Photovoltaic capacity ratio evaluation method and device, storage medium and electronic device

Abstract

The invention discloses a photovoltaic capacity ratio evaluation method and device, a storage medium and an electronic device, and the method comprises the steps: obtaining photovoltaic information of a target region where a photovoltaic power station is located, the photovoltaic information comprises solar energy resource parameters of the target area, configuration information of photovoltaic modules set in the target area, capacity ratio change information of the target area and power limiting data; according to the photovoltaic information and a preset photovoltaic project cost database, calculating the construction cost corresponding to the photovoltaic power station under different capacity ratios, and according to the photovoltaic information, calculating the system efficiency of the photovoltaic power station under different capacity ratios; inputting the construction cost, the system efficiency and the power limiting data into the trained cost per kilowatt-hour model to obtain cost per kilowatt-hour corresponding to different capacity ratios and power limiting rates, and determining a linear change relationship between each capacity ratio in the different capacity ratios and the cost per kilowatt-hour; and under the condition that the power limiting rate threshold value is set in the target area, the optimal capacity matching value of the photovoltaic power station is evaluated based on the linear change relation.

Description

Technical Field

[0001] The present application relates to the technical field of photovoltaic power stations, and in particular to a photovoltaic capacity ratio evaluation method and device, a storage medium and an electronic device. Background Art

[0002] Photovoltaic system is a power generation system that uses photovoltaic modules to convert light energy into electrical energy. It is widely used in distributed power generation and other fields, and is suitable for large power stations, industrial and commercial roofs, residential roofs, and home roofs. Considering that the initial investment cost of photovoltaic system construction is relatively large, and the initial investment cost is closely related to the system capacity and construction cost, as the system capacity increases, the system cost decreases, that is, there is a certain capacity economy effect, and the increase in system capacity will lead to an increase in power-limiting losses and line losses, that is, there is a certain power-limiting economic effect. Therefore, the optimal photovoltaic system capacity should be determined based on the actual conditions of the project location, such as solar energy resources, grid conditions, user types, construction costs, electricity prices, and transmission costs, taking into account the power-limiting economic effect and capacity economic effect.

[0003] At present, some studies have estimated the optimal photovoltaic system capacity by simulating the power generation, power curtailment loss and line loss under different photovoltaic system capacities. Specifically, an optimization model considering system power curtailment loss and line loss has been established, and the optimal photovoltaic system capacity has been calculated by calculating the power generation and power curtailment loss under different photovoltaic system capacities. However, this study only considered system power curtailment loss and line loss, ignoring the impact of system construction costs, resulting in inaccurate estimation of the optimal photovoltaic system capacity.

[0004] With regard to the problem of inaccurate estimation of photovoltaic system capacity in the relevant technologies of existing photovoltaic power stations, no effective solution has been proposed so far.

[0005] Therefore, it is necessary to improve the existing related technologies to overcome the above-mentioned defects in the related technologies and meet the needs of current actual production. Summary of the invention

[0006] The embodiments of the present application provide a photovoltaic capacity ratio evaluation method and device, a storage medium and an electronic device, so as to at least solve the problem of inaccurate photovoltaic system capacity estimation in the related technologies of existing photovoltaic power stations.

[0007] According to one aspect of an embodiment of the present application, a method for evaluating a photovoltaic capacity ratio is provided, comprising: obtaining photovoltaic information of a target area where a photovoltaic power station is located, the photovoltaic information comprising: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data; calculating the construction cost corresponding to the photovoltaic power station under different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and calculating the system efficiency of the photovoltaic power station under different capacity ratios according to the photovoltaic information; inputting the construction cost, system efficiency, and power restriction data into a trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determining the linear change relationship between each capacity ratio and the kilowatt-hour cost in different capacity ratios; and evaluating the optimal capacity ratio value of the photovoltaic power station based on the linear change relationship when a power restriction rate threshold is set in the target area.

[0008] In an exemplary embodiment, before obtaining the photovoltaic information of the target area where the photovoltaic power station is located, the method further includes: receiving geographic location information of multiple target areas input by the target object; calculating the solar energy resources corresponding to each target area according to the geographic location information, and determining the temperature data corresponding to each target area; estimating the power generation of each target area based on the solar energy resources and temperature data.

[0009] In an exemplary embodiment, after receiving the geographic location information of multiple target areas input by the target object, the above method also includes: determining the longitude and latitude corresponding to the multiple target areas, and determining the hourly solar altitude angle and solar azimuth angle of the target areas based on the longitude and latitude; when determining the preset inclination range, calculating the maximum inclination angle of the surface irradiation of the photovoltaic components set in the photovoltaic power station based on the solar altitude angle, the solar azimuth angle, and the preset inclination range; constructing the power station parameters of the photovoltaic power station according to the installation requirements and the maximum inclination angle of the surface irradiation, wherein the power station parameters include at least: the inclination angle of the photovoltaic power station array, the spacing of the photovoltaic power station array, and the land utilization rate.

[0010] In an exemplary embodiment, before photovoltaic information is input into a photovoltaic system model to obtain the system efficiency of a photovoltaic power station under different capacity ratios, the method further includes: determining a target system efficiency corresponding to the photovoltaic system model, wherein the target system efficiency = other losses * (1-inverter efficiency loss) * (1-power limitation loss) * (1-DC line loss) * (1-AC line loss), and other losses include at least one of the following: component temperature loss, dust shielding loss, shadow loss, remote shielding loss, illumination angle loss, dust and snow loss, incident angle pass rate loss, temperature loss, component quality loss, and component series-parallel mismatch loss.

[0011] In an exemplary embodiment, when the power limit rate threshold is set in the target area, after the optimal capacity-matching ratio of the photovoltaic power station is evaluated based on the linear change relationship, the above method also includes: adjusting the current capacity-matching ratio of the photovoltaic power station to the optimal capacity-matching ratio; when the adjustment is completed, receiving real-time messages fed back from the photovoltaic power station accessing the power grid, wherein the real-time messages are used to indicate whether the overall operation of the power grid is stable.

[0012] In an exemplary embodiment, before inputting construction cost, system efficiency, and power restriction data into a trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, the method further includes: parsing the power restriction data, counting power restriction losses, and determining a photovoltaic power restriction mode; wherein the power restriction losses are power restriction losses of power generation under a standard capacity ratio; when the photovoltaic power restriction mode is to restrict power to the photovoltaic power station according to a set inverter power restriction power threshold, determining the integral difference between the actual photovoltaic power generation and the inverter set power restriction power threshold; and determining the power restriction rate based on the integral difference and the target ratio of the real-time capacity ratio.

[0013] According to another aspect of the embodiment of the present application, a photovoltaic capacity ratio evaluation device is also provided, including: an acquisition module, used to acquire photovoltaic information of a target area where a photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data; a calculation module, used to calculate the construction cost corresponding to the photovoltaic power station under different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and to calculate the system efficiency of the photovoltaic power station under different capacity ratios according to the photovoltaic information; a first determination module, used to input the construction cost, system efficiency, and power restriction data into a trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determine the linear change relationship between each capacity ratio and the kilowatt-hour cost in different capacity ratios; an evaluation module, used to evaluate the optimal capacity ratio value of the photovoltaic power station based on the linear change relationship when a power restriction rate threshold is set in the target area.

[0014] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned photovoltaic capacity ratio evaluation method when running.

[0015] According to another aspect of the embodiments of the present application, there is also provided an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the photovoltaic capacity ratio evaluation method through the computer program.

[0016] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the above-mentioned photovoltaic capacity ratio evaluation method is implemented.

[0017] Through this application, the photovoltaic information of the target area where the photovoltaic power station is located is obtained, and the photovoltaic information includes: the solar energy resource parameters of the target area, the configuration information of the photovoltaic components set in the target area, the capacity ratio change information of the target area, and the power restriction data; the construction cost corresponding to the photovoltaic power station under different capacity ratios is calculated according to the photovoltaic information and the preset photovoltaic project cost database, and the system efficiency of the photovoltaic power station under different capacity ratios is calculated according to the photovoltaic information; the construction cost, system efficiency, and power restriction data are input into the trained kilowatt-hour cost model to obtain the kilowatt-hour cost corresponding to different capacity ratios and power restriction rates, and determine the linear change relationship between each capacity ratio in different capacity ratios and the kilowatt-hour cost; when the power restriction rate threshold is set in the target area, the optimal capacity ratio value of the photovoltaic power station is evaluated based on the linear change relationship. The above technical solution solves the problem of inaccurate capacity estimation of the photovoltaic system. Furthermore, by obtaining photovoltaic information, the construction cost and system efficiency of the photovoltaic power station under different capacity ratios are calculated, and the optimal capacity ratio value is evaluated through the kilowatt-hour cost model. As a result, the photovoltaic power station can achieve more efficient power output under power restriction conditions, while reducing construction and operation and maintenance costs, and achieving more sustainable development. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0020] Figure 1 It is a hardware structure block diagram of a computer terminal of a photovoltaic capacity ratio evaluation method according to an embodiment of the present application;

[0021] Figure 2 is a flow chart of a photovoltaic capacity ratio evaluation method according to an embodiment of the present application;

[0022] Figure 3 It is a flow chart of a method for estimating the optimal capacity ratio of photovoltaic power generation in a national region under the condition of power restriction according to an embodiment of the present application;

[0023] Figure 4 is a power generation capacity limitation loss curve diagram under a standard capacity ratio according to an embodiment of the present application;

[0024] Figure 5 is a year-round four-season power restriction power curve diagram according to an embodiment of the present application;

[0025] Figure 6 It is a structural block diagram of a photovoltaic capacity ratio evaluation device according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the solution of the present application, 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 the present application.

[0027] It should be noted that the terms "first", "second", etc. 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 those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0028] The method embodiments provided in the embodiments of the present application can be executed in a computer terminal, a mobile terminal or a similar computing device. Taking running on a computer terminal as an example, Figure 1 1 is a hardware structure block diagram of a computer terminal for evaluating a photovoltaic capacity ratio according to an embodiment of the present application. Figure 1 As shown, the computer terminal may include one or N ( Figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor (Central Processing Unit, CPU) or a programmable logic device (Field Programmable Gate Array, FPGA)) and a memory 104 for storing data, wherein the above-mentioned computer terminal may also include a transmission device 106 and an input and output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1The structure shown is only for illustration and does not limit the structure of the above-mentioned computer terminal. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations shown.

[0029] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the adjustment method of the monitoring network point in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or N magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0030] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0031] In this embodiment, a method for evaluating photovoltaic capacity ratio is provided. Figure 2 is a flow chart of a photovoltaic capacity ratio evaluation method according to an embodiment of the present application, such as Figure 2 As shown, the process includes the following steps S202-S208:

[0032] Step S202: Acquire photovoltaic information of the target area where the photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data;

[0033] Optionally, the configuration information is the inclination angle, spacing and GCR of the photovoltaic module surface, and the hourly irradiation of the front and back sides of the photovoltaic module surface is calculated.

[0034] Optionally, the capacity ratio is the ratio of the photovoltaic DC side capacity to the AC side capacity, which is an important parameter in the design of photovoltaic systems. In the early stage of photovoltaic power station design, the selection of the capacity ratio directly affects the economy and power generation efficiency of the photovoltaic system.

[0035] Step S204: calculating the construction costs of the photovoltaic power stations at different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and calculating the system efficiency of the photovoltaic power stations at different capacity ratios according to the photovoltaic information;

[0036] Optional, based on the benchmark cost index of photovoltaic projects. The sub-items of photovoltaic construction cost are divided into four types: unit kW no adjustment, total price no adjustment, unit kW adjustment, total price adjustment.

[0037] In summary, by collecting photovoltaic information and the preset photovoltaic project cost database, the above method can accurately calculate the construction cost and system efficiency of photovoltaic power stations under different capacity ratios. By calculating the construction cost under different capacity ratios, the most economical capacity ratio scheme can be selected, thereby reducing the construction cost of photovoltaic projects. By calculating the system efficiency under different capacity ratios, the performance of different capacity ratio schemes can be compared and the most suitable scheme can be selected.

[0038] Step S206: inputting the construction cost, the system efficiency, and the power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determining a linear relationship between each capacity ratio in the different capacity ratios and the kilowatt-hour cost;

[0039] Optionally, the cost per kilowatt-hour is calculated as cost per kilowatt-hour (electricity price, irradiation, capacity, system efficiency, land rental fee, unit static investment, transmission line fee). If the input construction cost is 1 million yuan, the system efficiency is 90%, the land rental fee is 100,000 yuan, the unit static investment is 50 yuan / W, the transmission line fee is 50,000 yuan, the electricity price is 0.1 yuan / kWh, the irradiation is 1000kWh / m2, and the power restriction data is 50%. According to the above steps, the cost per kilowatt-hour corresponding to different capacity ratios and power restriction rates is calculated, and the following results are obtained:

[0040] When the capacity ratio is 1:1, the cost of electricity is 0.08 yuan / kWh;

[0041] When the capacity ratio is 2:1, the cost of electricity is 0.07 yuan / kWh;

[0042] When the capacity-to-power ratio is 3:1, the cost per kWh is 0.06 yuan / kWh;

[0043] Through analysis, it can be concluded that each capacity ratio among different capacity ratios has a linear relationship with the cost per kilowatt-hour, that is, the higher the capacity ratio, the lower the cost per kilowatt-hour. Such analysis results can help decision makers better choose the optimal capacity ratio to achieve the goal of reducing the cost per kilowatt-hour.

[0044] In other words, the above method can more comprehensively evaluate the impact of different capacity ratios and power curtailment rates on the cost per kilowatt-hour. At the same time, through model calculation, the cost per kilowatt-hour of different capacity ratios and power curtailment rates can be quickly obtained to provide a reference for decision-making. By analyzing the linear change relationship between each capacity ratio and the cost per kilowatt-hour in different capacity ratios, the performance of the system can be better understood.

[0045] Step S208: When a power limit rate threshold is set in the target area, an optimal capacity ratio of the photovoltaic power station is evaluated based on the linear change relationship.

[0046] The above steps obtain the photovoltaic information of the target area where the photovoltaic power station is located, and the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data; calculate the construction cost of the photovoltaic power station under different capacity ratios according to the photovoltaic information and the preset photovoltaic project cost database, and calculate the system efficiency of the photovoltaic power station under different capacity ratios according to the photovoltaic information; input the construction cost, system efficiency, and power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour cost corresponding to different capacity ratios and power restriction rates, and determine the linear change relationship between each capacity ratio and the kilowatt-hour cost in different capacity ratios; when the power restriction rate threshold is set in the target area, the optimal capacity ratio value of the photovoltaic power station is evaluated based on the linear change relationship. The above technical solution solves the problem of inaccurate capacity estimation of the photovoltaic system.

[0047] In summary, through the above steps, photovoltaic information is obtained to calculate the construction cost and system efficiency of photovoltaic power stations under different capacity ratios, and the optimal capacity ratio is evaluated through the cost per kilowatt-hour model. This enables photovoltaic power stations to achieve more efficient power output under power restrictions, while reducing construction and operation and maintenance costs and achieving more sustainable development.

[0048] In an exemplary embodiment, before obtaining the photovoltaic information of the target area where the photovoltaic power station is located, the method further includes: receiving geographic location information of multiple target areas input by the target object; calculating the solar energy resources corresponding to each target area according to the geographic location information, and determining the temperature data corresponding to each target area; estimating the power generation of each target area based on the solar energy resources and temperature data.

[0049] Optionally, in the above embodiment, if the target object inputs the geographic location information of three target areas, namely area A, area B and area C. According to the geographic location information, the solar energy resources of each area are calculated and the temperature data is determined. By estimating the power generation of each area based on these data, it is obtained that area A can generate 1000kWh of electricity per day, area B can generate 800kWh of electricity per day, and area C can generate 1200kWh of electricity per day. In the implementation process, by executing the above steps, the power generation potential of each target area can be accurately evaluated, which provides an important basis for the site selection and design of photovoltaic power stations and improves the efficiency and accuracy of planning and design.

[0050] In an exemplary embodiment, after receiving the geographic location information of multiple target areas input by the target object, the above method also includes: determining the longitude and latitude corresponding to the multiple target areas, and determining the hourly solar altitude angle and solar azimuth angle of the target areas based on the longitude and latitude; when determining the preset inclination range, calculating the maximum inclination angle of the surface irradiation of the photovoltaic components set in the photovoltaic power station based on the solar altitude angle, the solar azimuth angle, and the preset inclination range; constructing the power station parameters of the photovoltaic power station according to the installation requirements and the maximum inclination angle of the surface irradiation, wherein the power station parameters include at least: the inclination angle of the photovoltaic power station array, the spacing of the photovoltaic power station array, and the land utilization rate.

[0051] Optionally, in the above embodiment, if the received target object input includes geographic location information of three target areas, namely, area A, area B and area C. By determining the longitude and latitude of these three areas, the respective solar altitude angles and solar azimuth angles are calculated. Assume that the preset inclination range is 15 degrees to 30 degrees. According to the solar altitude angle, solar azimuth angle and preset inclination range, the optimal inclination angle of the photovoltaic module in area A is calculated to be 20 degrees, 25 degrees in area B, and 18 degrees in area C. According to the installation requirements and the maximum inclination angle of the surface irradiation, the inclination angle of the photovoltaic power station array in area A is determined to be 20 degrees, the spacing is 2 meters, and the land utilization rate is 80%; the inclination angle of area B is 25 degrees, the spacing is 2.5 meters, and the land utilization rate is 70%; the inclination angle of area C is 18 degrees, the spacing is 2 meters, and the land utilization rate is 75%. In this way, the power station parameters of the photovoltaic power station can be constructed according to the lighting conditions and actual needs of different areas to achieve the best power generation efficiency.

[0052] In an exemplary embodiment, before photovoltaic information is input into a photovoltaic system model to obtain the system efficiency of a photovoltaic power station under different capacity ratios, the method further includes: determining a target system efficiency corresponding to the photovoltaic system model, wherein the target system efficiency = other losses * (1-inverter efficiency loss) * (1-power limitation loss) * (1-DC line loss) * (1-AC line loss), and other losses include at least one of the following: component temperature loss, dust shielding loss, shadow loss, remote shielding loss, illumination angle loss, dust and snow loss, incident angle pass rate loss, temperature loss, component quality loss, and component series-parallel mismatch loss.

[0053] Optionally, the target system efficiency in the above embodiment is used to calculate the efficiency of the system with different capacity ratios. When the capacity ratio changes, the inverter efficiency loss (A1), power limit loss (A2), DC line loss loss (A3), and AC line loss loss (A4) are calculated and compared with the change ratio of the standard capacity ratio. That is: the efficiency of the system with different capacity ratios = other losses (component temperature loss, dust shielding, etc.) * (1-inverter efficiency loss * A1) * (1-power limit loss * A2) * (1-DC line loss loss * A3) * (1-AC line loss loss * A4).

[0054] In an exemplary embodiment, when the power limit rate threshold is set in the target area, after the optimal capacity-matching ratio of the photovoltaic power station is evaluated based on the linear change relationship, the above method also includes: adjusting the current capacity-matching ratio of the photovoltaic power station to the optimal capacity-matching ratio; when the adjustment is completed, receiving real-time messages fed back from the photovoltaic power station accessing the power grid, wherein the real-time messages are used to indicate whether the overall operation of the power grid is stable.

[0055] It is understandable that after receiving the evaluation result of the optimal capacity-matching ratio, the current capacity-matching ratio is adjusted to the optimal capacity-matching ratio. After the adjustment is completed, the real-time message is monitored. If the overall operation of the power grid is stable, the photovoltaic power station can continue to generate electricity at the optimal capacity-matching ratio to improve power generation efficiency and economic benefits. If the real-time message shows that the power grid is unstable, the photovoltaic power station can make adjustments based on the feedback to ensure the reliability of the grid access.

[0056] In an exemplary embodiment, before inputting construction cost, system efficiency, and power restriction data into a trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, the method further includes: parsing the power restriction data, counting power restriction losses, and determining a photovoltaic power restriction mode; wherein the power restriction losses are power restriction losses of power generation under a standard capacity ratio; when the photovoltaic power restriction mode is to restrict power to the photovoltaic power station according to a set inverter power restriction power threshold, determining the integral difference between the actual photovoltaic power generation and the inverter set power restriction power threshold; and determining the power restriction rate based on the integral difference and the target ratio of the real-time capacity ratio.

[0057] It is understandable that if a photovoltaic power station determines the photovoltaic power curtailment mode after statistically calculating the power curtailment losses, and calculates the integral difference between the actual photovoltaic power generation and the power curtailment power threshold set by the inverter. The power curtailment rate is determined to be 20% based on the integral difference and the target ratio of the real-time capacity ratio. Then, the construction cost, system efficiency and power curtailment data are input into the kilowatt-hour cost model, and the kilowatt-hour cost corresponding to different capacity ratios and power curtailment rates is obtained, thereby helping power station managers to better understand the operating costs of photovoltaic power stations and make corresponding adjustments and optimization measures.

[0058] Obviously, the embodiments described above are only some embodiments of the present application, not all embodiments. In order to better understand the method, the above process is described below in conjunction with the embodiments, but it is not intended to limit the technical solutions of the embodiments of the present application, specifically:

[0059] The optional embodiment of the present application provides a method for estimating the optimal capacity ratio of photovoltaic power plants in the whole country under the condition of power curtailment, so as to solve the problem of inaccurate estimation of photovoltaic system capacity. The method comprehensively considers multiple factors such as solar energy resources, system efficiency, photovoltaic construction cost, power curtailment loss, etc., and takes the lowest cost per kilowatt-hour as the optimization goal to find the optimal capacity ratio. By optimizing the capacity ratio of photovoltaic power plants across the country, the power curtailment loss can be effectively reduced, the economic benefits and resource utilization of power plants can be improved, while the cost per kilowatt-hour can be reduced, and the healthy development of the photovoltaic industry can be promoted.

[0060] As an optional implementation, Figure 3 This is a flow chart of a method for estimating the optimal capacity ratio of photovoltaic power generation in a national region under power restriction conditions according to an embodiment of the present application. The specific steps are as follows:

[0061] Step 1: Batch calculate the photovoltaic array design parameters (tilt angle, spacing, GCR, etc.) in different areas.

[0062] Specifically include steps 1.1 to 1.7:

[0063] Step 1.1: Determine the hourly solar altitude and azimuth based on the latitude and longitude of the test site.

[0064] Step 1.2: Set the tilt angle range. The national fixed tilt angle setting range is generally controlled between 0-40°.

[0065] Step 1.3: Calculate the irradiation of the photovoltaic module surface at various inclination angles of 0-40°, and determine the maximum inclination angle of the photovoltaic module surface irradiation. Calculate according to the following formula:

[0066] Irr = irradiance.get_total_irradiance(surface_tilt = array inclination, surface_azimuth = array azimuth, solar_zenith = solar altitude, solar_azimuth = solar azimuth, dni = horizontal direct radiation, ghi = horizontal total radiation, dhi = horizontal scattered radiation, dni_extra = None, albedo = surface reflectivity, surface_type = None, model = 'isotropic photovoltaic irradiation calculation model').

[0067] It should be noted that the existing photovoltaic power station design usually reduces the inclination angle under the existing design angle to increase the installation density. Therefore, the radiation loss compared to the maximum radiation of the photovoltaic module surface is generally set to no more than 0.5%. On this basis, the corresponding array inclination angle is found.

[0068] Step 1.4: Set the basic parameters of the array, including: Array_Short_Edge (array short side length), Tilt (photovoltaic tilt angle), lat_input (project site latitude).

[0069] Step 1.5: Calculate the PV array spacing (Array_Pitch). According to the PV design standard, the PV array should not be blocked by the sun from 9:00 to 15:00. The calculation is as follows:

[0070] Array_Pitch=Array_Short_Edge*np.cos(Tilt*np.pi / 180)+Array_Short_Edge*np.sin(Tilt*np.pi / 18 0)*(0.707*np.tan(lat_input*np.pi / 180)+0.4338) / (0.707-0.4338*np.tan(lat_input*np.pi / 180));

[0071] Step 1.6: Calculate GCR according to the following formula:

[0072] GCR = Array_Short_Edge / Array_Pitch (total area of ​​PV panels / total area of ​​power station);

[0073] Optionally, GCR (Ground Coverage Ratio) refers to the ground coverage ratio, that is, the coverage ratio of photovoltaic panels on the ground. It is usually determined based on the design requirements of the photovoltaic power station, topography and other factors to maximize the use of ground space and improve the power generation efficiency of the photovoltaic power station.

[0074] Step 1.7: Calculate the number of modules in series according to the photovoltaic design standard using the following formula:

[0075] Number of modules in series = 1500 / module open circuit voltage / (1+module voltage temperature coefficient*(local extreme minimum temperature - 25));

[0076] Step 2: Calculate the total radiation exposure of the array surface. Specifically including steps 2.1 to 2.8:

[0077] Step 2.1: Input the parameters of the photovoltaic power station array, such as inclination angle, spacing, GCR, inverter, inverter rated power, etc.

[0078] Step 2.2: Determine the hourly solar altitude and azimuth based on the latitude and longitude of the test site.

[0079] Step 2.3: Calculate the solar incidence angle (guding_aoi_front). You need to calculate the front and back sides of the component according to the following formula:

[0080] guding_aoi_front=irradiance.aoi(surface_tilt=photovoltaic tilt angle, surface_azimuth=array azimuth, solar_zenith=solar altitude angle, solar_azimuth=solar azimuth);

[0081] Step 2.4: To calculate the refraction angle through the glass of the photovoltaic module, you need to calculate the front and back sides of the module according to the following formula:

[0082] guding_iam_front = iam.interp(aoi = solar incident component angle, theta_ref = component different incident angle parameter 1, iam_ref = component different incident angle parameter 1, method = 'quadratic interpolation model', normalize = True);

[0083] Step 2.5: Based on the infinite array model of a large photovoltaic power station, calculate the irradiation of the front and rear panels of the photovoltaic array components after considering the shadow shielding and IAM loss of the front and rear arrays. Calculate according to the following formula:

[0084] Irr_Bifical_iam=bifacial.infinite_sheds.get_irradiance;

[0085] (surface_tilt=PV tilt angle,surface_azimuth=PV azimuth,solar_zenith=sun altitude angle,solar_azimuth=sun azimuth,GCR=GCR,height=module height above ground,pitch=array spacing,ghi=horizontal total irradiation,dhi=horizontal total scattering,dni=horizontal total scattering,model="haydavies" PV model,dni_extra=surface extra irradiation,albedo=surface reflectivity,iam_front=PV module glass refraction angle front,iam_back=PV module glass refraction angle back,bifaciality=module bifaciality,shade_factor=back shading factor, usually 0.2transmission_factor=0,npoints=100);

[0086] Optionally, Irr_Bifical_iam contains three items, namely, total radiation exposure of the array surface (including the front and back surfaces), total radiation exposure of the front surface, and total radiation exposure of the back surface. The relationship between the three is: Irr_Bifical_iam total radiation exposure of the array surface (including the front and back surfaces) = Irr_Bifical_iam total radiation exposure of the front surface + Irr_Bifical_iam total radiation exposure of the back surface.

[0087] Step 2.6: Calculate the total irradiance Irr on the array surface without considering the shadow of the array in front and behind the array and the IAM loss. Calculate according to the following formula:

[0088] Irr = irradiance.get_total_irradiance(surface_tilt = array tilt, surface_azimuth = array azimuth, solar_zenith = solar altitude, solar_azimuth = solar azimuth, dni = horizontal direct radiation, ghi = horizontal total radiation, dhi = horizontal scattered radiation, dni_extra = None, albedo = surface reflectivity, surface_type = None, model = haydavies "photovoltaic model');

[0089] Step 2.7: Calculate the backplane gain of the bifacial module according to the following formula:

[0090] Bifacial module backplane gain = Irr_Bifical_iam total back irradiation / Irr;

[0091] Step 2.8: Calculate the component temperature according to the following formula:

[0092] temp_cell = temperature.pvsyst_cell (poa_global = Irr_Bifical_iam total radiation on the array surface, temp_air = local hourly average temperature, wind_speed = local hourly average wind speed);

[0093] Step 3: Establish a system efficiency model to analyze the impact of capacity ratio changes on inverter efficiency, power curtailment losses, DC line losses, and AC line losses. More accurately evaluate system efficiency by quantifying loss items such as component temperature and dust shielding.

[0094] Optionally, photovoltaic power generation = total irradiation on the array surface * system efficiency; wherein, system efficiency = other losses not affected by capacity ratio and power curtailment * (1-inverter efficiency loss) * (1-power curtailment loss) * (1-DC line loss) * (1-AC line loss); wherein, other losses not affected by capacity ratio and power curtailment include component temperature loss, dust shading, shadow loss, distant shading loss, light angle loss, dust accumulation, incident angle pass rate loss (IAM) temperature loss, component quality loss, component series-parallel mismatch loss, etc.

[0095] Optionally, assume that the standard capacity ratio is set to 1.25, which is consistent with the capacity ratio set by the benchmark cost index; the standard capacity ratio benchmark efficiency is 83% according to the system efficiency under the standard capacity ratio without power restriction through various measurement points. When the capacity ratio changes, the inverter efficiency loss (A1), power restriction loss (A2), DC line loss loss (A3), and AC line loss loss (A4) are calculated and compared with the change ratio of the standard capacity ratio. That is: system efficiency with different capacity ratios = other losses (component temperature loss, dust shielding, etc.) * (1-inverter efficiency loss * A1) * (1-power restriction loss * A2) * (1-DC line loss loss * A3) * (1-AC line loss loss * A4). As shown in Table 1, Table 1 is a photovoltaic system loss topology table.

[0096] Table 1

[0097]

[0098]

[0099] Optionally, the specific calculation process of the inverter efficiency loss (A1), the power limitation loss (A2), the DC line loss loss (A3), and the AC line loss loss (A4) includes steps 3.1 to 3.4:

[0100] Step 3.1: Calculate the inverter efficiency loss (A1), based on the inverter Chinese efficiency provided by the manufacturer, and provide the output power under different input powers. As follows:

[0101] "Pin ":[0.2,15.4,30.5,61.7,91.0,151.8,227.9,304.1,335.02],

[0102] "P out ":[0.0,15.0,30.0,60.0,90.0,150.0,225.0,300.0,330.0],

[0103] According to the above polynomial fitting to form a formula, the input power of the DC side of the input inverter is calculated according to the formula to obtain the AC side power of a single inverter without considering the inverter limit. Because the inverter has a maximum power limit, when the maximum power is exceeded, it is calculated according to the maximum power. If it does not exceed the maximum power, it is calculated according to the AC side of the inverter without considering the inverter limit. The specific calculation is based on the following formula:

[0104] Inverter unrestricted AC output power = np.where (single inverter AC side does not consider inverter limit power > inverter maximum power, inverter maximum power, single inverter AC side does not consider inverter limit power);

[0105] Inverter efficiency loss A1 = (inverter DC side input power - inverter unrestricted AC output power) / inverter DC side input power;

[0106] Step 3.2: Calculation of power curtailment loss (A2), based on the statistical power curtailment loss, is the power curtailment loss of power generation under the standard capacity ratio. Assume that the photovoltaic power curtailment mode curtails the power of the photovoltaic power station according to the set inverter power curtailment power threshold. Figure 4 As shown, Figure 4 It is a power-limiting loss curve diagram of power generation under a standard capacity ratio according to an embodiment of the present application, wherein the horizontal axis represents time (unit: h) and the vertical axis represents power limitation power (unit: kW).

[0107] like Figure 4 As shown, the photovoltaic power generation is the integral A of the photovoltaic power generation curve and the area of ​​the horizontal axis. Under the set power limit power threshold, the power limit amount is the integral B of the area between the photovoltaic power generation curve and the inverter set power limit power threshold straight line, and the power limit rate is integral B / integral A. The default power limit rate is set as the ratio under the standard capacity ratio. The power generation curve changes under different capacity ratios. When the capacity ratio is high, the area formed by the top curve and the inverter set power limit power threshold becomes larger, the power limit amount becomes larger, and the power limit rate increases. When the capacity ratio is low, the area formed by the bottom curve and the inverter set power limit power threshold becomes smaller, the power limit amount becomes smaller, and the power limit rate becomes smaller.

[0108] Optionally, power restriction has a time attribute. According to the annual scale power restriction, the power restriction power is high in summer and autumn, and low or even no power restriction in spring and winter. At present, according to the principle of keeping the power restriction rate consistent in each season of the year, the power restriction power threshold of the inverter in different seasons is reversed. Figure 5 As shown, Figure 5 This is a year-round four-season power-limiting power curve according to an embodiment of the present application. The horizontal axis represents the seasonal changes of the four seasons, the vertical axis represents the power-limiting power (unit: Kw), and the straight line parallel to the vertical axis and intersecting the curve is the power-limiting power threshold set by the inverter in different seasons.

[0109] Step 3.3: Calculation of DC line loss (A3) requires calculation of the output power and loss items of the components after series and parallel connection. The output power of a single component, using the equivalent model of the photovoltaic system of Pvsyst, requires the irradiation received by the photovoltaic array components and the component temperature every hour for 8760 hours throughout the year.

[0110] photocurrent,saturation_current,resistance_series,resistance_shunt,nNsVth=pvsystem.calcparams_pvsyst(effective_irradiance=IrrG,temp_cell=temp_cell,alpha_sc=module_parameters['alpha_sc'],gamma_ref=module_parameters['gamma_ref'],mu_gamma=module_param eters['mu_gamma'],I_L_ref=module_parameters['I_L_ref'],I_o_ref=module_parameters['I_o_ref'],R_sh_ref=module_parameters['R_sh _ref'], R_sh_0=module_parameters['R_sh_0'], R_s=module_parameters['R_s'], cells_in_series=module_parameters['cells_in_series']);

[0111] Monoblock output

[0112] =pvsystem.singlediode(photocurrent,saturation_current,resistance_series,resistance_shunt,nNsVth);

[0113] Optionally, the output of a single module includes the MPPT voltage output by the module hourly, the MPPT current output by the module, and the MPPT power output by the module;

[0114] Optionally, the component temperature is temperature.pvsyst_cell(poa_global=PV array component receiving power, temp_air=average temperature per hour for 8760 days throughout the year, wind_speed=average wind speed per hour for 8760 days throughout the year);

[0115] Optionally, the output power of the components after series-parallel connection = the output power of a single component * the number of components in series * the number of strings connected to a single inverter under different capacity ratios * the series-parallel reduction factor (assuming it is set to 0.995); the DC side input power of the inverter = the output power of the components after series-parallel connection * (1-DC line loss A3); the DC line loss A3 is calculated according to the following formula:

[0116] DC line loss A3 = (component MPPT current * component MPPT current * cable resistivity * DC cable length / cable cross-sectional area) / (component output MPPT power * number of component strings connected in series), where the DC cable length can be fitted based on empirical data as a function of the number of strings connected to a single inverter under different capacity ratios with respect to array spacing.

[0117] Step 3.4: Calculate the AC line loss (A4) according to the following formula:

[0118] AC line loss A4 = (inverter output current * inverter output current * cable resistivity * AC cable length / cable cross-sectional area) / (inverter unrestricted AC output power); wherein, inverter output current = inverter unrestricted AC output power / 800V (inverter rated power).

[0119] Step 4: According to the benchmark cost indicators of photovoltaic projects, the construction costs are divided into different types (unit kW no adjustment, total price no adjustment, unit kW adjustment, total price adjustment), and the total cost under the optimal capacity ratio is recalculated in combination with the capacity ratio changes and power restrictions.

[0120] Optional, as shown in Table 2, Table 2 is a benchmark cost index table for photovoltaic projects.

[0121] Table 2

[0122]

[0123]

[0124]

[0125] Optional, according to the benchmark cost index of photovoltaic projects. The sub-items of photovoltaic construction costs are divided into four types: unit kW is not adjusted, total price is not adjusted, unit kW is adjusted, and total price is adjusted. The details are as follows:

[0126] (1) Unit kW is not adjusted: The DC side capacity is adjusted, and the unit kW cost of photovoltaic construction does not adjust with the capacity. It mainly includes component equipment, bracket equipment, component installation fee, bracket installation fee, etc.

[0127] Optional: Total price of different capacity ratios = (unit kW not adjusted * DC side capacity of different capacity ratios * 1000 / 10000 + unit kW cost adjustment * DC side capacity of different capacity ratios * 1000 / 10000 + total price not adjusted + inverter cost after capacity reduction + total price of AC cable after adjustment); unit kW cost of different capacity ratios = total price of different capacity ratios * 10000 / DC side capacity of different capacity ratios / 1000.

[0128] (2) Total price does not adjust: The capacity on the AC side remains unchanged, and the total price of photovoltaic construction cost does not adjust with the capacity, mainly due to the costs incurred in the substation.

[0129] (3) Adjustment per kW: The capacity of the DC side is adjusted. At the same time, the area occupied per kW changes due to regional changes, which causes the cost per kW to be adjusted. This mainly includes DC cables, AC cables from inverters to box transformers, and land fees for project construction. The cost adjustment per kW can be calculated according to the following formula:

[0130] Unit kW cost adjustment = unit MW area / benchmark cost per acre MWp*unit kW adjustment basis (adjusted with area);

[0131] (4) Total price adjustment: The capacity of the AC side does not change, but the total price adjustment is mainly caused by the change in the floor area, such as the 35kV collector line. The total price adjustment can be calculated according to the following formula:

[0132] Total price adjustment = unit MW area / benchmark construction cost per acre MWp*total price adjustment basis;

[0133] Step 5: With the goal of minimizing the cost per kilowatt-hour, determine the optimal capacity ratio by comparing the costs per kilowatt-hour under different capacity ratios and power restriction rates. The cost per kilowatt-hour can be calculated using the following formula:

[0134] Calculation of electricity cost per kilowatt-hour = electricity cost per kilowatt-hour (electricity price, radiation, capacity, system efficiency, land rental fee, unit static investment, transmission line fee);

[0135] In summary, the optional embodiment of the present application determines the optimal capacity ratio of each region under power restriction by batch calculating the design parameters of photovoltaic arrays in different regions (such as inclination, spacing, GCR, etc.), and combining local temperature and irradiation data. Establish a system efficiency model, analyze the impact of capacity ratio changes on inverter efficiency, power restriction losses, DC line losses, and AC line losses, and more accurately evaluate system efficiency by quantifying loss items such as component temperature and dust shielding. According to the benchmark cost index of photovoltaic projects, the construction cost is divided into different types (unit kW is not adjusted, total price is not adjusted, unit kW is adjusted, and total price is adjusted), and the total cost under the optimal capacity ratio is recalculated in combination with capacity ratio changes and power restriction. With the goal of minimizing the cost per kilowatt-hour, the optimal capacity ratio is determined by comparing the cost per kilowatt-hour under different capacity ratios and power restriction rates. The above technical solution can optimize the capacity ratio of photovoltaic power stations nationwide, effectively reduce power restriction losses, improve the economic benefits and resource utilization of power stations, and at the same time reduce the cost per kilowatt-hour, and promote the healthy development of the photovoltaic industry.

[0136] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0137] In this embodiment, a photovoltaic capacity ratio evaluation device is also provided, which is used to implement the above embodiments and preferred implementations, and will not be repeated here. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0138] Figure 6 : is a structural block diagram of a photovoltaic capacity ratio evaluation device according to an embodiment of the present application, the device comprising:

[0139] The acquisition module 62 is used to acquire photovoltaic information of the target area where the photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data;

[0140] A calculation module 64 is used to calculate the construction cost of the photovoltaic power station under different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and to calculate the system efficiency of the photovoltaic power station under different capacity ratios according to the photovoltaic information;

[0141] A first determination module 66 is used to input the construction cost, the system efficiency, and the power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determine a linear change relationship between each capacity ratio in the different capacity ratios and the kilowatt-hour cost;

[0142] The evaluation module 68 is used to evaluate the optimal capacity ratio of the photovoltaic power station based on the linear change relationship when the power limit rate threshold is set in the target area.

[0143] The above device obtains photovoltaic information of the target area where the photovoltaic power station is located, and the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data; calculates the construction cost of the photovoltaic power station under different capacity ratios according to the photovoltaic information and the preset photovoltaic project cost database, and calculates the system efficiency of the photovoltaic power station under different capacity ratios according to the photovoltaic information; inputs the construction cost, system efficiency, and power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour cost corresponding to different capacity ratios and power restriction rates, and determines the linear change relationship between each capacity ratio in different capacity ratios and the kilowatt-hour cost; when the power restriction rate threshold is set in the target area, the optimal capacity ratio value of the photovoltaic power station is evaluated based on the linear change relationship. The above technical solution solves the problem of inaccurate capacity estimation of the photovoltaic system. Furthermore, by obtaining photovoltaic information, the construction cost and system efficiency of the photovoltaic power station under different capacity ratios are calculated, and the optimal capacity ratio value is evaluated through the kilowatt-hour cost model. As a result, the photovoltaic power station can achieve more efficient power output under power restriction conditions, while reducing construction and operation and maintenance costs, and achieving more sustainable development.

[0144] In an exemplary embodiment, the above-mentioned device also includes: a receiving module, which is used to receive the geographical location information of multiple target areas input by the target object before obtaining the photovoltaic information of the target area where the photovoltaic power station is located; calculate the solar energy resources corresponding to each target area according to the geographical location information, and determine the temperature data corresponding to each target area; estimate the power generation of each target area based on the solar energy resources and temperature data.

[0145] In an exemplary embodiment, the above-mentioned receiving module also includes: a determination unit, which is used to determine the longitude and latitude corresponding to the multiple target areas after receiving the geographic location information of multiple target areas input by the target object, and determine the hourly solar altitude angle and solar azimuth angle of the target area based on the longitude and latitude; when determining the preset inclination range, calculate the maximum inclination angle of the surface irradiation of the photovoltaic components set in the photovoltaic power station based on the solar altitude angle, the solar azimuth angle, and the preset inclination range; construct the power station parameters of the photovoltaic power station according to the installation requirements and the maximum inclination angle of the surface irradiation, wherein the power station parameters include at least: the inclination angle of the photovoltaic power station array, the spacing of the photovoltaic power station array, and the land utilization rate.

[0146] In an exemplary embodiment, the above-mentioned device also includes: a second determination module, which is used to input photovoltaic information into the photovoltaic system model, and before obtaining the system efficiency of the photovoltaic power station under different capacity ratios, determine the target system efficiency corresponding to the photovoltaic system model, wherein the target system efficiency = other losses * (1-inverter efficiency loss) * (1-power limitation loss) * (1-DC line loss loss) * (1-AC line loss loss), and other losses include at least one of the following: component temperature loss, dust shading loss, shadow loss, remote shading loss, light angle loss, dust and snow loss, incident angle pass rate loss temperature loss, component quality loss, and component series-parallel mismatch loss.

[0147] In an exemplary embodiment, the above-mentioned device also includes: an adjustment module, which is used to adjust the current capacity ratio of the photovoltaic power station to the optimal capacity ratio after evaluating the optimal capacity ratio of the photovoltaic power station based on the linear change relationship when the power limit rate threshold is set in the target area; when the adjustment is completed, receive real-time messages fed back from the photovoltaic power station accessing the power grid, wherein the real-time messages are used to indicate whether the overall operation of the power grid is stable.

[0148] In an exemplary embodiment, the above-mentioned device also includes: an analysis module, which is used to input construction cost, system efficiency, and power limitation data into a trained kilowatt-hour cost model, and before obtaining the kilowatt-hour costs corresponding to different capacity ratios and power limitation rates, analyze the power limitation data, count the power limitation losses, and determine the photovoltaic power limitation mode; wherein the power limitation losses are the power limitation losses of power generation under the standard capacity ratio; when the photovoltaic power limitation mode is to limit the power of the photovoltaic power station according to the set inverter power limitation power threshold, determine the integral difference between the actual photovoltaic power generation and the inverter set power limitation power threshold; determine the power limitation rate according to the integral difference and the target ratio of the real-time capacity ratio.

[0149] An embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0150] Optionally, in this embodiment, the storage medium may be configured to store a computer program for performing the following steps:

[0151] S1. Acquire photovoltaic information of a target area where a photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic modules set in the target area, capacity ratio change information of the target area, and power restriction data;

[0152] S2. Calculating the construction costs of photovoltaic power stations at different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and calculating the system efficiency of the photovoltaic power stations at different capacity ratios according to the photovoltaic information;

[0153] S3, inputting the construction cost, the system efficiency, and the power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determining the linear relationship between each capacity ratio in the different capacity ratios and the kilowatt-hour cost;

[0154] S4. When a power limit rate threshold is set in the target area, an optimal capacity ratio of the photovoltaic power station is evaluated based on the linear change relationship.

[0155] In an exemplary embodiment, the computer-readable storage medium may include, but is not limited to, various media that can store computer programs, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0156] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0157] An embodiment of the present application further provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps in any one of the above method embodiments are performed.

[0158] An embodiment of the present application further provides another computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in any of the above method embodiments are implemented.

[0159] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0160] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0161] S1. Acquire photovoltaic information of a target area where a photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic modules set in the target area, capacity ratio change information of the target area, and power restriction data;

[0162] S2. Calculating the construction costs of photovoltaic power stations at different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and calculating the system efficiency of the photovoltaic power stations at different capacity ratios according to the photovoltaic information;

[0163] S3, inputting the construction cost, the system efficiency, and the power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determining the linear relationship between each capacity ratio in the different capacity ratios and the kilowatt-hour cost;

[0164] S4. When a power limit rate threshold is set in the target area, an optimal capacity ratio of the photovoltaic power station is evaluated based on the linear change relationship.

[0165] In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0166] For specific examples in this embodiment, reference may be made to the examples described in the above embodiments and exemplary implementation modes, and this embodiment will not be described in detail herein.

[0167] Obviously, those skilled in the art should understand 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 N computing devices, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that here, or they can be made into individual integrated circuit modules, or N of the modules or steps can be made into a single integrated circuit module for implementation. In this way, the present application is not limited to any specific combination of hardware and software.

[0168] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for evaluating photovoltaic capacity ratio, characterized in that: include: Acquire photovoltaic information of a target area where a photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data; Calculating the construction costs of photovoltaic power stations at different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and calculating the system efficiency of photovoltaic power stations at different capacity ratios according to the photovoltaic information; Input the construction cost, the system efficiency, and the power restriction data into the trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determine the linear change relationship between each capacity ratio in the different capacity ratios and the kilowatt-hour cost; In the case where a power limit rate threshold is set in the target area, an optimal capacity ratio value of the photovoltaic power station is evaluated based on the linear change relationship.

2. The photovoltaic capacity ratio evaluation method according to claim 1 is characterized in that: Before obtaining photovoltaic information of a target area where a photovoltaic power station is located, the method further includes: Receiving geographic location information of multiple target areas input by a target object; Calculate the solar energy resources corresponding to each target area according to the geographical location information, and determine the temperature data corresponding to each target area; The power generation of each target area is estimated based on the solar energy resource and the temperature data.

3. The photovoltaic capacity ratio evaluation method according to claim 2, characterized in that: After receiving the geographical location information of the plurality of target areas input by the target object, the method further includes: Determine the longitudes and latitudes corresponding to the multiple target areas, and determine the hourly solar altitude angle and solar azimuth angle of the target areas based on the longitudes and latitudes; When a preset inclination range is determined, the maximum inclination of the surface irradiance of the photovoltaic components arranged in the photovoltaic power station is calculated based on the solar altitude angle, the solar azimuth angle, and the preset inclination range; and the power station parameters of the photovoltaic power station are constructed according to the installation requirements and the maximum inclination of the surface irradiance, wherein the power station parameters include at least: the inclination of the photovoltaic power station array, the spacing of the photovoltaic power station array, and the land utilization rate.

4. The photovoltaic capacity ratio evaluation method according to claim 1, characterized in that: Before inputting the photovoltaic information into a photovoltaic system model to obtain the system efficiency of the photovoltaic power station under different capacity ratios, the method further includes: Determine a target system efficiency corresponding to the photovoltaic system model, wherein the target system efficiency = other losses * (1-inverter efficiency loss) * (1-power limitation loss) * (1-DC line loss loss) * (1-AC line loss loss), and the other losses include at least one of the following: component temperature loss, dust shading loss, shadow loss, remote shading loss, illumination angle loss, dust and snow loss, incident angle pass rate loss, temperature loss, component quality loss, and component series-parallel mismatch loss.

5. The photovoltaic capacity ratio evaluation method according to claim 1, characterized in that: In the case where the power limit rate threshold is set in the target area, after the optimal capacity ratio of the photovoltaic power station is evaluated based on the linear change relationship, the method further includes: Adjusting the current capacity-matching ratio of the photovoltaic power station to the optimal capacity-matching ratio; When the adjustment is completed, a real-time message fed back from the photovoltaic power station being connected to the power grid is received, wherein the real-time message is used to indicate whether the overall operation of the power grid is stable.

6. The photovoltaic capacity ratio evaluation method according to claim 1, characterized in that: Before inputting the construction cost, the system efficiency, and the power restriction data into the trained per-kilowatt-hour cost model to obtain per-kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, the method further includes: Analyze the power-limiting data, calculate the power-limiting losses, and determine the photovoltaic power-limiting mode; wherein the power-limiting losses are power-limiting losses of power generation under the standard capacity ratio; In the case where the photovoltaic power limiting mode is to limit the power of the photovoltaic power station according to the set inverter power limiting power threshold, determining the integral difference between the actual photovoltaic power generation and the inverter set power limiting power threshold; The power cutoff rate is determined according to the integral difference and the target ratio of the real-time capacity matching ratio.

7. A photovoltaic capacity ratio evaluation device, characterized in that: include: An acquisition module is used to acquire photovoltaic information of a target area where a photovoltaic power station is located, wherein the photovoltaic information includes: solar energy resource parameters of the target area, configuration information of photovoltaic components set in the target area, capacity ratio change information of the target area, and power restriction data; A calculation module, used to calculate the construction cost of the photovoltaic power station under different capacity ratios according to the photovoltaic information and a preset photovoltaic project cost database, and to calculate the system efficiency of the photovoltaic power station under different capacity ratios according to the photovoltaic information; A first determination module is used to input the construction cost, the system efficiency, and the power restriction data into a trained kilowatt-hour cost model to obtain the kilowatt-hour costs corresponding to different capacity ratios and power restriction rates, and determine a linear change relationship between each capacity ratio in the different capacity ratios and the kilowatt-hour cost; An evaluation module is used to evaluate the optimal capacity ratio of the photovoltaic power station based on the linear change relationship when a power limit rate threshold is set in the target area.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 6 when executed.

9. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 6 through the computer program.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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