Photovoltaic engineering design optimization method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a photovoltaic engineering design optimization method and device, equipment and a storage medium, and the method comprises the steps: obtaining the generation power information of a target photovoltaic engineering, and determining the array design parameters corresponding to the target photovoltaic engineering; wherein the array design parameters comprise at least one of a component spacing, an installed capacity, a capacity ratio and a power generation correction coefficient; based on the generated power information and the array design parameters, determining an engineering simulation model corresponding to the target photovoltaic engineering; and based on the engineering simulation model, target engineering parameters in the target photovoltaic engineering are optimized, and the optimization process of the target photovoltaic engineering is realized. According to the technical scheme, the problems that in the prior art, a photovoltaic system is long in design period, high in design difficulty and insufficient in design accuracy are solved, a standard optimization method for the photovoltaic engineering design scheme can be provided, data support can be provided for early-stage investment decision making of a photovoltaic project, and the method is suitable for large-scale popularization and application. The design efficiency of the photovoltaic system is improved, the operation risk is reduced, and the market competitiveness is enhanced.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of photovoltaic engineering design, and in particular to a photovoltaic engineering design optimization method, device, equipment and storage medium. Background Art

[0002] In recent years, with the proposal of the "dual carbon" goal, the transformation of the global energy structure and the concept of sustainable development have gradually gained popularity. As an important part of the renewable energy field, the photovoltaic industry is increasingly attracting the attention of governments and enterprises around the world.

[0003] However, with the continuous growth of photovoltaic installed capacity and the expansion of photovoltaic business scale, the management and regulation of photovoltaic systems are facing unprecedented challenges. Traditional photovoltaic business regulation methods often rely on manual experience and simple control strategies, which makes it difficult to achieve accurate and efficient operation of photovoltaic systems. At the same time, the operation of photovoltaic systems is affected by many factors, such as light intensity, temperature, equipment performance, etc. The changes in these factors make the regulation of photovoltaic business more complicated. In the rapid development of the photovoltaic industry, how to achieve accurate and efficient design of photovoltaic power generation systems has become one of the key factors in the development of the photovoltaic industry. Summary of the invention

[0004] The embodiments of the present invention provide a photovoltaic engineering design optimization method, device, equipment and storage medium, which can propose a standard optimization method for photovoltaic engineering design schemes, provide data support for early investment decisions of photovoltaic projects, improve the design efficiency of photovoltaic systems, reduce operational risks, and enhance market competitiveness.

[0005] In a first aspect, an embodiment of the present invention provides a photovoltaic engineering design optimization method, the method comprising:

[0006] Obtain power generation information of a target photovoltaic project, and determine array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio, and power generation correction factor; based on the power generation information and the array design parameters, determine an engineering simulation model corresponding to the target photovoltaic project; based on the engineering simulation model, optimize target engineering parameters in the target photovoltaic project to achieve an optimization process for the target photovoltaic project.

[0007] In a second aspect, an embodiment of the present invention provides a photovoltaic engineering design optimization device, the device comprising:

[0008] A design parameter determination module is used to obtain the power generation information of the target photovoltaic project and determine the array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio and power generation correction coefficient; a simulation model determination module is used to determine the engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters; an engineering optimization module is used to optimize the target engineering parameters in the target photovoltaic project based on the engineering simulation model to achieve the optimization process of the target photovoltaic project.

[0009] In a third aspect, an embodiment of the present invention provides a computer device, the computer device comprising:

[0010] one or more processors;

[0011] A memory for storing one or more programs;

[0012] When the one or more programs are executed by the one or more processors, the one or more processors implement the photovoltaic engineering design optimization method described in any embodiment.

[0013] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the photovoltaic engineering design optimization method described in any embodiment.

[0014] The technical solution provided by the embodiment of the present invention obtains the power generation information of the target photovoltaic project and determines the array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio and power generation correction coefficient; based on the power generation information and the array design parameters, the engineering simulation model corresponding to the target photovoltaic project is determined; based on the engineering simulation model, the target engineering parameters in the target photovoltaic project are optimized to achieve the optimization process of the target photovoltaic project. The technical solution of the embodiment of the present invention solves the problems of the prior art such as the long design cycle, high design difficulty and insufficient design accuracy of the photovoltaic system, and can propose a standard optimization method for the photovoltaic engineering design scheme, which can provide data support for the early investment decision of the photovoltaic project, improve the design efficiency of the photovoltaic system, reduce the operation risk and enhance the market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of a photovoltaic engineering design optimization method provided by an embodiment of the present invention;

[0016] Figure 2 This is another flow chart of a photovoltaic engineering design optimization method provided by an embodiment of the present invention;

[0017] Figure 3 It is a schematic diagram of component types of a model component list provided by an embodiment of the present invention;

[0018] Figure 4 is a schematic diagram of a simulation model interface provided by an embodiment of the present invention;

[0019] Figure 5 is a schematic diagram of an engineering simulation model provided by an embodiment of the present invention;

[0020] Figure 6 This is a workflow diagram for optimizing photovoltaic engineering design provided by an embodiment of the present invention;

[0021] Figure 7 It is a structural schematic diagram of a photovoltaic engineering design optimization device provided by an embodiment of the present invention;

[0022] Figure 8 It is a structural schematic diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0024] Figure 1 It is a flow chart of a photovoltaic engineering design optimization method provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the design scheme of photovoltaic engineering. The method can be executed by a photovoltaic engineering design optimization device, and the device can be implemented by software and / or hardware.

[0025] like Figure 1 As shown, the photovoltaic engineering design optimization method includes the following steps:

[0026] S110, obtaining power generation information of a target photovoltaic project, and determining array design parameters corresponding to the target photovoltaic project.

[0027] Among them, the target photovoltaic project may be a photovoltaic project that needs to be optimized in design. The power generation information may be information indicating the size of the power generation corresponding to the target photovoltaic project. Exemplarily, the power generation information may be obtained by statistics on the power consumption end, or may be obtained by manual input. The specific method of obtaining the power generation information is not limited here. Exemplarily, historical load data may be used to analyze the load of the power consumption unit. Before performing the load calculation, it is necessary to understand the power consumption classification (single system, two-part system), voltage level, capacity (demand) power price, etc. of the power consumption unit; obtain the power consumption unit's electricity bill in previous years, and calculate the electricity charges for different periods of each month of the year through the total power consumption, billing cycle, electricity price structure and total cost on the electricity bill, and obtain the electricity charges for different periods of the power consumption unit through the electricity price information. The load curve of the power consumption unit is obtained based on the average load value of the same period for many years, which is also the power generation curve of the photovoltaic project.

[0028] Further, the array design parameters may be arrangement parameters associated with the photovoltaic equipment in the target photovoltaic project. Exemplarily, the array design parameters include: at least one of component spacing, installed capacity, capacity-matching ratio, and power generation correction factor. Among them, the component spacing represents the spacing between photovoltaic components in the site corresponding to the target photovoltaic project. The installed capacity represents the installed number of photovoltaic components in the site corresponding to the target photovoltaic project. The capacity-matching ratio represents the ratio of the number of inverters to the number of photovoltaic components in the site corresponding to the target photovoltaic project. The power generation correction factor may be a correction factor for the power generation power of the target photovoltaic project.

[0029] S120: Determine an engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters.

[0030] The engineering simulation model may be a simulation model of a target photovoltaic project. Specifically, the user may pre-build an initial simulation model based on interactive operations, and then assign values ​​to the initial simulation model based on the power generation information and the array design parameters to obtain an engineering simulation model.

[0031] S130: Optimizing target engineering parameters in the target photovoltaic project based on the engineering simulation model to achieve an optimization process for the target photovoltaic project.

[0032] The target engineering parameter may be an engineering parameter that needs to be optimized. Specifically, the target engineering parameter may be manually specified and selected. Furthermore, a simulation test may be performed based on the engineering simulation model, and the target engineering parameter may be optimized through the simulation test to obtain the preferred parameters of the target engineering parameter, and then the target engineering parameter may be adjusted to the corresponding preferred parameters to achieve the optimization process of the target photovoltaic project.

[0033] The technical solution provided by the embodiment of the present invention obtains the power generation information of the target photovoltaic project and determines the array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio and power generation correction coefficient; based on the power generation information and the array design parameters, the engineering simulation model corresponding to the target photovoltaic project is determined; based on the engineering simulation model, the target engineering parameters in the target photovoltaic project are optimized to achieve the optimization process of the target photovoltaic project. The technical solution of the embodiment of the present invention solves the problems of the prior art such as the long design cycle, high design difficulty and insufficient design accuracy of the photovoltaic system, and can propose a standard optimization method for the photovoltaic engineering design scheme, which can provide data support for the early investment decision of the photovoltaic project, improve the design efficiency of the photovoltaic system, reduce the operation risk and enhance the market competitiveness.

[0034] Figure 2 It is another flow chart of a photovoltaic engineering design optimization method provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the design scheme of a photovoltaic project. Based on the above embodiment, this embodiment further explains how to obtain the power generation information of the target photovoltaic project and determine the array design parameters corresponding to the target photovoltaic project; how to determine the engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters; and how to optimize the target engineering parameters in the target photovoltaic project based on the engineering simulation model. The device can be implemented by software and / or hardware and integrated in a computer device with application development function.

[0035] like Figure 2 As shown, the photovoltaic engineering design optimization method includes the following steps:

[0036] S210: Acquire power generation information of a target photovoltaic project, and determine array design parameters corresponding to the target photovoltaic project.

[0037] Optionally, determining the component spacing corresponding to the target photovoltaic project includes: obtaining lighting parameter information of the location of the target photovoltaic project and component arrangement information of photovoltaic components in the target photovoltaic project, determining the minimum component spacing between photovoltaic components, and using the minimum component spacing as the component spacing corresponding to the target photovoltaic project.

[0038] The illumination parameter information may include the solar altitude angle and the solar azimuth angle. The component arrangement information includes: the size information, arrangement method, installation inclination angle and other information of the photovoltaic components. The minimum component spacing may be the minimum spacing to ensure that the photovoltaic components do not block each other. Specifically, based on the illumination parameter information and the component arrangement information, the lowest spacing when the photovoltaic components do not block each other in the true sun at the location can be determined to obtain the minimum component spacing.

[0039] Optionally, determining the installed capacity corresponding to the target photovoltaic project includes: determining the occupied area of ​​a single photovoltaic module based on the module spacing and module parameter information of the photovoltaic modules in the target photovoltaic project; obtaining the available site area corresponding to the target photovoltaic project, and determining the installed capacity based on the occupied area of ​​a single photovoltaic module and the available site area.

[0040] The component parameter information may be the size parameters of the photovoltaic component. The occupied area may be the area used by a single photovoltaic component while ensuring that there is no mutual obstruction. Specifically, the component area of ​​the photovoltaic component itself may be determined based on the component parameter information, and then the component spacing may be increased around the component area to obtain the occupied area. The available area of ​​the site may be the available area of ​​the site where the target photovoltaic project is located. Furthermore, the available area of ​​the site may be divided by the occupied area of ​​a single photovoltaic component to obtain the installed capacity.

[0041] Exemplarily, specific calculation methods for various array design parameters are listed below.

[0042] (1) Calculation of minimum spacing between components

[0043] The spacing calculation is based on the parameters of the photovoltaic modules. The specific requirements for the minimum spacing calculation are that the spacing between the rows and columns in the photovoltaic array and between the photovoltaic arrays should ensure that the photovoltaic modules are not blocked from front to back, left to right, and right to left during the period of 09:00 to 15:00 (local true solar time) every day. The solar altitude angle and azimuth angle of the true solar time on the winter solstice are used for spacing calculation. The size and arrangement of the photovoltaic modules must be considered during the calculation process, and whether they are horizontally or vertically arranged when the tilt installation is used. The calculation formula for the center spacing of the photovoltaic array on a flat site that is not blocked is:

[0044] D=L*cosθ+D'

[0045] in

[0046] D'=L*sinθ*cotα*cosγ

[0047] Where L is the length of the array slope, θ is the installation inclination angle of the photovoltaic component, α is the solar azimuth, and γ is the azimuth of the photovoltaic component.

[0048] (2) Installed capacity estimation

[0049] The installed capacity is estimated based on the minimum spacing between components and the available area of ​​the site. The area occupied by a single component can be estimated through the size parameters of the photovoltaic panels and the minimum spacing. The number of components to be arranged at the current site can be estimated through the quotient of the available area of ​​the site and the area occupied by a single component.

[0050] P install =N*M*P m Where N is the number of components in series, M is the number of strings in parallel, and P_m is the peak power of the photovoltaic module.

[0051] (3) String design

[0052] The string design designs the number of PV modules connected to the inverter in series and parallel based on the parameters of the inverter and PV modules. The appropriate number of inverters is selected considering the inverter capacity and the installed capacity of the site. The economic factors are considered while keeping the capacity ratio of the entire site below 1.2. The calculation principle is as follows:

[0053] a) The output voltage of a string formed by connecting solar panels in series must be within the allowable input voltage range for normal operation of the inverter;

[0054] b) The open circuit voltage of the solar cell modules connected in series should not exceed the maximum DC voltage of the inverter;

[0055] c) The short-circuit current of the solar cell groups connected in series and parallel should not exceed the maximum input current of the inverter;

[0056] d) The temperature characteristics of solar cell modules should be considered;

[0057] e) The DC cable path from the solar panel to the inverter should be as short as possible to reduce DC voltage loss and power loss.

[0058] (4) Loss calculation

[0059] The loss coefficient of the photovoltaic power generation system mainly includes the photovoltaic module type correction coefficient, the inclination angle of the photovoltaic array, the azimuth correction coefficient, the availability of the photovoltaic power generation system, the light utilization rate, the inverter efficiency, the collection line loss, the step-up transformer loss, the photovoltaic module surface contamination correction coefficient and other factors. The comprehensive loss is obtained by multiplying the various losses.

[0060] K=K1*K3*K4*K5*K6*K7*K8

[0061] Where K1 is the PV module type correction coefficient, K2 is the PV array inclination and azimuth correction coefficient, K3 is the PV power generation system availability, K4 is the light utilization rate, K5 is the inverter efficiency, K6 is the collector line loss, K7 is the step-up transformer loss, and K8 is the PV module surface contamination correction coefficient.

[0062] (5) Calculation of power generation

[0063] The annual power generation can be calculated based on the installed capacity and losses combined with the sunlight conditions at the project location.

[0064]

[0065] Where K is the comprehensive efficiency coefficient of the photovoltaic system, H_A is the total horizontal solar radiation (kWh / m2, peak hours). When calculating the monthly power generation, it should be the product of the average daily total horizontal solar radiation of each month and the number of days in each month. E_P is the grid-connected power generation (kWh), E_S is the irradiance under standard conditions (constant, 1kW / m2), A is the total area of ​​the array components within the calculation range (m2), and η is the component conversion efficiency (%), which is determined by the data provided by the manufacturer.

[0066] (6) Calculation of self-generation and self-consumption rate

[0067] The self-generation and self-use rate refers to the user's self-built photovoltaic power generation system, the electricity generated is used for their own use first, and the excess electricity is sold online. The higher the self-generation and self-use rate, the higher the user's utilization of renewable energy. The annual self-generation and self-use rate is calculated as follows:

[0068]

[0069] Among them, I_year is the annual self-generation and self-consumption rate; E_P is the peak power generation; E_P is the peak power generation; E_P is the flat power generation; E_P is the valley power generation; P_P is the peak load; P_P is the peak load; P_P is the flat load; P_P is the valley load.

[0070] S220: When a model building instruction is received, construct an initial simulation model based on the model building instruction.

[0071] The model building instruction may be an interactive instruction for building a simulation model. The initial simulation model may be an engineering simulation model of a target photovoltaic project.

[0072] Optionally, an initial simulation model is constructed based on the model construction instruction, including: when a model trigger instruction is received, a model component list is displayed on a preset interface; when a component interaction instruction is received, a target photovoltaic component is determined from the model component list; when a component arrangement instruction is received, an association relationship is established between the target photovoltaic components to obtain an initial simulation model.

[0073] The model trigger instruction may be a trigger instruction for starting to build a simulation model. The model component list may include multiple model components for the user to select. For example, Figure 3 : is a schematic diagram of component types of a model component list provided by an embodiment of the present invention. Figure 3 As shown, the model components in the model component list include: grounding device, monitoring device, current transformer, cable head, plug and socket, solar irradiation component, photovoltaic component, inverter, junction box, well point, transformer, distribution cabinet, fuse, circuit breaker, disconnector and surge protector.

[0074] Further, the component interaction instruction may be a selection instruction for a model component. The target photovoltaic component may be based on the model component determined for building the simulation model. Specifically, based on the component interaction instruction, the corresponding model component may be selected from the model component list as the target model component. The component arrangement instruction may be an instruction for establishing a connection relationship between target model components. Specifically, based on the component arrangement instruction, an association relationship between target model components may be constructed, and then the target model components may be arranged and connected based on the association relationship to obtain an initial simulation model.

[0075] For example, Figure 4 FIG. 1 is a schematic diagram of a simulation model interface provided by an embodiment of the present invention. Figure 4 As shown, the user can select available model components and then build association relationships between multiple model components based on interactive operations.

[0076] S230. Based on the power generation information and the array design parameters, the operating parameters and posture parameters of the photovoltaic components in the initial simulation model are adjusted to obtain an engineering simulation model.

[0077] Among them, the working parameters can be the simulation parameters of the initial simulation model for photovoltaic power generation. The posture parameters can be the position and posture parameters of each component in the initial simulation model. The engineering simulation model can be a simulation model obtained after adjusting the initial simulation model. Specifically, based on the parameters corresponding to the power generation information and the array design parameters, the target working parameters and target posture parameters can be determined, and then the working parameters of the initial simulation model can be adjusted to the target working parameters, and the posture parameters of the initial simulation model can be adjusted to the target posture parameters, thereby obtaining the engineering simulation model.

[0078] Exemplarily, a simulation model library can be constructed based on the Modelica language, so that users can construct an initial simulation model based on the simulation model library. Furthermore, the power generation information and array design parameters can be assigned to the initial simulation model, such as light irradiation, photovoltaic array electrical parameters and quantity, inverter electrical parameters and quantity, etc., to provide some fixed parameters for subsequent parameter optimization. When building the model, it is necessary to consider the primary and secondary factors of the photovoltaic model. In the photovoltaic project planning stage, the focus should be on estimating the system installed capacity and power generation. In the modeling process, only factors related to power generation need to be considered. Exemplarily, Figure 5 It is a schematic diagram of an engineering simulation model provided by an embodiment of the present invention.

[0079] S240: Optimizing target engineering parameters in the target photovoltaic project based on the engineering simulation model to achieve an optimization process for the target photovoltaic project.

[0080] The target engineering parameter may be an engineering parameter that needs to be optimized. Specifically, the target engineering parameter may be manually specified and selected. Furthermore, a simulation test may be performed based on the engineering simulation model, and the target engineering parameter may be optimized through the simulation test to obtain the preferred parameters of the target engineering parameter, and then the target engineering parameter may be adjusted to the corresponding preferred parameters to achieve the optimization process of the target photovoltaic project.

[0081] Optionally, based on an engineering simulation model, with a preset capacity ratio range and the total price of the inverter as constraints, the number of inverters can be used as a target engineering parameter for optimization to determine the target number of inverters.

[0082] The preset capacity ratio range may be a preset reference range for the capacity ratio. Exemplarily, the preset capacity ratio range may be set manually, for example, the preset capacity ratio range may be set to be no greater than 1.2. Furthermore, within the set capacity ratio range and with the total price of the inverter as a constraint, the number of inverters may be optimized to determine the preferred value corresponding to the number of inverters.

[0083] Exemplarily, the particle swarm optimization algorithm can be used as a parameter optimization algorithm to improve the design accuracy and economy of the photovoltaic system. For example, for the inverter quantity matching problem, it is necessary to ensure that the capacity ratio of each site is not greater than 1.2, while meeting the best economy. The capacity ratio and the total price of the inverter are used as optimization constraints, and the number of site inverters is used as the constraint target for optimization. Among them, the particle swarm optimization algorithm is the first to propose a particle swarm optimization algorithm based on the laws of bird flock flight and fish school predation. This method belongs to the random evolutionary search algorithm, has parallel processing characteristics, good robustness, easy implementation, high computational efficiency, and can effectively solve most global optimization problems.

[0084] For example, in order to better understand the technical solution provided by the present invention, a specific embodiment is introduced below:

[0085] Figure 6 This is a workflow diagram for optimizing photovoltaic engineering design provided by an embodiment of the present invention. Figure 6 As shown in the figure, the workflow for photovoltaic engineering design optimization includes the following steps: first import the initial plan, then select the parameter optimization algorithm, then set the parameters to be optimized (such as the number of inverters of each model) and constraints, select fixed parameters, set the optimization goals (such as capacity ratio less than or equal to 1.2; the lowest inverter price; the largest inverter capacity), then optimize after evaluating the rationality of the parameters to be optimized, and output the optimization results after multiple iterations of optimization.

[0086] The technical solution provided by the embodiment of the present invention obtains the power generation information of the target photovoltaic project and determines the array design parameters corresponding to the target photovoltaic project; upon receiving the model building instruction, builds an initial simulation model based on the model building instruction; based on the power generation information and the array design parameters, adjusts the working parameters and posture parameters of the photovoltaic components in the initial simulation model to obtain the engineering simulation model; based on the engineering simulation model, optimizes the target engineering parameters in the target photovoltaic project to achieve the optimization process of the target photovoltaic project. The technical solution of the embodiment of the present invention solves the problems of the long design cycle, high design difficulty and insufficient design accuracy of the photovoltaic system in the prior art, and can propose a standard optimization method for the photovoltaic engineering design scheme, which can provide data support for the early investment decision of photovoltaic projects, improve the design efficiency of photovoltaic systems, reduce operational risks, and enhance market competitiveness.

[0087] Figure 7 It is a structural schematic diagram of a photovoltaic engineering design optimization device provided by an embodiment of the present invention. The embodiment of the present invention can be applied to the scenario of optimizing the design scheme of photovoltaic engineering. The device can be implemented by software and / or hardware and integrated into a computer device with application development function.

[0088] like Figure 7 As shown, the photovoltaic engineering design optimization device includes: a design parameter determination module 310 , a simulation model determination module 320 and an engineering optimization module 330 .

[0089] Among them, the design parameter determination module 310 is used to obtain the power generation information of the target photovoltaic project and determine the array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio and power generation correction coefficient; the simulation model determination module 320 is used to determine the engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters; the engineering optimization module 330 is used to optimize the target engineering parameters in the target photovoltaic project based on the engineering simulation model to realize the optimization process of the target photovoltaic project.

[0090] The technical solution provided by the embodiment of the present invention obtains the power generation information of the target photovoltaic project and determines the array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio and power generation correction coefficient; based on the power generation information and the array design parameters, the engineering simulation model corresponding to the target photovoltaic project is determined; based on the engineering simulation model, the target engineering parameters in the target photovoltaic project are optimized to achieve the optimization process of the target photovoltaic project. The technical solution of the embodiment of the present invention solves the problems of the prior art such as the long design cycle, high design difficulty and insufficient design accuracy of the photovoltaic system, and can propose a standard optimization method for the photovoltaic engineering design scheme, which can provide data support for the early investment decision of the photovoltaic project, improve the design efficiency of the photovoltaic system, reduce the operation risk and enhance the market competitiveness.

[0091] In an optional embodiment, the design parameter determination module 310 includes: a component spacing determination unit, which is used to: obtain the lighting parameter information of the location of the target photovoltaic project, and the component arrangement information of the photovoltaic components in the target photovoltaic project, determine the minimum component spacing between the photovoltaic components, and use the minimum component spacing as the component spacing corresponding to the target photovoltaic project.

[0092] In an optional embodiment, the installed capacity determination module 310 includes: a component spacing determination unit, used to: determine the occupied area of ​​a single photovoltaic component based on the component spacing and component parameter information of the photovoltaic components in the target photovoltaic project; obtain the site available area corresponding to the target photovoltaic project, and determine the installed capacity according to the occupied area of ​​the single photovoltaic component and the site available area.

[0093] In an optional embodiment, the simulation model determination module 320 is specifically used to: display a model component list on a preset interface when a model trigger instruction is received; determine a target photovoltaic component from the model component list when a component interaction instruction is received; and establish an association relationship between the target photovoltaic components to obtain the initial simulation model when a component arrangement instruction is received.

[0094] In an optional embodiment, the engineering optimization module 330 includes: an inverter quantity optimization unit, which is used to: based on the engineering simulation model, with a preset capacity ratio range and the total price of the inverter as constraints, and with the number of inverters as the target engineering parameter for optimization, determine the target number of inverters.

[0095] In an optional embodiment, the model components in the model component list include at least: grounding device, monitoring device, current transformer, cable head, plug and socket, solar radiation component, photovoltaic component, inverter, junction box, well point, transformer, distribution cabinet, fuse, circuit breaker, isolating switch and surge protector.

[0096] The photovoltaic engineering design optimization device provided in the embodiment of the present invention can execute the photovoltaic engineering design optimization method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0097] Figure 8 A schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Figure 8 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 8 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention. The computer device 12 can be any terminal device with computing capability and can be configured in the photovoltaic engineering design optimization device.

[0098] like Figure 8 As shown, the computer device 12 is in the form of a general-purpose computing device. The components of the computer device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that connects various system components (including the system memory 28 and the processing unit 16).

[0099] The bus 18 may be 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. For 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.

[0100] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0101] 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 32. The computer device 12 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 8 not shown, usually called a "hard drive"). Although Figure 8 Not shown in the figure, 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 invention.

[0102] 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.

[0103] The computer device 12 may also communicate with one or more external devices 14 (e.g., keyboards, pointing devices, displays 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., network cards, modems, etc.). Such communication may be performed through an input / output (I / O) interface 22. Furthermore, the computer device 12 may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter 20. Figure 8 As shown, the network adapter 20 communicates with other modules of the computer device 12 via the bus 18. It should be understood that although Figure 8 Not shown, other hardware and / or software modules may be used in conjunction with computer device 12, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0104] The processing unit 16 executes various functional applications and data processing by running the program stored in the system memory 28, for example, implementing the photovoltaic engineering design optimization method provided in the embodiment of the present invention, the method comprising:

[0105] Obtain power generation information of a target photovoltaic project, and determine array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio, and power generation correction factor; based on the power generation information and the array design parameters, determine an engineering simulation model corresponding to the target photovoltaic project; based on the engineering simulation model, optimize target engineering parameters in the target photovoltaic project to achieve an optimization process for the target photovoltaic project.

[0106] This embodiment provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the photovoltaic engineering design optimization method provided in any embodiment of the present invention is implemented, including:

[0107] Obtain power generation information of a target photovoltaic project, and determine array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio, and power generation correction factor; based on the power generation information and the array design parameters, determine an engineering simulation model corresponding to the target photovoltaic project; based on the engineering simulation model, optimize target engineering parameters in the target photovoltaic project to achieve an optimization process for the target photovoltaic project.

[0108] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it.

[0109] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, which carry computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0110] The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0111] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or combinations thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0112] It should be understood by those skilled in the art that the modules or steps of the present invention described above can be implemented by a general-purpose 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 invention is not limited to any specific combination of hardware and software.

[0113] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention 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 invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A photovoltaic engineering design optimization method, characterized in that: include: Acquire power generation information of a target photovoltaic project, and determine array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio, and power generation correction coefficient; Determining an engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters; Based on the engineering simulation model, target engineering parameters in the target photovoltaic project are optimized to achieve an optimization process for the target photovoltaic project.

2. The method according to claim 1, characterized in that: The determining of the component spacing corresponding to the target photovoltaic project includes: The illumination parameter information of the location of the target photovoltaic project and the component arrangement information of the photovoltaic components in the target photovoltaic project are obtained, the minimum component spacing between the photovoltaic components is determined, and the minimum component spacing is used as the component spacing corresponding to the target photovoltaic project.

3. The method according to claim 1, characterized in that The step of determining the installed capacity corresponding to the target photovoltaic project includes: Determining an occupied area of ​​a single photovoltaic module based on the module spacing and the module parameter information of the photovoltaic modules in the target photovoltaic project; The available site area corresponding to the target photovoltaic project is obtained, and the installed capacity is determined according to the occupied area of ​​the single photovoltaic module and the available site area.

4. The method according to claim 1, characterized in that The step of determining the engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters includes: Upon receiving the model building instruction, building an initial simulation model based on the model building instruction; Based on the power generation information and the array design parameters, the working parameters and posture parameters of the photovoltaic components in the initial simulation model are adjusted to obtain the engineering simulation model.

5. The method according to claim 4, characterized in that The constructing of the initial simulation model based on the model construction instruction comprises: When a model trigger instruction is received, a model component list is displayed on a preset interface; In case of receiving the component interaction instruction, determining a target photovoltaic component from the model component list; When the component arrangement instruction is received, an association relationship between the target photovoltaic components is established to obtain the initial simulation model.

6. The method according to claim 1, characterized in that Optimizing target engineering parameters in the target photovoltaic project based on the engineering simulation model includes: Based on the engineering simulation model, with the preset capacity ratio range and the total price of the inverter as constraints, the number of inverters is used as the target engineering parameter for optimization to determine the target number of inverters.

7. The method according to claim 5, characterized in that The model components in the model component list include at least: grounding device, monitoring device, current transformer, cable head, plug and socket, solar radiation component, photovoltaic component, inverter, junction box, well point, transformer, distribution cabinet, fuse, circuit breaker, disconnector and surge protector.

8. A photovoltaic engineering design optimization device, characterized in that: The device comprises: A design parameter determination module, used to obtain power generation information of a target photovoltaic project and determine array design parameters corresponding to the target photovoltaic project; wherein the array design parameters include: at least one of component spacing, installed capacity, capacity ratio and power generation correction coefficient; A simulation model determination module, used to determine an engineering simulation model corresponding to the target photovoltaic project based on the power generation information and the array design parameters; The engineering optimization module is used to optimize the target engineering parameters in the target photovoltaic project based on the engineering simulation model to achieve the optimization process of the target photovoltaic project.

9. A computer device, characterized in that: The computer device comprises: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the photovoltaic engineering design optimization method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the photovoltaic engineering design optimization method as described in any one of claims 1 to 7 is implemented.

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