Photovoltaic project income measuring and calculating method and device, computer equipment and storage medium

Abstract

The embodiment of the invention discloses a profit measuring and calculating method and device of a photovoltaic project, computer equipment and a storage medium. The method comprises the following steps: acquiring an installation address corresponding to a target photovoltaic project and an installable photovoltaic area; determining a target photovoltaic capacity and a target photovoltaic power generation curve corresponding to the target photovoltaic project according to a target standardized power generation curve corresponding to the installation address and the installable photovoltaic area; determining a target consumption rate calculation rule according to the data type of the target power consumption data; based on a target consumption rate calculation rule, determining a target consumption rate according to the target power consumption data and the target photovoltaic power generation curve; obtaining photovoltaic project core parameters corresponding to the target photovoltaic project; and according to the photovoltaic project core parameters and a preset multi-target economic optimization evaluation model, determining an income measurement and calculation result of the target photovoltaic project. According to the scheme provided by the embodiment of the invention, the speed of photovoltaic project income measurement and calculation can be improved, and the photovoltaic project income measurement and calculation error can be reduced.

Description

Technical Field

[0001] This application relates to the field of photovoltaic project technology, and in particular to methods, apparatus, computer equipment and storage media for calculating the revenue of photovoltaic projects. Background Technology

[0002] As the global energy structure shifts towards clean energy, photovoltaic (PV) projects have become one of the core areas of new energy investment due to their advantages such as being renewable, low-pollution, and widely distributed. The profitability calculation of PV projects is a crucial step in investment decision-making and feasibility analysis; its accuracy and efficiency directly determine the scientific validity of the project's investment value assessment, and are of great significance for reducing investment risks and optimizing resource allocation.

[0003] Existing methods for calculating the revenue of photovoltaic projects heavily rely on manual processes in data collection, model calculation, and report generation, resulting in slow response times and difficulty in meeting the market's need for rapid decision-making. Furthermore, existing methods for calculating the revenue of photovoltaic projects are limited by data completeness in core aspects such as power generation forecasting and grid connection rate calculation. Because these methods require extensive manual data collection, they are prone to lacking calculation parameters. In scenarios where complete calculation parameters are lacking, the calculation error of photovoltaic project revenue is relatively large.

[0004] There is an urgent need for a method to improve the speed of revenue calculation for photovoltaic projects and reduce the error in revenue calculation. Summary of the Invention

[0005] This application provides a method, apparatus, computer equipment, and storage medium for calculating the revenue of photovoltaic projects, which can improve the speed of revenue calculation and reduce the error in revenue calculation.

[0006] In a first aspect, embodiments of this application provide a method for calculating the revenue of a photovoltaic project, which includes: Obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project; Based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area, determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project; The calculation rules for the target absorption rate are determined based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; Based on the target absorption rate calculation rules, the target absorption rate is determined according to the target electricity consumption data and the target photovoltaic power generation curve. Obtain the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target grid connection rate, the photovoltaic unit investment cost, the project operation period, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The revenue calculation results of the target photovoltaic project are determined based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

[0007] In some embodiments, determining the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area includes: The target photovoltaic capacity is determined based on the installable photovoltaic area and the preset unit area capacity coefficient; The target standardized power generation curve corresponding to the installation address is determined from multiple preset standardized power generation curves corresponding to different regions. The target photovoltaic power generation curve is determined based on the installable photovoltaic area, the target standardized power generation curve, the preset first-year degradation rate, and the preset subsequent annual degradation rate.

[0008] In some embodiments, determining the target photovoltaic power generation curve based on the installable photovoltaic area, the target standardized power generation curve, a preset first-year degradation rate, and a preset subsequent annual degradation rate includes: The area of ​​the photovoltaic modules is determined based on the installable photovoltaic area and the preset photovoltaic module layout rules; The initial photovoltaic power generation curve is determined based on the target standardized power generation curve, the preset first-year degradation rate and the preset subsequent annual degradation rate, the photovoltaic module area, the capacity ratio corresponding to the target photovoltaic project, the inverter efficiency, and the photovoltaic system efficiency. The initial photovoltaic power generation curve is adjusted according to the environmental factors corresponding to the installation address to obtain the target photovoltaic power generation curve.

[0009] In some embodiments, determining the target grid connection rate based on the target power consumption data and the target photovoltaic power generation curve according to the target grid connection rate calculation rule includes: When the target absorption rate calculation rule is a finite data calculation rule, the target absorption rate is determined based on the target photovoltaic power generation curve, target electricity consumption data, electricity consumption patterns during holidays and non-holiday periods; When the target absorption rate calculation rule is a complete data calculation rule, the project load curve is generated based on the target electricity consumption data; The project load curve and the target photovoltaic power generation curve are time-aligned, and the target absorption rate is determined based on the aligned project load curve and the target photovoltaic power generation curve.

[0010] In some embodiments, the aligned project load curve and the target photovoltaic power generation curve include multiple curve segments; determining the target grid integration rate based on the aligned project load curve and the target photovoltaic power generation curve includes: Obtain the minimum power consumption and minimum power generation within each curve segment. The minimum power consumption is obtained from the corresponding curve segment of the project load curve, and the minimum power generation is obtained from the corresponding curve segment of the target photovoltaic power generation curve. The target absorption rate is determined based on the minimum electricity consumption and the minimum power generation corresponding to each of the curve segments.

[0011] In some embodiments, determining the revenue calculation result of the target photovoltaic project based on the core parameters of the photovoltaic project and a preset multi-objective economic optimization evaluation model includes: The target economic optimization evaluation model is constructed with the objectives of maximizing the internal rate of return, minimizing the cost per kilowatt-hour, and minimizing the investment payback period. The core parameters of the photovoltaic project are input into the target economic optimization evaluation model, and the Pareto optimal solution set is solved using the NSGA-III algorithm to obtain the revenue calculation results.

[0012] In some embodiments, after determining the revenue calculation results of the target photovoltaic project based on the core parameters of the photovoltaic project and a preset multi-objective economic optimization evaluation model, the method further includes: Multiple preset sensitive factors are simulated for fluctuations of various magnitudes. The sensitivity coefficients of each of the preset sensitive factors to the core economic indicators are automatically calculated and ranked. The core economic indicators include the internal rate of return, the cost per kilowatt-hour, and the investment payback period.

[0013] Secondly, embodiments of this application also provide a revenue calculation device for a photovoltaic project, comprising: The transceiver unit is used to obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project. The processing unit is configured to: determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area; determine the target absorption rate calculation rule based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; and determine the target absorption rate based on the target absorption rate calculation rule, the target electricity consumption data, and the target photovoltaic power generation curve. The transceiver unit is also used to acquire the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target absorption rate, the photovoltaic unit investment cost, the project operating years, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The processing unit is also used to determine the revenue calculation results of the target photovoltaic project based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

[0014] Thirdly, embodiments of this application also provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0015] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, the computer program including program instructions that, when executed by a processor, can implement the above-described method.

[0016] This application provides a method, apparatus, computer equipment, and storage medium for calculating the revenue of photovoltaic (PV) projects. The method includes: obtaining the installation address and installable PV area corresponding to a target PV project; determining the target PV capacity and target PV power generation curve corresponding to the target PV project based on the target standardized power generation curve corresponding to the installation address and the installable PV area; determining a target grid connection rate calculation rule based on the data type of target electricity consumption data, where the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target PV project, and the data type indicates the completeness of the target electricity consumption data; determining the target grid connection rate based on the target grid connection rate calculation rule, according to the target electricity consumption data and the target PV power generation curve; obtaining the core parameters of the PV project corresponding to the target PV project, whereby the core parameters include the target PV capacity, the target PV power generation curve, the target grid connection rate, the PV unit investment cost, the project operating years, the average customer electricity price, the feed-in tariff, the electricity price discount percentage, and the rooftop rental fee; and determining the revenue calculation result of the target PV project based on the core parameters of the PV project and a preset multi-objective economic optimization evaluation model. In this embodiment of the application, when calculating the revenue of a photovoltaic project, a pre-constructed target standardized power generation curve is directly called, avoiding the need for real-time data collection during project calculation and improving the speed of photovoltaic project revenue calculation. In addition, this embodiment of the application can call different absorption rate calculation rules based on the completeness of the target electricity consumption data, reducing the calculation error of the absorption rate, and thus reducing the error in photovoltaic project revenue calculation. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating the revenue calculation method for photovoltaic projects provided in this application embodiment; Figure 2 A schematic diagram of a sub-process of the photovoltaic project revenue calculation method provided in the embodiments of this application; Figure 3 This is another schematic diagram of a sub-process of the photovoltaic project revenue calculation method provided in the embodiments of this application; Figure 4 A schematic block diagram of a photovoltaic project revenue calculation device provided in the embodiments of this application; Figure 5 A schematic block diagram of a computer device provided in an embodiment of this application. Detailed Implementation

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

[0020] It should be understood that, when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

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

[0022] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0023] This application provides a method, apparatus, computer equipment, and storage medium for calculating the revenue of photovoltaic projects.

[0024] The entity executing the revenue calculation method for the photovoltaic project can be the revenue calculation device for the photovoltaic project provided in the embodiments of this application, or a computer device that integrates the revenue calculation device for the photovoltaic project. The revenue calculation device for the photovoltaic project can be implemented in hardware or software. The computer device can be a terminal or a server. The terminal can be a smartphone, tablet computer, handheld computer, or laptop computer, etc.

[0025] Figure 2 This is a flowchart illustrating the revenue calculation method for photovoltaic projects provided in this application. Figure 2 As shown, the method includes the following steps S110-S160.

[0026] S110. Obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project.

[0027] In this embodiment, the installation address and the installable photovoltaic area are information input by the user. The installation address includes the province / city / county, and the installable photovoltaic area is the maximum usable area that meets the conditions for photovoltaic module installation, does not affect the original function of the site, and can ensure the safe and stable operation of the photovoltaic system.

[0028] S120. Based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area, determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project.

[0029] In this embodiment, the target photovoltaic capacity refers to the sum of the rated DC output power of all photovoltaic modules installed in the photovoltaic power generation system corresponding to the target photovoltaic project under standard test conditions. The target photovoltaic power generation curve includes the power generation curve within a preset time period, for example, a curve containing 25 years (calculated from the start date of the project) of photovoltaic power generation data.

[0030] Specifically, in some embodiments, such as Figure 2 As shown, step S120 includes: S1201. Determine the target photovoltaic capacity based on the installable photovoltaic area and the preset unit area capacity coefficient.

[0031] Specifically, the unit area capacity factor is the industry standard unit area capacity factor (100 W / m²). 2 - 200 W / m 2 The target photovoltaic capacity is obtained by applying the formula: target photovoltaic capacity = installable photovoltaic area × capacity coefficient per unit area.

[0032] S1202. Determine the target standardized power generation curve corresponding to the installation address from multiple preset standardized power generation curves corresponding to different regions.

[0033] It should be noted that this application pre-constructs standardized power generation curves for different regions. The target standardized power generation curve is the standardized power generation curve of the region corresponding to the installation address of the current project. In some other embodiments, it is also necessary to obtain the installation conditions of the target photovoltaic project. In this case, it is also necessary to construct standardized power generation curves for different installation conditions for the same region. The target standardized power generation curve is the standardized power generation curve of the installation address and installation conditions corresponding to the target photovoltaic project.

[0034] Specifically, this standardized power generation curve is constructed through the following steps: A nationwide database of photovoltaic resources for all cities, optimized for query efficiency using spatiotemporal indexing technology. The database includes longitude, latitude, and horizontal coordinates. Total solar radiation - daily average irradiance (kWh / m²) 2Photovoltaic power generation curves are constructed using data such as daily output and system efficiency (e.g., 15 minutes / 60 minutes as a test point).

[0035] By pre-stored historical data and standardized power generation curves, a "data-as-calculation" support system is constructed. This design can directly call the pre-calculated results (i.e., directly call the power generation at each time point in the standardized power generation curve), avoiding real-time data collection and complex model calculations during project measurement, and significantly improving the response speed of subsequent photovoltaic project evaluation.

[0036] Regarding data integrity, this embodiment ensures the accuracy of basic parameters through cross-validation of multi-source data, while the standardized curve provides a unified performance reference benchmark for photovoltaic systems in different regions and under different installation conditions, providing a reliable data foundation for rapid calculation.

[0037] Among them, the core of the database of standardized power generation curves includes: (1) multi-source data fusion (dual verification of publicly available data from the National Meteorological Administration and measured data from power plants (e.g., taking the average of the two)); (2) efficient query design, with spatiotemporal indexing technology optimizing the retrieval efficiency of geographical and time dimensions; (3) real-time calculation support, with pre-stored standardized power generation curves to achieve "zero real-time calculation" in the calculation process.

[0038] S1203. Determine the target photovoltaic power generation curve based on the installable photovoltaic area, the target standardized power generation curve, the preset first-year degradation rate, and the preset subsequent annual degradation rate.

[0039] In this embodiment, the photovoltaic module area is determined based on the installable photovoltaic area and the preset photovoltaic module layout rules; the initial photovoltaic power generation curve is determined based on the target standardized power generation curve, the preset first-year degradation rate and the preset subsequent annual degradation rate, the photovoltaic module area, the capacity ratio corresponding to the target photovoltaic project, the inverter efficiency, and the photovoltaic system efficiency; the initial photovoltaic power generation curve is adjusted according to the environmental factors corresponding to the installation address to obtain the target photovoltaic power generation curve.

[0040] The photovoltaic module layout rules indicate the ratio between the installable photovoltaic area and the photovoltaic module area. The first-year degradation rate can be set to 1% / year, and the subsequent annual degradation rate can be set to 0.4% / year. Then, combined with the basic power generation calculation formula and the target standardized power generation curve, the annual power generation is extrapolated to obtain the target photovoltaic power generation curve corresponding to the target photovoltaic project. The target photovoltaic power generation curve indicates the power generation of the target photovoltaic project within a preset time period (such as 25 years).

[0041] The formula for calculating basic power generation is: E h = A × r × H × η inv × η sys ; Among them, E h The basic power generation per unit time is given by A, where A is the module area (m²). 2 ), r is the volume ratio (e.g., 1.2~1.5), H is the total irradiance of the horizontal plane (kWh / m²). 2 (Taken from typical annual data in the database), η inv For inverter efficiency (e.g., 0.96-0.98), η sys The system efficiency is set to (e.g., 0.75-0.85). After obtaining the basic power generation per unit time, the target photovoltaic power generation curve is adjusted based on the basic power generation per unit time. For example, the value of each point in the basic power generation per unit time is multiplied by the basic power generation per unit time, and then combined with the first year's degradation rate and the subsequent year's degradation rate to generate the target photovoltaic power generation curve (the power generation in the same period of each year is decreasing and conforms to the first year's degradation rate / subsequent year's degradation rate).

[0042] Furthermore, after obtaining the target photovoltaic power generation curve, a 25-year annual power generation data table and a cumulative degradation trend chart can be output. The obtained data can be directly connected to the economic assessment module for revenue calculation.

[0043] S130. Determine the target absorption rate calculation rule according to the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customer of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data.

[0044] Specifically, this embodiment pre-sets finite data calculation rules and complete data calculation rules. The data type corresponding to the finite data calculation rules is a finite data type, for example, the target electricity consumption data is a monthly electricity bill; the data corresponding to the complete data calculation rules is a complete data type, for example, the target electricity consumption data is a load curve with high resolution.

[0045] S140. Based on the target absorption rate calculation rule, determine the target absorption rate according to the target electricity consumption data and the target photovoltaic power generation curve.

[0046] Specifically, in some embodiments, such as Figure 3 As shown, step S140 includes: S1401. When the target absorption rate calculation rule is a finite data calculation rule, the target absorption rate is determined according to the target photovoltaic power generation curve, target electricity consumption data, electricity consumption patterns during holidays and non-holiday periods.

[0047] Among them, the electricity consumption patterns during holidays and non-holiday periods can be either default patterns or patterns customized according to customer preferences.

[0048] Specifically, this embodiment uses a core algorithm of "time-period electricity consumption ratio × monthly electricity consumption" to break down photovoltaic time-period electricity consumption and embeds a holiday rule correction mechanism—distinguishing between the differences in photovoltaic time-period electricity consumption ratios on holidays and non-holidays—to achieve absorption rate estimation when there is no load curve. This method only requires input of photovoltaic power generation time, holiday rest rules, time-period electricity consumption ratio, and total monthly electricity consumption to quickly solve the problem. A three-level algorithm system of "data-driven prediction - intelligent scenario switching - dynamic error correction" is constructed. In addition, for scenarios with limited data, an innovative LSTM short-term load forecasting model is integrated to compensate for insufficient data through historical electricity consumption pattern mining.

[0049] S1402. When the target absorption rate calculation rule is a complete data calculation rule, the project load curve is generated based on the target electricity consumption data.

[0050] S1403. Perform time alignment processing on the project load curve and the target photovoltaic power generation curve, and determine the target absorption rate based on the aligned project load curve and the target photovoltaic power generation curve.

[0051] The aligned project load curve and the target photovoltaic power generation curve include multiple curve segments. Determining the target absorption rate based on the aligned project load curve and the target photovoltaic power generation curve includes: obtaining the minimum electricity consumption and minimum power generation within each curve segment, wherein the minimum electricity consumption is obtained from the corresponding curve segment of the project load curve, and the minimum power generation is obtained from the corresponding curve segment of the target photovoltaic power generation curve; and determining the target absorption rate based on the minimum electricity consumption and minimum power generation corresponding to each curve segment.

[0052] Specifically, the target electricity consumption data can be data that can generate a project load curve, i.e., continuous electricity consumption data. When the project has a high-resolution load curve, a time-period matching strategy is adopted: import the project load curve at the 15-minute or 60-minute level, align it with the photovoltaic power generation curve of the same granularity in the database on the time axis, obtain the absorbable photovoltaic load by vectorizing the calculation of the min(project electricity load, photovoltaic power generation load) function, and finally calculate it accurately according to the formula "absorption rate = absorbable load / photovoltaic power generation load".

[0053] Meanwhile, both scenarios incorporate a Bayesian error correction module to improve prediction accuracy across all scenarios.

[0054] Bayesian error correction: Posterior(R) ∝ Likelihood(R|Observations) × Prior(R); The prior probability is updated by monthly actual consumption data, and the prediction bias is dynamically adjusted.

[0055] This embodiment achieves full coverage from complete data to extremely limited scenarios through scenario-based algorithm switching, addressing the industry pain point of traditional calculation methods relying on complete load data, and significantly improving engineering applicability while ensuring calculation accuracy. By introducing a Bayesian learning process, the prediction error gradually decreases with increasing runtime.

[0056] S150. Obtain the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target absorption rate, the photovoltaic unit investment cost, the project operation period, the average customer electricity price, the grid connection price, the electricity price discount ratio, and the rooftop rental.

[0057] Specifically, this embodiment provides a photovoltaic project parameter intelligent input and management system adapted to multiple scenarios, which inputs the aforementioned core parameters of photovoltaic projects.

[0058] Furthermore, the system establishes a two-tier parameter classification system of "mandatory + optional", which can flexibly adapt to the personalized needs of projects of different regions and scales, thereby reducing the threshold for basic data entry and meeting the requirements for refined modeling in complex scenarios.

[0059] The core parameters include the target photovoltaic capacity (calculated using the results of the aforementioned steps), the target photovoltaic power generation curve (calculated using the results of the aforementioned steps), the target grid integration rate (calculated using the results of the aforementioned steps), the photovoltaic unit investment cost, the project's operating life, the average customer electricity price, the grid connection price, the electricity price discount percentage, and the rooftop rental fee. All of these data must be entered to ensure the integrity of the core data.

[0060] The auxiliary parameters are set with built-in industry default values, such as annual operation and maintenance costs (e.g., the average operation and maintenance cost of photovoltaic projects is 0.04 yuan / W / year), insurance premiums, inflation rate, photovoltaic degradation rate (first year and subsequent years), failure rate, depreciation period, various taxes (value-added tax, urban construction tax, education surcharge, etc.), equity ratio, loan term, loan interest rate and repayment method, etc., which users can adjust according to their actual needs.

[0061] S160. Determine the revenue calculation results of the target photovoltaic project based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

[0062] The multi-objective economic optimization evaluation model in this embodiment incorporates algorithmic formulas for various indicators, including project operating revenue, operating costs, customer revenue, taxes and surcharges, net present value, internal rate of return on total investment, internal rate of return on equity, payback period, and other indicators. These indicators are calculated based on the core parameters of the photovoltaic project (and built-in industry default values) and the corresponding algorithmic formulas. Then, the multi-objective optimization model in the multi-objective economic optimization evaluation model generates revenue calculation results based on the calculated indicators. In this embodiment, the objective economic optimization evaluation model is constructed with the goals of maximizing the internal rate of return, minimizing the cost per kilowatt-hour, and minimizing the investment payback period. The core parameters of the photovoltaic project are input into the objective economic optimization evaluation model, and the Pareto optimal solution set is solved using the NSGA-Ⅲ algorithm to obtain the revenue calculation results.

[0063] This embodiment introduces the NSGA-III photovoltaic project optimization algorithm to construct a three-objective optimization model centered on financial benefit (IRR), investment risk (payback period), and cost control (levelized cost of electricity). An improved NSGA-III algorithm is used to solve for the Pareto optimal solution set. IRR, payback period, and levelized cost of electricity are optimized simultaneously. The optimal solution is directly integrated into the financial analysis module, which can automatically generate key charts and graphs for the feasibility study report.

[0064] The multi-objective function preset in this multi-objective economic optimization evaluation model is: min f(x,t)={f1(x,t),f2(x,t),…f M (x,t)}; g(x,t)≤0,i=1,2,…,p; h(x,t)=0,j=1,2,…q; min: The optimization direction is (if the goal needs to be maximized, it can be transformed into minimizing its opposite, such as maximizing IRR → minimizing -IRR). f(x,t) is a global multi-objective function set, containing M independent objective functions f1(x,t) to f M (x,t); x is the decision variable (adjustable core parameters of photovoltaic projects), such as "installable area, capacity ratio, unit investment cost, electricity price discount ratio" and other optimizable parameters; t represents a state variable / time variable (in photovoltaic projects, state parameters that change or remain fixed over time, such as "project operating years, 25-year decay cycle, and irradiance time series"). Overall meaning: By adjusting the decision variable x and combining it with the state variable t, we can simultaneously minimize M objective functions (adapting to multi-objective balance optimization).

[0065] g(x,t) includes p inequality constraints that limit the range of values ​​for decision variable x and state variable t, ensuring that the optimal solution is within the feasible range of actual engineering, policy, and economic considerations (without exceeding the boundaries). h(x,t) includes q equality constraints, which force the decision variable x and the state variable t to satisfy a strict quantitative relationship (they must be exactly equal to ensure that the scheme conforms to physical laws or fixed rules).

[0066] First, the population is initialized by randomly generating an initial set of solutions that meet the constraints. Then, the fitness value of each individual is calculated, and non-dominated solutions are sorted to identify the non-dominated solutions in the current population. Next, an elite retention strategy is implemented, directly saving the non-dominated solutions to the next generation. Adaptive crossover and mutation operations are performed on the remaining individuals to generate new offspring. This process is repeated until the termination condition is met, and finally, the Pareto optimal solution set is output.

[0067] Furthermore, after obtaining the above-mentioned indicators such as project operating revenue, operating costs, customer revenue, taxes and surcharges, net present value, internal rate of return on total investment, internal rate of return on equity, payback period, and payback period, this embodiment also automatically generates key financial documents such as the main economic indicators table, customer revenue table, total investment profit table, equity profit table, total investment cash flow table, equity cash flow table, and loan principal and interest repayment table, which mainly comprehensively cover the entire process analysis needs from investment estimation to profit distribution.

[0068] Furthermore, the reporting system in this embodiment also adopts a data linkage update mechanism. When basic parameters such as electricity price and power generation are adjusted, the corresponding profit indicators and cash flow statement data will be updated synchronously in real time. This effectively solves the pain points of poor data consistency and low update efficiency in the traditional manual compilation mode, ensuring the accuracy and timeliness of financial analysis. The main economic indicators table covers key parameters such as photovoltaic installed capacity, average annual power generation, static / dynamic total investment, total revenue, total profit, net profit, internal rate of return, net present value, and payback period, providing comprehensive data support for project decision-making.

[0069] Furthermore, this embodiment also performs multi-amplitude fluctuation simulation on multiple preset sensitive factors, automatically calculates and sorts the sensitivity coefficients of each of the sensitive factors to the core economic indicators, including the internal rate of return, the cost per kilowatt-hour, and the investment payback period.

[0070] Specifically, this step is used to assess the impact of fluctuations in key parameters on the economic feasibility of the project. It includes built-in sensitive factors such as total investment, electricity price, operation and maintenance, and project duration, and automatically calculates them based on ±20%, ±10%, and ±5% (amplitude fluctuations). The sensitive factors are then ranked according to their sensitivity coefficients, and a standardized table is output. The sensitivity coefficient is calculated as (ΔY / Y) / (ΔX / X), where ΔY is the change in the dependent variable, Y is the original value of the dependent variable, ΔX is the change in the independent variable, and X is the original value of the independent variable.

[0071] To improve analysis efficiency and result usability, this embodiment integrates a fast sorting algorithm to sort the absolute values ​​of sensitivity coefficients, automatically generating a standardized analysis table containing factor names, magnitudes of change, rate of change of indicators, and sensitivity coefficients. This design achieves fully automated calculation and sorting of multiple factors and magnitudes, reducing sensitivity analysis that traditionally takes hours to complete to minutes. It also supports parallel calculation of 10+ sensitivity factors, and the output standardized table can be directly used as parameter input for risk warning models, significantly improving the scientific rigor and timeliness of photovoltaic project investment decisions.

[0072] In summary, the embodiments of this application directly call the pre-constructed target standardized power generation curve when calculating the revenue of photovoltaic projects, avoiding the need for real-time collection of relevant data during project calculation, thus improving the speed of photovoltaic project revenue calculation. In addition, the embodiments of this application can call different absorption rate calculation rules based on the completeness of the target electricity consumption data, reducing the calculation error of the absorption rate, thereby reducing the error in photovoltaic project revenue calculation.

[0073] Figure 4 This is a schematic block diagram of a photovoltaic project revenue calculation device provided in an embodiment of this application. Figure 4 As shown, corresponding to the above-described method for calculating the revenue of photovoltaic projects, this application also provides a photovoltaic project revenue calculation device 400. This photovoltaic project revenue calculation device 400 includes a unit for executing the above-described method for calculating the revenue of photovoltaic projects, and can be configured in a desktop computer, tablet computer, laptop computer, or other terminal. For details, please refer to... Figure 4 The revenue calculation device 400 for the photovoltaic project includes a transceiver unit 401 and a processing unit 402, wherein: The transceiver unit 401 is used to obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project. Processing unit 402 is configured to: determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area; determine the target absorption rate calculation rule based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customer of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; and determine the target absorption rate based on the target absorption rate calculation rule, the target electricity consumption data, and the target photovoltaic power generation curve. The transceiver unit 401 is also used to obtain the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target absorption rate, the photovoltaic unit investment cost, the project operation period, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The processing unit 402 is also used to determine the revenue calculation results of the target photovoltaic project based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

[0074] In some embodiments, when the processing unit 402 performs the step of determining the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area, it is specifically used for: The target photovoltaic capacity is determined based on the installable photovoltaic area and the preset unit area capacity coefficient; The target standardized power generation curve corresponding to the installation address is determined from multiple preset standardized power generation curves corresponding to different regions. The target photovoltaic power generation curve is determined based on the installable photovoltaic area, the target standardized power generation curve, the preset first-year degradation rate, and the preset subsequent annual degradation rate.

[0075] In some embodiments, when the processing unit 402 performs the step of determining the target photovoltaic power generation curve based on the installable photovoltaic area, the target standardized power generation curve, the preset first-year degradation rate, and the preset subsequent annual degradation rate, it is specifically used for: The area of ​​the photovoltaic modules is determined based on the installable photovoltaic area and the preset photovoltaic module layout rules; The initial photovoltaic power generation curve is determined based on the target standardized power generation curve, the preset first-year degradation rate and the preset subsequent annual degradation rate, the photovoltaic module area, the capacity ratio corresponding to the target photovoltaic project, the inverter efficiency, and the photovoltaic system efficiency. The initial photovoltaic power generation curve is adjusted according to the environmental factors corresponding to the installation address to obtain the target photovoltaic power generation curve.

[0076] In some embodiments, when the processing unit 402 executes the step of determining the target grid connection rate based on the target grid connection rate calculation rule, according to the target electricity consumption data and the target photovoltaic power generation curve, it is specifically used for: When the target absorption rate calculation rule is a finite data calculation rule, the target absorption rate is determined based on the target photovoltaic power generation curve, target electricity consumption data, electricity consumption patterns during holidays and non-holiday periods; When the target absorption rate calculation rule is a complete data calculation rule, the project load curve is generated based on the target electricity consumption data; The project load curve and the target photovoltaic power generation curve are time-aligned, and the target absorption rate is determined based on the aligned project load curve and the target photovoltaic power generation curve.

[0077] In some embodiments, the aligned project load curve and the target photovoltaic power generation curve include multiple curve segments; when the processing unit 402 performs the step of determining the target absorption rate based on the aligned project load curve and the target photovoltaic power generation curve, it is specifically used for: Obtain the minimum power consumption and minimum power generation within each curve segment. The minimum power consumption is obtained from the corresponding curve segment of the project load curve, and the minimum power generation is obtained from the corresponding curve segment of the target photovoltaic power generation curve. The target absorption rate is determined based on the minimum electricity consumption and the minimum power generation corresponding to each of the curve segments.

[0078] In some embodiments, when the processing unit 402 executes the step of determining the revenue calculation result of the target photovoltaic project based on the core parameters of the photovoltaic project and a preset multi-objective economic optimization evaluation model, it is specifically used for: The target economic optimization evaluation model is constructed with the objectives of maximizing the internal rate of return, minimizing the cost per kilowatt-hour, and minimizing the investment payback period. The core parameters of the photovoltaic project are input into the target economic optimization evaluation model, and the Pareto optimal solution set is solved using the NSGA-Ⅲ algorithm to obtain the revenue calculation results.

[0079] In some embodiments, after the processing unit 402 executes the step of determining the revenue calculation result of the target photovoltaic project based on the core parameters of the photovoltaic project and a preset multi-objective economic optimization evaluation model, it is further configured to: Multiple preset sensitive factors are simulated for fluctuations of various magnitudes. The sensitivity coefficients of each of the preset sensitive factors to the core economic indicators are automatically calculated and ranked. The core economic indicators include the internal rate of return, the cost per kilowatt-hour, and the investment payback period.

[0080] In summary, the embodiments of this application directly call the pre-constructed target standardized power generation curve when calculating the revenue of photovoltaic projects, avoiding the need for real-time collection of relevant data during project calculation, thus improving the speed of photovoltaic project revenue calculation. In addition, the embodiments of this application can call different absorption rate calculation rules based on the completeness of the target electricity consumption data, reducing the calculation error of the absorption rate, thereby reducing the error in photovoltaic project revenue calculation.

[0081] It should be noted that those skilled in the art can clearly understand that the specific implementation process of the above-mentioned photovoltaic project revenue calculation device and each unit can be referred to the corresponding description in the foregoing method embodiments. For the sake of convenience and brevity, it will not be repeated here.

[0082] The revenue calculation device for the aforementioned photovoltaic project can be implemented as a computer program, which can be used in, for example... Figure 5 It runs on the computer device shown.

[0083] Please see Figure 5 , Figure 5 This is a schematic block diagram of a computer device provided in an embodiment of this application. The computer device 500 can be a terminal or a server. The terminal can be an electronic device with communication functions, such as a smartphone, tablet, laptop, desktop computer, personal digital assistant, or wearable device. The server can be a standalone server or a server cluster composed of multiple servers.

[0084] See Figure 5 The computer device 500 includes a processor 502, a memory, and a network interface 505 connected via a system bus 501. The memory may include a non-volatile storage medium 503 and internal memory 504.

[0085] The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032 includes program instructions that, when executed, cause the processor 502 to perform a method for calculating the revenue of a photovoltaic project.

[0086] The processor 502 provides computing and control capabilities to support the operation of the entire computer device 500.

[0087] The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503. When the computer program 5032 is executed by the processor 502, the processor 502 can execute a method for calculating the revenue of a photovoltaic project.

[0088] This network interface 505 is used for network communication with other devices. Those skilled in the art will understand that... Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device 500 to which the present application is applied. The specific computer device 500 may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0089] The processor 502 is used to run a computer program 5032 stored in the memory to perform the following steps: Obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project; Based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area, determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project; The calculation rules for the target absorption rate are determined based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; Based on the target absorption rate calculation rules, the target absorption rate is determined according to the target electricity consumption data and the target photovoltaic power generation curve. Obtain the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target grid connection rate, the photovoltaic unit investment cost, the project operation period, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The revenue calculation results of the target photovoltaic project are determined based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

[0090] It should be understood that in the embodiments of this application, the processor 502 may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0091] It will be understood by those skilled in the art that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the computer system to implement the process steps of the embodiments of the above methods.

[0092] Therefore, this application also provides a storage medium. This storage medium can be a computer-readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. When executed by a processor, the program instructions cause the processor to perform the following steps: Obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project; Based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area, determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project; The calculation rules for the target absorption rate are determined based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; Based on the target absorption rate calculation rules, the target absorption rate is determined according to the target electricity consumption data and the target photovoltaic power generation curve. Obtain the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target grid connection rate, the photovoltaic unit investment cost, the project operation period, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The revenue calculation results of the target photovoltaic project are determined based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

[0093] The storage medium can be any computer-readable storage medium capable of storing program code, such as a USB flash drive, portable hard drive, read-only memory (ROM), magnetic disk, or optical disk.

[0094] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of each unit is merely a logical functional division, and there may be other division methods in actual implementation. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0096] The steps in the methods of this application embodiment can be adjusted, merged, or deleted according to actual needs. The units in the apparatus of this application embodiment can be merged, divided, or deleted according to actual needs. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0097] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a terminal, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0098] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for calculating the revenue of a photovoltaic project, characterized in that, include: Obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project; Based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area, determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project; The calculation rules for the target absorption rate are determined based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; Based on the target absorption rate calculation rules, the target absorption rate is determined according to the target electricity consumption data and the target photovoltaic power generation curve. Obtain the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target grid connection rate, the photovoltaic unit investment cost, the project operation period, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The revenue calculation results of the target photovoltaic project are determined based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

2. The method according to claim 1, characterized in that, The step of determining the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area includes: The target photovoltaic capacity is determined based on the installable photovoltaic area and the preset unit area capacity coefficient; The target standardized power generation curve corresponding to the installation address is determined from multiple preset standardized power generation curves corresponding to different regions. The target photovoltaic power generation curve is determined based on the installable photovoltaic area, the target standardized power generation curve, the preset first-year degradation rate, and the preset subsequent annual degradation rate.

3. The method according to claim 2, characterized in that, The step of determining the target photovoltaic power generation curve based on the installable photovoltaic area, the target standardized power generation curve, the preset first-year degradation rate, and the preset subsequent annual degradation rate includes: The area of ​​the photovoltaic modules is determined based on the installable photovoltaic area and the preset photovoltaic module layout rules; The initial photovoltaic power generation curve is determined based on the target standardized power generation curve, the preset first-year degradation rate and the preset subsequent annual degradation rate, the photovoltaic module area, the capacity ratio corresponding to the target photovoltaic project, the inverter efficiency, and the photovoltaic system efficiency. The initial photovoltaic power generation curve is adjusted according to the environmental factors corresponding to the installation address to obtain the target photovoltaic power generation curve.

4. The method according to claim 1, characterized in that, The determination of the target grid connection rate based on the target grid connection rate calculation rule, according to the target electricity consumption data and the target photovoltaic power generation curve, includes: When the target absorption rate calculation rule is a finite data calculation rule, the target absorption rate is determined based on the target photovoltaic power generation curve, target electricity consumption data, electricity consumption patterns during holidays and non-holiday periods; When the target absorption rate calculation rule is a complete data calculation rule, the project load curve is generated based on the target electricity consumption data; The project load curve and the target photovoltaic power generation curve are time-aligned, and the target absorption rate is determined based on the aligned project load curve and the target photovoltaic power generation curve.

5. The method according to claim 4, characterized in that, The aligned project load curve and the target photovoltaic power generation curve include multiple curve segments; determining the target grid integration rate based on the aligned project load curve and the target photovoltaic power generation curve includes: Obtain the minimum power consumption and minimum power generation within each curve segment. The minimum power consumption is obtained from the corresponding curve segment of the project load curve, and the minimum power generation is obtained from the corresponding curve segment of the target photovoltaic power generation curve. The target absorption rate is determined based on the minimum electricity consumption and the minimum power generation corresponding to each of the curve segments.

6. The method according to claim 1, wherein determining the revenue calculation result of the target photovoltaic project based on the core parameters of the photovoltaic project and a preset multi-objective economic optimization evaluation model includes: The target economic optimization evaluation model is constructed with the objectives of maximizing the internal rate of return, minimizing the cost per kilowatt-hour, and minimizing the investment payback period. The core parameters of the photovoltaic project are input into the target economic optimization evaluation model, and the Pareto optimal solution set is solved using the NSGA-Ⅲ algorithm to obtain the revenue calculation results.

7. The method according to claim 1, characterized in that, After determining the revenue calculation results of the target photovoltaic project based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model, the method further includes: Multiple preset sensitive factors are simulated for fluctuations of various magnitudes. The sensitivity coefficients of each of the preset sensitive factors to the core economic indicators are automatically calculated and ranked. The core economic indicators include the internal rate of return, the cost per kilowatt-hour, and the investment payback period.

8. A revenue calculation device for a photovoltaic project, characterized in that, include: The transceiver unit is used to obtain the installation address and installable photovoltaic area corresponding to the target photovoltaic project. The processing unit is configured to: determine the target photovoltaic capacity and target photovoltaic power generation curve corresponding to the target photovoltaic project based on the target standardized power generation curve corresponding to the installation address and the installable photovoltaic area; determine the target absorption rate calculation rule based on the data type of the target electricity consumption data, wherein the target electricity consumption data is the electricity consumption data corresponding to the target customers of the target photovoltaic project, and the data type indicates the completeness of the target electricity consumption data; and determine the target absorption rate based on the target absorption rate calculation rule, the target electricity consumption data, and the target photovoltaic power generation curve. The transceiver unit is also used to acquire the core parameters of the photovoltaic project corresponding to the target photovoltaic project. The core parameters of the photovoltaic project include the target photovoltaic capacity, the target photovoltaic power generation curve, the target absorption rate, the photovoltaic unit investment cost, the project operating years, the average customer electricity price, the grid connection electricity price, the electricity price discount ratio, and the rooftop rental. The processing unit is also used to determine the revenue calculation results of the target photovoltaic project based on the core parameters of the photovoltaic project and the preset multi-objective economic optimization evaluation model.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the revenue calculation method for the photovoltaic project as described in any one of claims 1-7.

10. A storage medium, characterized in that, The storage medium stores a computer program, which includes program instructions that, when executed by a processor, cause the processor to perform the revenue calculation method for a photovoltaic project as described in any one of claims 1-7.

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