the area to be planned is predicted according to the power generation and electricity consumption attribute information of the total assembly area and the area to be planned, including: Determine the photovoltaic power generation load curve of the area to be planned according to the total assembly area and the power generation attribute information of the area to be planned; Predicting a power load prediction curve of the area to be planned according to the power consumption attribute information of the area to be planned; The target photovoltaic load is obtained by performing data processing on the photovoltaic power generation load curve and the power load forecast curve.

6. The method for determining a photovoltaic access strategy according to claim 1, characterized in that: The step of determining the number of transformers to be configured for the area to be planned according to the target photovoltaic load includes: Determining a load density according to the target photovoltaic load and the total installation area; The number of the devices is calculated according to the preset capacity-load ratio and the load density.

7. A device for determining a photovoltaic access strategy, characterized in that: The device comprises: An analysis module, used for constructing a regional digital model according to the spatial information of the area to be planned, and analyzing the regional digital model to obtain a total assembly area for configuring photovoltaic equipment for the area to be planned; A prediction module, used for predicting the target photovoltaic load of the area to be planned according to the power generation and power consumption attribute information of the total assembly area and the area to be planned; A quantity determination module, used to determine the number of transformers to be configured for the area to be planned according to the target photovoltaic load; A strategy determination module, used to determine the photovoltaic access strategy of the area to be planned based on the planning constraints of the area to be planned and the number of devices; Among them, the photovoltaic access strategy includes the assembly position of the transformer equipment and the wiring path of the photovoltaic equipment, and the strategy determination module is specifically used to: cluster multiple assembly sub-areas in the total assembly area to obtain multiple photovoltaic distribution centers equal to the number of the equipment, each photovoltaic distribution center includes at least one assembly sub-area; for each photovoltaic distribution center in the multiple photovoltaic distribution centers, determine the assembly position of the transformer equipment from at least one assembly sub-area contained in each photovoltaic distribution center based on the planning constraints; based on the assembly position of the transformer equipment, wire the photovoltaic equipment in the at least one assembly sub-area to obtain the wiring path of each photovoltaic distribution center; determine the photovoltaic access strategy according to the assembly position and the wiring path.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for determining a photovoltaic access strategy as described in any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for determining a photovoltaic access strategy described in any one of claims 1 to 6 is implemented.

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