Economic evaluation system and method for full life cycle of photovoltaic project

Abstract

The invention provides an economic evaluation system and method for a full life cycle of a photovoltaic project, and relates to the technical field of photovoltaics. The system comprises a data acquisition module used for acquiring project engineering construction parameters and income driving parameters; the cost prediction module is used for establishing cost models of a construction period and an operation period based on the engineering construction parameters so as to calculate investment cost and operation cost; the income prediction module is used for establishing an income model based on the income driving parameters to calculate investment income; the benefit analysis module is used for establishing a benefit analysis model based on the investment cost, the operation cost and the investment income, and predicting the project full life cycle income by using the benefit analysis model; and the analogue simulation module is used for carrying out analogue simulation on the full-life-cycle income based on the uncertain variables so as to determine the project economy grade according to the economy index obtained through simulation. According to the method, the full-life-cycle model is dynamically constructed, so that project income and risks can be accurately quantified, and project investment decision making is facilitated.

Description

Technical Field

[0001] The present disclosure relates to the field of photovoltaic technology, and in particular to a system and method for evaluating the economic performance of a photovoltaic project over its entire life cycle. Background Art

[0002] The installed capacity of new energy sources such as wind power and photovoltaic power is growing rapidly, and the construction of a new power system based on new energy is accelerating. Taking offshore photovoltaic projects as an example, offshore photovoltaic projects have shown broad development prospects with abundant marine resources and less land occupation requirements. However, the investment and construction of offshore photovoltaic projects face great economic uncertainty, and the cost, income and economic benefit calculation throughout their life cycle has become a key link in investment decision-making.

[0003] At present, the economic benefits of offshore photovoltaic projects are usually calculated statically, lacking quantitative analysis of investment risks. Since the costs and benefits of offshore photovoltaic projects are affected by a variety of uncertain factors, such as construction period, electricity price fluctuations, equipment failure rate, etc., static calculation methods are difficult to truly reflect the economic feasibility of the project, resulting in investment decision-making deviations. Moreover, the relevant technology fails to integrate construction period investment, operation period costs, power generation income and financial indicators, lacks a comprehensive assessment of the entire life cycle of the project, and is difficult to meet the accuracy requirements of project investment evaluation.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the embodiments of the present disclosure is to provide a system and method for economic evaluation of the entire life cycle of a photovoltaic project, thereby at least to a certain extent solving the problem that related technologies lack a comprehensive evaluation of the entire life cycle of a project and are difficult to meet the accuracy requirements of project investment evaluation.

[0006] According to a first aspect of an embodiment of the present disclosure, a system for evaluating the economic performance of a photovoltaic project throughout its life cycle is provided, comprising: Data acquisition module, used to obtain engineering construction parameters and revenue driving parameters of the target photovoltaic project; A cost prediction module, for establishing a construction period investment cost model and an operation and maintenance cost model based on the engineering construction parameters, and using the construction period investment cost model and the operation and maintenance cost model to respectively calculate the investment cost and the operation cost of the target photovoltaic project; A revenue prediction module, used to establish a revenue model based on the revenue driving parameter, and calculate the investment return of the target photovoltaic project using the revenue model; A benefit analysis module, for establishing a benefit analysis model based on the investment cost, operating cost and investment income, and using the benefit analysis model to predict the full life cycle income of the target photovoltaic project; The simulation module is used to simulate the full life cycle benefits of the target photovoltaic project based on preset uncertain variables, obtain the probability distribution of the full life cycle economic indicators, and determine the economic level of the target photovoltaic project according to the probability distribution of the full life cycle economic indicators.

[0007] In an exemplary embodiment of the present disclosure, the engineering construction parameters include investment parameters during the construction period and operation and maintenance parameters during the operation period; the cost prediction module includes: A model building submodule, used to establish a construction period investment cost model based on the construction period investment parameters, and to establish an operation and maintenance cost model based on the operation and maintenance parameters; A cost prediction submodule, used to calculate the investment cost and operation cost of the target photovoltaic project respectively by using the construction period investment cost model and the operation period operation and maintenance cost model; Among them, the investment cost at least includes the photovoltaic area equipment and installation cost, the photovoltaic area construction cost, the substation equipment and installation cost, and the substation construction cost; the operating cost at least includes the photovoltaic power generation cost, fixed asset depreciation cost, equipment repair cost, labor input cost, insurance cost, material loss and operation and maintenance cost.

[0008] In an exemplary embodiment of the present disclosure, the revenue driving parameters include annual grid-connected electricity and grid-connected electricity price; the revenue prediction module includes: An income model building module is used to establish an income model based on the annual grid-connected electricity and the grid-connected electricity price; wherein the original annual power generation is determined according to the installed capacity of the photovoltaic power station, the reference irradiance and the corresponding annual horizontal plane total solar irradiance, and the annual grid-connected electricity is calculated based on the spatial layout correction factor, the component performance correction factor, the operation efficiency correction factor and the original annual power generation; The power generation revenue prediction module is used to calculate the annual power generation sales revenue according to the revenue model, and calculate the annual power generation revenue based on the annual power generation sales revenue, operating costs and taxes.

[0009] In an exemplary embodiment of the present disclosure, the revenue prediction module further includes: The income index calculation module is used to calculate the investment return rate using the annual power generation income, wherein the investment return rate is equal to the proportion of the annual power generation income corresponding to the investment amount.

[0010] In an exemplary embodiment of the present disclosure, the benefit analysis module includes: An analysis model building module is used to establish a benefit analysis model based on the investment cost, operating cost and investment income, wherein the benefit analysis model includes an investment plan and fund raising sub-model, a loan principal and interest payment sub-model, a planned cash flow quantum model, an asset-liability sub-model, a project investment cash flow quantum model, and a project capital cash flow quantum model; The life cycle benefit analysis module is used to calculate the full life cycle benefits of the target photovoltaic project using the benefit analysis model. The full life cycle benefits include the total project investment and total fund raising, the amount of principal and interest to be repaid, the annual accumulated surplus funds, the total assets and total liabilities, the financial internal rate of return, and the investment payback period.

[0011] In an exemplary embodiment of the present disclosure, the preset uncertain variables include operating years, operating costs and sales revenue; the simulation module includes: A distribution model building module, used to build an input variable probability distribution model based on the cost data and revenue data of the benefit analysis model, wherein the input variable probability distribution model includes a uniform distribution of operating years, a normal distribution of operating costs, and a triangular distribution of sales revenue; An uncertainty simulation module, used to perform uncertainty simulation based on the input variable probability distribution model using a Monte Carlo simulation method to obtain a probability distribution of the economic indicators of the entire life cycle; An economic grade determination module is used to determine the economic grade of the target photovoltaic project according to the probability distribution of the full life cycle economic indicators and a preset probability distribution threshold.

[0012] In an exemplary embodiment of the present disclosure, the uncertainty simulation module includes: A sample generation submodule, used for randomly extracting a plurality of random samples from the input variable probability distribution model; The simulation submodule is used to calculate the full life cycle economic indicators corresponding to each random sample, and obtain the probability distribution of the full life cycle economic indicators through multiple simulations.

[0013] In an exemplary embodiment of the present disclosure, the simulation module further includes: A sensitivity analysis submodule, for calculating the sensitivity coefficient corresponding to the life cycle economic index based on the change of each input variable, and determining the sensitivity index from each input variable according to the sensitivity coefficient; The parameter optimization submodule is used to adjust the target parameters in the construction period investment cost model, operation period operation and maintenance cost model and income model according to the probability distribution and sensitivity index of the full life cycle economic indicators.

[0014] According to a second aspect of an embodiment of the present disclosure, a method for economic evaluation of a photovoltaic project throughout its life cycle is provided, comprising: Obtain engineering construction parameters and revenue driving parameters of the target PV project; Based on the engineering construction parameters, a construction period investment cost model and an operation and maintenance cost model are established, and the investment cost and operation cost of the target photovoltaic project are calculated using the construction period investment cost model and the operation and maintenance cost model respectively; Based on the revenue driving parameters, establishing a revenue model, and using the revenue model to calculate the investment return of the target photovoltaic project; Based on the investment cost, operating cost and investment income, a benefit analysis model is established, and the benefit analysis model is used to predict the full life cycle income of the target photovoltaic project; Based on preset uncertain variables, the full life cycle benefits of the target photovoltaic project are simulated to obtain the probability distribution of the full life cycle economic indicators, and the economic level of the target photovoltaic project is determined according to the probability distribution of the full life cycle economic indicators.

[0015] According to a third aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, any step of the method for economic evaluation of the entire life cycle of a photovoltaic project described in the second aspect is implemented.

[0016] According to a fourth aspect of the present disclosure, there is provided an electronic device, including: A processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, any step of the method for economic evaluation of the entire life cycle of a photovoltaic project described in the second aspect is implemented.

[0017] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects: In the economic evaluation system of the photovoltaic project life cycle provided by the exemplary embodiment of the present disclosure, the data acquisition module ensures the accurate acquisition of engineering construction parameters and income driving parameters, and provides basic data support for subsequent calculations. The cost prediction module establishes the investment cost model of the construction period and the operation and maintenance cost model of the operation period based on the engineering construction parameters, thereby calculating the investment cost and the operating cost respectively, so that the economic expenditure of the photovoltaic project can be systematically quantified and predicted. The income prediction module uses the income driving parameters to establish the income model and calculate the investment income, so that the income potential of the project can be clearly evaluated. The benefit analysis module establishes a benefit analysis model based on the investment cost, operating cost and investment income, and predicts the full life cycle income according to the benefit analysis model, thereby providing a reliable basis for investment decisions. The simulation module simulates the full life cycle income through preset uncertain variables, calculates the probability distribution of the full life cycle economic indicators, and determines the economic level based on the indicators, so that investors can have a more comprehensive understanding of the risk-return characteristics of the project. In general, the present disclosure accurately quantifies the project income and risks by dynamically constructing a full life cycle model, which is helpful for project investment decisions.

[0018] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification are used to explain the principles of the present disclosure. Obviously, the accompanying drawings described below are only some embodiments of the present disclosure, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0020] Figure 1 A schematic diagram of the architecture of an economic evaluation system for the entire life cycle of a photovoltaic project in an embodiment of the present disclosure is shown.

[0021] Figure 2 A schematic diagram of a simulation module in an embodiment of the present disclosure is shown.

[0022] Figure 3 A schematic flow chart of a method for economic evaluation of a photovoltaic project throughout its life cycle in an embodiment of the present disclosure is shown.

[0023] Figure 4 A schematic diagram of the structure of an electronic device suitable for implementing the embodiments of the present disclosure is shown.

[0024] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0025] The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit this specification. The singular forms "a", "the" and "the" used in this specification and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0026] It should be understood that although the terms first, second, third, etc. may be used in this specification to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this specification, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0027] Figure 1 The schematic diagram of the architecture of an economic evaluation system for the entire life cycle of a photovoltaic project according to an embodiment of the present disclosure is shown. Figure 1 As shown, the economic evaluation system 100 for the whole life cycle of a photovoltaic project includes a data acquisition module 110, a cost prediction module 120, a revenue prediction module 130, a benefit analysis module 140 and a simulation module 150. Among them, the data acquisition module 110 is used to obtain the engineering construction parameters and revenue driving parameters of the target photovoltaic project. The cost prediction module 120 is used to establish the investment cost model of the construction period and the operation and maintenance cost model of the operation period based on the engineering construction parameters, and use the investment cost model of the construction period and the operation and maintenance cost model of the operation period to calculate the investment cost and operation cost of the target photovoltaic project respectively. The revenue prediction module 130 is used to establish the income model based on the revenue driving parameters, and use the income model to calculate the investment income of the target photovoltaic project. The benefit analysis module 140 is used to establish the benefit analysis model based on the investment cost, operating cost and investment income, and use the benefit analysis model to predict the whole life cycle income of the target photovoltaic project. The simulation module 150 is used to simulate the whole life cycle income of the target photovoltaic project based on the preset uncertain variables, obtain the probability distribution of the whole life cycle economic indicators, and determine the economic level of the target photovoltaic project according to the probability distribution of the whole life cycle economic indicators.

[0028] The present disclosure realizes accurate cost and benefit prediction of the target photovoltaic project from construction to operation by constructing an economic evaluation system for the entire life cycle of the photovoltaic project. Among them, the engineering construction parameters and benefit driving parameters provided by the data acquisition module 110 provide basic data support for subsequent cost prediction, benefit prediction and economic evaluation. The phased modeling of the cost prediction module 120 and the benefit prediction module 130 makes the calculation of investment cost, operating cost and investment income more targeted. The benefit analysis module 140 combines cost and benefit data to improve the scientific nature of economic benefit evaluation. The simulation module 150 optimizes the reliability of economic indicators by introducing uncertainty factors, so that the benefit forecast is more in line with the actual situation. Based on this, the present disclosure improves the accuracy of photovoltaic project investment evaluation, enhances the visualization of economic analysis, and provides more valuable data support for investment decisions.

[0029] In the exemplary implementation of the present disclosure, the target photovoltaic project refers to a photovoltaic power station for solar power generation, which can be a ground photovoltaic power station, a rooftop distributed photovoltaic power station, an offshore photovoltaic power station, etc. Among them, an offshore photovoltaic power station refers to a photovoltaic power generation facility installed in a marine environment, which is suitable for large-scale photovoltaic power generation using marine space resources. Taking a pile-based fixed offshore photovoltaic power station as an example, the photovoltaic components are supported above the water surface by fixing the pile foundation to ensure the stable operation of the photovoltaic power station in the marine environment. The photovoltaic power station uses steel piles, concrete piles or composite piles to fix the photovoltaic bracket on the seabed or offshore area to ensure that the power station has a strong wind and wave resistance in the marine environment. The photovoltaic power station can also adapt to special environmental conditions such as seawater corrosion, high humidity, high wind speed and tidal changes, and enhance the structural durability through anti-corrosion coatings, sacrificial anode protection and salt spray resistant materials. In addition, booster stations, submarine transmission lines and remote monitoring systems are usually configured to achieve stable grid access and remote operation and maintenance management. In addition, due to the restrictions of the offshore environment, the construction process involves marine surveys, pile foundations, floating construction platforms and submarine cable laying, which is more complicated than onshore photovoltaic power stations.

[0030] It is understandable that for different types of photovoltaic power stations, the present disclosure can adapt to investment evaluation requirements in different environments by adjusting the cost prediction model, the revenue prediction model and the simulation parameters.

[0031] In the data acquisition module 110, the engineering construction parameters of the target photovoltaic project collected include photovoltaic area equipment parameters, construction environment parameters, infrastructure parameters, construction cycle data, operation and maintenance demand data, etc., and the revenue-driven parameters include annual power generation data, electricity price data, tax policy data, etc.

[0032] The data acquisition module 110 provides high-precision data support for the cost prediction module 120, the revenue prediction module 130, the benefit analysis module 140 and the simulation module 150 by accurately acquiring the engineering construction parameters and the revenue driving parameters, thereby ensuring that the economic evaluation results of the photovoltaic project over its entire life cycle are more in line with the actual situation.

[0033] Exemplarily, the engineering construction parameters include construction period investment parameters and operation period operation and maintenance parameters. Among them, the construction period investment parameters involve all investments in the target photovoltaic project during the construction phase, including equipment procurement, infrastructure, installation and construction, and supporting facilities. Operation period operation and maintenance parameters involve the continuous investment of the target photovoltaic project during the operation phase, including equipment maintenance, labor costs, depreciation and amortization, etc.

[0034] Accordingly, the cost prediction module 120 is responsible for calculating the investment cost and operating cost based on the investment parameters of the construction period and the operation and maintenance parameters of the operation period. Specifically, the cost prediction module 120 includes a model building submodule and a cost prediction submodule. Among them, the model building submodule is used to establish a construction period investment cost model based on the investment parameters of the construction period, and to establish an operation and maintenance cost model for the operation period based on the operation and maintenance parameters of the operation period, that is, to integrate the scattered cost parameters into a computable mathematical model. The cost prediction submodule is used to use the construction period investment cost model and the operation and maintenance cost model of the operation period to respectively calculate the investment cost and operating cost of the target photovoltaic project, and the investment cost and operating cost together constitute the full life cycle cost.

[0035] Taking the offshore photovoltaic project as an example, the investment cost at least includes the equipment and installation cost of the photovoltaic area, the construction cost of the photovoltaic area, the equipment and installation cost of the booster station, and the construction cost of the booster station. Among them, the equipment and installation cost of the photovoltaic area includes the photovoltaic power generation equipment and installation engineering fee, the convergence and transformation and distribution equipment and installation engineering fee, the collection line material and installation engineering fee, the grounding engineering fee, the system commissioning fee, the optical cable and cable laying engineering fee, and other equipment and installation engineering fees. The construction engineering cost of the photovoltaic area includes the basic engineering fee of the power generation equipment, the basic engineering fee of the convergence and transformation and distribution equipment, the collection line engineering fee and other construction engineering fees. The equipment and installation cost of the booster station includes the transformation and distribution equipment and installation engineering fee of the booster station, the control and protection equipment and installation engineering fee, and other equipment and installation engineering fees. The construction engineering cost of the booster station includes the booster substation engineering fee, the housing construction engineering fee, the transportation engineering fee and other construction engineering fees. In addition, it also includes other fees such as project construction land fees, project construction management fees, production preparation fees, survey and design fees, water conservation facility compensation fees, etc., which are not limited in this disclosure.

[0036] For example, when the photovoltaic area equipment and installation engineering costs consist of photovoltaic power generation equipment and installation engineering costs, convergence and transformation and distribution equipment and installation engineering costs, and other equipment and installation engineering costs, the photovoltaic power generation equipment and installation engineering costs consist of component equipment and installation engineering costs, bracket and installation engineering costs, and marine transportation and hoisting engineering costs. The convergence and transformation and distribution equipment and installation engineering costs consist of inverter equipment and installation engineering costs, 35KV step-up box transformer equipment and installation engineering costs, photovoltaic area monitoring system and other equipment and installation engineering costs. The collection line material and installation engineering costs consist of photovoltaic area DC cable engineering costs, photovoltaic area AC cable engineering costs, 35KV aluminum core cable engineering costs, cable heads, sea-land cable conversion joints, land cable head engineering costs, sea cable anchoring device engineering costs, sea cable online detection system engineering costs, optical fiber composite submarine cable engineering costs, bend limiters, J-tube engineering costs, cable protection pipe engineering costs, fire retardant coatings, fire retardant plugging materials and other engineering costs. The grounding engineering fee consists of the photovoltaic module grounding wire engineering fee, the inverter connection wire engineering fee, the horizontal grounding copper-plated flat steel engineering fee, and the cable trench support grounding device engineering fee. The system commissioning fee consists of the power generation electronic array system commissioning fee and the power plant electrical complete set startup commissioning fee. The optical cable and cable laying engineering fee consists of the data acquisition cabinet communication cable materials and installation engineering fee, communication power line materials and installation engineering fee, control cable materials and installation engineering fee, optical cable 36 core, 24 core materials and installation engineering fee. Other equipment and installation engineering fees consist of fire protection system equipment and installation engineering fees, labor safety and industrial hygiene equipment and installation engineering fees, sea area early warning system engineering fees, intelligent digital platform fees, intelligent laser flash bird repellent engineering fees, high-power strong sound wave bird repellent system, operation and maintenance robot, cleaning robot fees, operation and maintenance vehicle fees, operation and maintenance ship, transportation ship fees, video surveillance system access to the emergency command center fees, bird repellent wire, glass wire fees, bird repellent wire steel support frame fees.

[0037] The construction costs of the photovoltaic area are composed of the construction costs of the power plant and other construction costs. Among them, the construction costs of the power plant are composed of the foundation engineering costs of the power generation equipment, the foundation engineering costs of the convergence and substation equipment, and the collection line engineering costs. The foundation engineering costs of the power generation equipment are composed of steel pile fees, steel pile anti-corrosion fees, sacrificial anode fees, and operation and maintenance pedestrian passage fees. The foundation engineering costs of the convergence and substation equipment are composed of prestressed concrete pipe pile fees, steel ladders, steel cages and other anti-corrosion fees, and steel structure anti-corrosion fees. The collection line engineering costs are composed of steel structure hot-dip galvanizing anti-corrosion fees, prestressed concrete pipe pile fees, cable bracket fees, cable marking pile fees, cable inspection well fees, and concrete cable trench fees. Other construction costs also include water supply engineering fees, power supply engineering fees, environmental protection fees, soil and water conservation engineering fees, labor safety and industrial hygiene engineering fees, pile foundation testing and trial pile fees, construction dock fees, seabed clearance fees, navigation marks, electronic fence fees, etc.

[0038] When the cost of the equipment and installation project of the booster station consists of the equipment and installation project fees of the power distribution equipment of the booster station, the control and protection equipment and installation project fees, and the other equipment and installation project fees, the equipment and installation project fees of the power distribution equipment of the booster station include the equipment and installation project fees of the main transformer, the equipment and installation project fees of the power distribution device, the equipment and installation project fees of the reactive power compensation system, the equipment and installation project fees of the station power equipment, the power cable laying project fees, the grounding project fees, the subsystem commissioning fees, and the startup and commissioning fees of the whole system. Among them, the equipment and installation project fees of the main transformer consist of the equipment and installation project fees of the main transformer, the equipment and installation project fees of the nitrogen-filled fire extinguishing device, the 220KV neutral point equipment and installation project fees, and the equipment and installation project fees of the air-cooled control cabinet. The equipment and installation project fees of the power distribution device include the equipment and installation project fees of 220KV and 35KV.

[0039] The control and protection equipment and installation project fees include monitoring system equipment and installation project fees, protection equipment and installation project fees, uninterruptible power supply system equipment and installation project fees, communication system equipment and installation project fees, dispatching automation equipment and electricity metering system equipment and installation project fees, optical power prediction system equipment and installation project fees, optical cable and cable laying project fees, subsystem debugging project fees, and complete system startup and debugging project fees.

[0040] Among them, the monitoring system equipment and installation project costs are composed of the monitoring layer equipment and installation project costs, and the interval layer equipment and installation project costs. The uninterruptible power supply system equipment and installation project costs include the DC power supply system equipment and installation project costs, UPS (uninterruptable power system) control power supply system equipment and installation project costs, bypass voltage stabilizer screen equipment and installation project costs, emergency lighting inverter power supply equipment and installation project costs, microcomputer-based integrated power supply monitoring device equipment and installation project costs, and communication DC / DC (switching modular voltage stabilized power supply) power supply equipment and installation project costs. The communication system equipment and installation project costs include the production scheduling management communication system equipment and installation project costs, system communication equipment and installation project costs, integrated communication line network equipment and installation project costs, and video conferencing system equipment and project installation costs. Other equipment and installation project costs also include heating and ventilation system equipment and installation project costs, fire protection system equipment and installation project costs, water supply and drainage system equipment and installation project costs, and outdoor lighting equipment and installation project costs.

[0041] When the construction cost of the booster station is composed of the construction cost of the booster substation, the building construction cost, the transportation engineering cost, and other construction costs, the construction cost of the booster substation includes the site leveling engineering cost, the foundation engineering cost of the main transformer and ancillary equipment, the frame and foundation engineering cost of the outdoor power distribution device, the foundation engineering cost of the reactive power compensation device, the station transformer system engineering cost, the lightning rod tower engineering cost, the GIS (Geographic Information System) foundation engineering cost, the cable trench engineering cost, and the building foundation engineering cost. The building construction cost includes the production construction cost and the outdoor engineering cost of the booster station. The transportation engineering cost includes the road fee to the station and the road fee to the booster station. Other construction engineering costs also include water supply engineering costs, power supply engineering costs, environmental protection engineering costs, soil and water conservation engineering costs, labor safety and industrial hygiene engineering costs, pile foundation testing and trial pile fees.

[0042] In addition, when other engineering costs in the investment cost include project construction land fees, project construction management fees, production preparation fees, survey and design fees, and water conservation facility compensation fees, the project construction land fees are composed of permanent land acquisition fees for substations, cable trench land acquisition fees, sea area use fees, 35KV lines and temporary sea use fees; the project construction management fees are composed of project pre-construction fees, project pre-construction related procedures fees, project construction management fees, general contracting management fees, project construction supervision fees, project consulting service fees, project military special report fees, project quality inspection and testing fees, project acceptance fees, project insurance premiums, excellence creation fees, etc. This disclosure does not limit this.

[0043] The operating costs include at least the cost of photovoltaic power generation, fixed asset depreciation, equipment repair, labor input, insurance, material loss and operation and maintenance. Among them, the cost of photovoltaic power generation is composed of depreciation, fixed repair, wages and benefits, insurance, material, interest, amortization and other expenses. Taking the annual depreciation as an example, the annual depreciation is calculated based on the original value of fixed assets and the annual depreciation rate, such as annual depreciation = original value of fixed assets × annual depreciation rate, original value of fixed assets = investment cost + construction period interest - deductible value-added tax, annual depreciation rate = (1-net residual value rate of fixed assets) / depreciation period × 100%. Taking the annual repair fee as an example, the annual repair fee = original value of fixed assets (minus the included construction period interest) × repair rate. Wages and benefits = fixed number × average wage of employees × (1 + welfare rate as a percentage of wages + labor insurance pooling rate as a percentage of wages + housing fund as a percentage of wages). Insurance premium = insurance premium rate × original value of fixed assets. Material cost = installed capacity of offshore photovoltaic field × material rate. Interest expense = loan repayment interest expense + working capital interest expense. Other expenses may also include installed capacity of offshore photovoltaic field × other expense rate + sea area use fee + land lease fee, etc. For example, the operating cost can be obtained by subtracting depreciation, interest expense and amortization from the photovoltaic power generation cost.

[0044] The investment cost model for the construction period is used to calculate the investment cost, which ensures detailed calculation of various construction expenditures such as photovoltaic area equipment, construction projects, and booster station facilities. The operation cost model for the operation period is used to calculate the operation cost, which covers the long-term cost of photovoltaic power generation, equipment depreciation, repair costs, labor costs, and insurance costs, etc., to ensure a comprehensive prediction of the economic feasibility of the photovoltaic power station throughout its life cycle.

[0045] In an example implementation, the revenue driving parameters include annual grid-connected electricity and grid-connected electricity price, wherein annual grid-connected electricity refers to the effective electricity actually delivered to the grid by the photovoltaic power station in one year, and grid-connected electricity price refers to the unit price of electricity sold after the photovoltaic power station generates electricity and is connected to the grid.

[0046] The revenue prediction module 130 includes a revenue model building module and a power generation revenue prediction module. The revenue model building module is used to establish a revenue model based on the annual grid-connected power and grid-connected power price. For example, annual power generation sales revenue = annual grid-connected power × grid-connected power price.

[0047] Exemplarily, the original annual power generation can be determined based on the installed capacity of the photovoltaic power station, the reference irradiance and the corresponding annual total horizontal solar irradiance, and the annual grid-connected power can be calculated based on the spatial layout correction factor, the component performance correction factor, the operating efficiency correction factor and the original annual power generation. Among them, the reference irradiance can be the irradiance under STC (Standard Test Conditions), the spatial layout correction factor includes the photovoltaic array solar irradiation inclination, the azimuth correction factor and the photovoltaic array shadow shielding loss correction factor, the component performance correction factor includes the photovoltaic component surface incident angle loss correction factor and the component operating temperature correction factor, and the operating efficiency correction factor includes the inverter input power conversion efficiency and other efficiency coefficients, such as power deviation, component mismatch, and collector line loss.

[0048] For example, there is: (1) in, is the original annual power generation, Install capacity for photovoltaic power plants, is the irradiance under STC, is the total annual horizontal solar radiation; (2) in, is the annual online electricity consumption, is the correction coefficient of the inclination and azimuth angle of the solar radiation of the photovoltaic array, is the photovoltaic array shadow loss correction coefficient, is the incident angle loss correction factor on the photovoltaic module surface, is the component operating temperature correction factor, is the inverter input power conversion efficiency, are other efficiency coefficients.

[0049] Furthermore, the power generation revenue prediction module is used to calculate the annual power generation sales revenue according to the revenue model, and the annual power generation revenue is calculated based on the annual power generation sales revenue, operating costs and taxes. After the annual power generation sales revenue is calculated, the annual operating income can be obtained by subtracting the tax from the annual power generation sales revenue, where the tax refers to the output tax of the value-added tax. The annual power generation revenue is the annual operating income minus the business tax and surcharges, and the photovoltaic power generation cost in the operating costs. For example, the business tax and surcharges include the urban maintenance and construction tax and the education surcharge, the urban maintenance and construction tax = value-added tax × urban maintenance and construction tax rate, and the education surcharge = value-added tax × education surcharge rate.

[0050] The income prediction module 130 also includes an income index calculation module, which is used to calculate the return on investment using the annual income, where the return on investment is equal to the proportion of annual power generation income corresponding to the investment amount. In the exemplary implementation of the present disclosure, the return on investment includes the total investment return rate and the net profit rate of capital. For example: (3) in, ROI The total investment return rate is used to measure the overall investment return level of the project. EBIT The profit before interest and taxes of the project in a normal year or the average profit before interest and taxes during the operation period. TI The total investment of the project.

[0051] (4) in, ROE It is the net profit rate of capital, which is used to measure the profitability of the project's capital. NP is the annual net profit of the project in a normal year or the average annual net profit during the operation period. EC is the project's capital.

[0052] The benefit analysis module 140 includes an analysis model construction module and a cycle benefit analysis module. Among them, the analysis model construction module is used to establish a benefit analysis model based on investment cost, operating cost and investment income. The benefit analysis model includes an investment plan and fund raising sub-model, a loan principal and interest payment sub-model, a planned cash flow quantum model, an asset-liability sub-model, a project investment cash flow quantum model, and a project capital cash flow quantum model. Correspondingly, the cycle benefit analysis module is used to calculate the full life cycle benefits of the target photovoltaic project using the benefit analysis model. In the example implementation of the present disclosure, the full life cycle benefits include the total project investment funds and the total fund raising amount, the amount of principal and interest to be paid, the annual accumulated surplus funds, the total assets and total liabilities, the financial internal rate of return, the payback period, etc.

[0053] In an example implementation, the process of building the investment plan and fund raising sub-model includes: The total investment of the project consists of investment cost, construction period interest and working capital, and the total amount of funds raised consists of capital, bank loans and other financing costs. Among them, capital = (investment cost + construction period interest) × capital ratio + working capital × working capital capital ratio, bank loans include long-term loans, working capital loans and other short-term loans, long-term loans = (investment cost + construction period interest) × (1-capital ratio), working capital loans = working capital × (1-capital ratio).

[0054] The process of building the loan principal and interest payment sub-model includes: The beginning loan balance includes the current year's loan and the interest during the construction period. The interest during the construction period is taken as the current principal and interest repayment. The current principal and interest repayment includes the current year's principal repayment and the current year's accrued interest. Among them, the current year's principal repayment = the accumulated principal and interest of the loan at the beginning of the year / repayment period, and the current year's accrued interest = the accumulated principal and interest of the loan at the beginning of the year × the long-term loan interest rate.

[0055] The total amount of working capital loans is calculated based on the annual working capital to loan ratio, and the working capital interest = total amount of working capital loans × short-term loan interest rate.

[0056] Furthermore, the interest coverage ratio and debt service coverage ratio can be calculated, where the interest coverage ratio is used to measure the project's interest payment ability, and the debt service coverage ratio is used to measure the project's overall debt repayment ability. For example, there are: (5) in, ICR is the interest coverage ratio, EBIT is the profit before interest and tax, PI Interest payable included in total cost.

[0057] (6) in, is the debt service coverage ratio, EBITAD is EBITDA plus depreciation and amortization, T AX For corporate income tax, PD The amount of principal and interest to be repaid.

[0058] The process of building a planned cash flow quantum model includes: Net cash flow from operating activities is the difference between the first cash inflow and the first cash outflow. The first cash inflow includes operating income, output tax of value-added tax, subsidy income, other inflows and recovered working capital. The first cash outflow includes operating costs, input tax of value-added tax, business tax and surcharges, value-added tax, income tax and other outflows.

[0059] Net cash flow from investing activities is the difference between the second cash inflow and the second cash outflow. The second cash outflow includes construction investment, operating maintenance investment, working capital and other outflows, while the second cash inflow includes investment recovery, government subsidies, etc.

[0060] Net cash flow from financing activities is the difference between the third cash inflow and the third cash outflow. Among them, the third cash inflow includes project capital investment, construction investment loans, working capital loans, bonds, short-term loans and other inflows. The third cash outflow includes various interest expenses, repayment of debt principal, repayment of working capital principal, payable profits (dividend distribution) and other outflows.

[0061] Finally, the net cash flow can be calculated by the net cash flow from operating activities, net cash flow from investing activities, and net cash flow from financing activities. Therefore, the annual accumulated surplus funds are composed of the accumulated surplus funds of the previous year and the net cash flow of the current year.

[0062] The process of building the asset-liability sub-model includes: Total assets include total current assets, construction in progress, net fixed assets, net intangible and deferred assets, and assets deductible from value-added tax. Among them, total current assets include current assets and accumulated surplus funds, construction in progress = investment cost + construction period interest - deductible value-added tax - loan repayment depreciation, net fixed assets in the first year of operation = construction in progress - loan repayment depreciation, net fixed assets in each year of operation except the first year = net fixed assets in the previous year - loan repayment depreciation, total liabilities include total current liabilities, construction investment loans, working capital loans and owner's equity. Among them, owner's equity is composed of capital, capital reserve, accumulated surplus reserve and accumulated retained earnings.

[0063] Furthermore, the debt-to-asset ratio can be calculated to measure the debt level of the project. A high debt-to-asset ratio indicates a higher financial risk of the project.

[0064] For example, there is: (7) in, LOAR is the debt-to-asset ratio, TL is the total liabilities at the end of the period, and TA is the total assets at the end of the period.

[0065] The process of building a quantum model of project investment cash flow includes: Project investment cash inflows include power generation sales revenue, subsidy revenue, recovery of fixed asset residual value and recovery of working capital. Project investment cash outflows include construction investment, working capital, operating costs, value-added tax, business tax and surcharges, and investment in maintaining operations. Net cash flow before income tax is project investment cash inflow minus project investment cash outflow. Cumulative net cash flow before income tax is the sum of the cumulative net cash flow before income tax in the previous year and the net cash flow before income tax in the current year. Net cash flow after income tax is project investment cash inflow minus project investment cash outflow and adjusted income tax. Cumulative net cash flow after income tax is the sum of the cumulative net cash flow after income tax in the previous year and the net cash flow after income tax in the current year.

[0066] In the disclosed embodiment, the project investment financial internal rate of return and investment payback period can be calculated. Among them, the project investment financial internal rate of return is used to measure the financial feasibility of the project, which represents the discount rate that makes the cumulative net cash flow present value zero during the entire life cycle of the project. The investment payback period is used to measure the speed of project fund recovery, that is, the time it takes for the project investment to pay back.

[0067] For example, there is: (8) in, =0 means that when the discount rate is the internal rate of return (IRR) of the project investment, NPV (Net Present Value) is equal to 0. CI represents the cash inflow from the project investment in period t, CO It represents the cash outflow of project investment in period t, and n is the life cycle of the project.

[0068] (9) in, is the payback period, T is the year when the cumulative net cash flow becomes positive or zero, It represents the absolute value of the cumulative net cash flow in the previous year. Indicates net cash flow in years with positive results.

[0069] The process of building the project capital cash flow quantum model includes: The cash inflow of project capital includes power generation sales revenue, subsidy income, recovery of fixed asset residual value, and recovery of working capital. The cash outflow of project capital includes project capital, loan principal repayment, loan interest payment, operating costs, value-added tax, business tax and surcharge, income tax, and investment in maintaining operations. The net cash flow of project capital is the cash inflow of project capital minus the cash outflow of project capital. The corresponding financial internal rate of return of capital can be calculated by referring to formula (8).

[0070] In this example, first, by building a benefit analysis model, the investment, financing, income and debt of the photovoltaic project can be comprehensively evaluated to improve the scientific nature of investment decisions. Secondly, the benefit analysis model can calculate key financial indicators such as internal rate of return and payback period based on the entire life cycle, providing investors with accurate income forecasts. In addition, through the collaborative analysis of sub-models such as investment plans and loan repayments, the use of funds can be reasonably arranged to improve the efficiency of fund operations. At the same time, through comprehensive financial calculations and income forecasts, potential financial risks can be identified in advance to ensure the sustainability and sound operation of the project.

[0071] In the exemplary implementation of the present disclosure, the preset uncertain variables include operating years, operating costs and sales revenue. Figure 2 As shown, the simulation module 150 includes: The distribution model building module 151 is used to build an input variable probability distribution model based on the cost data and revenue data of the benefit analysis model, wherein the input variable probability distribution model includes uniform distribution of operating years, normal distribution of operating costs and triangular distribution of sales revenue.

[0072] For example, because the life of equipment is affected by factors such as marine corrosion and extreme weather, there is no clear attenuation law, so a uniform distribution is used to reflect the equal probability of each year, such as a uniform distribution of project operation years within the range of 20-30 years. The mean and standard deviation are fitted based on historical operation and maintenance data, assuming that operating costs fluctuate normally around the mean. The triangular distribution parameters of sales revenue are defined as the minimum sales value, the most likely sales value, and the maximum sales value.

[0073] The uncertainty simulation module 152 is used to perform uncertainty simulation based on the probability distribution model of the input variables using the Monte Carlo simulation method to obtain the probability distribution of the economic indicators of the entire life cycle.

[0074] Exemplarily, the uncertainty simulation module 152 includes a sample generation submodule 1521 and a simulation submodule 1522. The sample generation submodule 1521 is used to randomly extract multiple random samples from the input variable probability distribution model, such as a sample including an operating period of 25 years, an operating cost of 50 million, and a sales revenue of 200 million. The simulation submodule 1522 is used to calculate the full life cycle economic indicators corresponding to each random sample, such as financial internal rate of return, investment payback period and other indicators. And through multiple simulations, the probability distribution of the full life cycle economic indicators is obtained.

[0075] The economic grade determination module 153 is used to determine the economic grade of the target photovoltaic project according to the probability distribution of the economic index of the whole life cycle and the preset probability distribution threshold. Taking the financial internal rate of return IRR as an example, the mean value can be obtained through the probability distribution statistics of IRR. If the IRR mean value is greater than the probability distribution threshold of 8%, the economic grade of the target photovoltaic project is determined to be low risk. If the IRR mean value is within the probability distribution threshold range of 5%~8% (including 5% and 8%), the economic grade of the target photovoltaic project is determined to be medium risk. If the IRR mean value is less than the probability distribution threshold of 5%, it can be known that the project is close to the loss threshold, and the economic grade of the target photovoltaic project is determined to be high risk, and the uncertain variables in the project need to be optimized. The economic grade determination module 153 can feed back the risk level to the project management system to trigger the risk control process.

[0076] In addition, the simulation module 150 also includes a sensitivity analysis submodule 154, which can quantify the impact of each input variable (operating years, operating costs, sales revenue) on the economic indicators of the entire life cycle, identify key risk sources, and adjust the economic level according to sensitivity.

[0077] Specifically, this module is used to calculate the sensitivity coefficient corresponding to the economic performance index of the entire life cycle based on the change of each input variable, and determine the sensitivity index from each input variable according to the sensitivity coefficient. For example, based on several simulation results of Monte Carlo simulation, a multivariate linear regression model is constructed to measure the sensitivity coefficient corresponding to each input variable with the standardized regression coefficient, which is: (10) in, , , The three input variables are operating years, operating costs, and sales revenue. , , are the sensitivity coefficients corresponding to each input variable, is the error term, including variables not included in the model, such as natural disasters, etc. If a sensitivity coefficient is greater than the preset sensitivity threshold, the input variable corresponding to the sensitivity coefficient is marked as a sensitivity index.

[0078] For example, if the sensitivity indicator is determined to be sales revenue, and the calculated sensitivity coefficient of sales revenue is greater than the preset sensitivity threshold, even if the IRR meets the standard, the economic grade may still be downgraded due to risk concentration.

[0079] The parameter optimization submodule 155 is used to adjust the target parameters in the construction period investment cost model, the operation and maintenance cost model and the income model according to the probability distribution and sensitivity index of the economic indicators of the whole life cycle.

[0080] For example, after determining the sensitivity index such as sales revenue, the distribution parameters of sales revenue can be modified to reduce the split line, such as raising the most likely value of the triangular distribution of sales revenue from 270 million yuan to 290 million yuan to reflect the results of the electricity price subsidy negotiation. The on-grid electricity price in the income model can also be adjusted, such as striving for electricity price subsidies, and the operation and maintenance strategy can be optimized by adjusting the operation and maintenance cost model during the operation period, such as reducing the repair fee rate from 1.0% to 0.8%.

[0081] Then, the distribution model building module 151 may be input based on the adjusted target parameters to perform a new round of Monte Carlo simulation to verify whether the IRR mean and sensitivity index are improved.

[0082] In this example, by constructing a probability model of operating years, operating costs and sales revenue, and combining Monte Carlo simulation to generate several random samples, the probability distribution of economic indicators of the target photovoltaic project throughout its life cycle is dynamically simulated, and the economic level of the target photovoltaic project is divided based on the preset probability distribution threshold. At the same time, sensitivity analysis is used to identify key risk variables, and model parameters are optimized for highly sensitive variables. Through closed-loop iterative verification, the coordination of risk quantification and strategy adjustment is achieved, which significantly improves the accuracy of project evaluation and the reliability of decision-making, effectively guides investors to avoid high-risk scenarios and prioritize the control of core variables, and ensures economic feasibility in complex environments and policy fluctuations.

[0083] The embodiment of the present disclosure also provides a method for evaluating the economic performance of a photovoltaic project over its entire life cycle, which is implemented based on an economic performance evaluation system for a photovoltaic project over its entire life cycle. Figure 3 As shown, the method may include steps S310 to S350: Step S310, obtaining engineering construction parameters and revenue driving parameters of the target photovoltaic project; The data collection system is used to collect infrastructure information and economic factors affecting photovoltaic projects. Engineering construction parameters include specific contents such as photovoltaic area equipment and installation, booster station construction, transmission lines and grid connection schemes, construction period, operation and maintenance requirements, etc., to ensure that relevant data on project construction and long-term operation and maintenance are fully acquired. Revenue-driven parameters include core data that affect project revenue, such as annual grid-connected electricity, grid-connected electricity prices, tax incentives, market trading mechanisms, financing conditions and government subsidies. By acquiring and classifying engineering construction parameters and revenue-driven parameters, high-precision input data is provided for subsequent cost estimation, revenue evaluation and economic analysis.

[0084] Step S320, establishing a construction period investment cost model and an operation period operation and maintenance cost model based on the engineering construction parameters, and using the construction period investment cost model and the operation period operation and maintenance cost model to respectively calculate the investment cost and the operation cost of the target photovoltaic project; First, through the model building method, the engineering construction parameters are refined into the construction period investment cost module and the operation and maintenance cost module. The construction period investment cost model is based on data such as photovoltaic area equipment, installation costs, construction project costs, and booster station construction costs to calculate the total investment amount of the project from project approval to commissioning. The operation and maintenance cost model in the operation period is based on factors such as equipment depreciation, regular maintenance, labor costs, insurance costs, and material losses to calculate the annual operation and maintenance expenses of the photovoltaic power station during the operation period. In the cost calculation process, the service life, maintenance cycle, and repair cost of different equipment are comprehensively considered to ensure the scientificity and predictability of investment and operation cost calculations.

[0085] Step S330, establishing an income model based on the income driving parameter, and calculating the investment income of the target photovoltaic project using the income model; First, the basic income model of photovoltaic projects is established using the annual grid-connected electricity and grid-connected electricity prices. The calculation of annual grid-connected electricity is combined with correction factors such as installed capacity, reference irradiance, component attenuation rate, inverter conversion efficiency, and shadow shielding to ensure the accuracy of power generation forecasts. The grid-connected electricity price data is calculated based on market transaction electricity prices, government subsidy policies, and grid settlement prices. The income model further refines the income structure, covering power generation sales income, etc., and combines financing methods and tax policies to calculate the actual investment income of photovoltaic projects. Through this model, the income of photovoltaic projects can be comprehensively evaluated, providing accurate income data for subsequent benefit analysis.

[0086] Step S340, establishing a benefit analysis model based on the investment cost, operating cost and investment income, and using the benefit analysis model to predict the full life cycle income of the target photovoltaic project; The economic evaluation framework of the target photovoltaic project is constructed through the benefit analysis model, and the long-term financial performance of the target photovoltaic project is comprehensively calculated. Among them, the benefit analysis model includes sub-models such as investment plan and fund raising, loan repayment, cash flow analysis, asset and liability calculation, and project investment return. By integrating investment costs, operating costs and investment returns, the annual net cash flow, return on capital and financial internal rate of return are calculated to form a complete economic measurement system. The investment payback period of the photovoltaic project is also calculated to clarify the investment payback period.

[0087] Step S350, based on preset uncertain variables, simulate the full life cycle benefits of the target photovoltaic project to obtain the probability distribution of the full life cycle economic indicators, and determine the economic level of the target photovoltaic project according to the probability distribution of the full life cycle economic indicators.

[0088] Monte Carlo simulation technology is used to simulate the impact of uncertain factors such as power generation fluctuations, electricity price changes, and operation and maintenance cost changes on the economic performance of the project. During the simulation process, multiple groups of random samples are generated by setting variables such as operating years, cost fluctuation range, and electricity price adjustment range, and the corresponding key economic indicators such as financial internal rate of return, investment payback period, and debt-to-asset ratio are calculated. Finally, through statistical analysis of simulation data, a probability distribution curve of the economic performance indicators of the entire life cycle is generated, and based on the rate of return distribution range, the economic performance level of the target photovoltaic project is determined, providing a reliable basis for investment decisions.

[0089] The specific details of each step in the above-mentioned photovoltaic project full life cycle economic evaluation method have been described in detail in the corresponding photovoltaic project full life cycle economic evaluation system, so they will not be repeated here.

[0090] The present disclosure realizes a comprehensive economic analysis from engineering construction to operation management by constructing an economic evaluation system for the entire life cycle of photovoltaic projects, ensuring the scientificity and accuracy of investment decisions. Through data collection, the system accurately obtains engineering construction parameters and revenue driving parameters, providing high-precision input data for cost prediction and revenue calculation. The cost prediction model combines the investment in the construction period and the operation and maintenance costs in the operation period to refine the investment estimates of photovoltaic areas, booster stations and transmission facilities, and improves the rationality of cost calculation. The revenue prediction model ensures the comprehensiveness of investment return calculation by comprehensively considering the power generation, electricity price and policy benefits. The benefit analysis model provides a long-term economic evaluation framework by integrating investment, financing, cash flow and asset-liability calculations, making the prediction of financial indicators more accurate. Simulation improves the predictability of project economic risks by introducing uncertain variables and calculating the probability distribution of economic indicators throughout the life cycle. The overall solution can improve the accuracy of investment return evaluation of photovoltaic projects, optimize fund raising and recovery cycles, and provide investors and managers with reliable economic analysis tools, thereby supporting the sustainable development of the photovoltaic industry.

[0091] The exemplary embodiments of the present disclosure also provide a computer-readable storage medium on which a program product capable of implementing the above-mentioned method of the present specification is stored. In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes a program code, and when the program product is run on an electronic device, the program code is used to enable the electronic device to perform the steps according to various exemplary embodiments of the present disclosure described in the above-mentioned "Exemplary Method" section of the present specification.

[0092] The program product may be in the form of a portable compact disk read-only memory (CD-ROM) and include program code, and may be run on an electronic device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0093] The program product may adopt any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, a system, device or component of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable 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 thereof.

[0094] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. 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. Readable signal media may also be any readable medium other than a 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.

[0095] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0096] Program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C#, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0097] In addition, an exemplary embodiment of the present disclosure also provides an electronic device capable of implementing the above-mentioned economic evaluation method for the entire life cycle of a photovoltaic project.

[0098] Refer to the following Figure 4 hereinafter describes an electronic device 400 according to such an embodiment of the present disclosure. Figure 4 The electronic device 400 shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0099] like Figure 4 As shown, the electronic device 400 is in the form of a general computing device. The components of the electronic device 400 may include but are not limited to: the at least one processing unit 410, the at least one storage unit 420, a bus 430 connecting different system components (including the storage unit 420 and the processing unit 410), and a display unit 440.

[0100] The storage unit 420 stores program codes, which can be executed by the processing unit 410, so that the processing unit 410 performs the steps according to various exemplary embodiments of the present disclosure described in the above “Exemplary Method” section of this specification. For example, the processing unit 410 can perform the method steps in the exemplary embodiments of the present disclosure.

[0101] The storage unit 420 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache memory unit (Cache) 422 , and may further include a read-only memory unit (ROM) 423 .

[0102] The storage unit 420 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 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.

[0103] Bus 430 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0104] The electronic device 400 may also communicate with one or more external devices 500 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may also communicate with one or more devices that enable a user to interact with the electronic device 400, and / or may communicate with any device that enables the electronic device 400 to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface 450. In addition, the electronic device 400 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 460. As shown, the network adapter 460 communicates with other modules of the electronic device 400 through a bus 430. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 400, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0105] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0106] In addition, the above-mentioned figures are only schematic illustrations of the processes included in the method according to the exemplary embodiments of the present disclosure, and are not intended to be limiting. It is easy to understand that the processes shown in the above-mentioned figures do not indicate or limit the time sequence of these processes. In addition, it is also easy to understand that these processes can be performed synchronously or asynchronously, for example, in multiple modules.

[0107] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the embodiment of the present disclosure.

[0108] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0109] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. An economic evaluation system for the entire life cycle of a photovoltaic project, characterized in that: include: Data acquisition module, used to obtain engineering construction parameters and revenue driving parameters of the target photovoltaic project; A cost prediction module, for establishing a construction period investment cost model and an operation and maintenance cost model based on the engineering construction parameters, and using the construction period investment cost model and the operation and maintenance cost model to respectively calculate the investment cost and the operation cost of the target photovoltaic project; A revenue prediction module, used to establish a revenue model based on the revenue driving parameter, and calculate the investment return of the target photovoltaic project using the revenue model; A benefit analysis module, for establishing a benefit analysis model based on the investment cost, operating cost and investment income, and using the benefit analysis model to predict the full life cycle income of the target photovoltaic project; The simulation module is used to simulate the full life cycle benefits of the target photovoltaic project based on preset uncertain variables, obtain the probability distribution of the full life cycle economic indicators, and determine the economic level of the target photovoltaic project according to the probability distribution of the full life cycle economic indicators.

2. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 1 is characterized in that: The engineering construction parameters include investment parameters during the construction period and operation and maintenance parameters during the operation period; the cost prediction module includes: A model building submodule, used to establish a construction period investment cost model based on the construction period investment parameters, and to establish an operation and maintenance cost model based on the operation and maintenance parameters; A cost prediction submodule, used to calculate the investment cost and operation cost of the target photovoltaic project respectively by using the construction period investment cost model and the operation period operation and maintenance cost model; Among them, the investment cost at least includes the photovoltaic area equipment and installation cost, the photovoltaic area construction cost, the substation equipment and installation cost, and the substation construction cost; the operating cost at least includes the photovoltaic power generation cost, fixed asset depreciation cost, equipment repair cost, labor input cost, insurance cost, material loss and operation and maintenance cost.

3. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 1 is characterized in that: The revenue driving parameters include annual grid-connected power and grid-connected power price; the revenue prediction module includes: An income model building module is used to establish an income model based on the annual grid-connected electricity and the grid-connected electricity price; wherein the original annual power generation is determined according to the installed capacity of the photovoltaic power station, the reference irradiance and the corresponding annual horizontal plane total solar irradiance, and the annual grid-connected electricity is calculated based on the spatial layout correction factor, the component performance correction factor, the operation efficiency correction factor and the original annual power generation; The power generation revenue prediction module is used to calculate the annual power generation sales revenue according to the revenue model, and calculate the annual power generation revenue based on the annual power generation sales revenue, operating costs and taxes.

4. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 3 is characterized in that: The revenue prediction module also includes: The income index calculation module is used to calculate the investment return rate using the annual power generation income, wherein the investment return rate is equal to the proportion of the annual power generation income corresponding to the investment amount.

5. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 1 is characterized in that: The benefit analysis module includes: An analysis model building module is used to establish a benefit analysis model based on the investment cost, operating cost and investment income, wherein the benefit analysis model includes an investment plan and fund raising sub-model, a loan principal and interest payment sub-model, a planned cash flow quantum model, an asset-liability sub-model, a project investment cash flow quantum model, and a project capital cash flow quantum model; The life cycle benefit analysis module is used to calculate the full life cycle benefits of the target photovoltaic project using the benefit analysis model. The full life cycle benefits include the total project investment and total fund raising, the amount of principal and interest to be repaid, the annual accumulated surplus funds, the total assets and total liabilities, the financial internal rate of return, and the investment payback period.

6. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 1 is characterized in that: The preset uncertain variables include operating years, operating costs and sales revenue; the simulation module includes: A distribution model building module, used to build an input variable probability distribution model based on the cost data and revenue data of the benefit analysis model, wherein the input variable probability distribution model includes a uniform distribution of operating years, a normal distribution of operating costs, and a triangular distribution of sales revenue; An uncertainty simulation module, used to perform uncertainty simulation based on the input variable probability distribution model using a Monte Carlo simulation method to obtain a probability distribution of the economic indicators of the entire life cycle; An economic grade determination module is used to determine the economic grade of the target photovoltaic project according to the probability distribution of the full life cycle economic indicators and a preset probability distribution threshold.

7. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 6 is characterized in that: The uncertainty simulation module includes: A sample generation submodule, used for randomly extracting a plurality of random samples from the input variable probability distribution model; The simulation submodule is used to calculate the full life cycle economic indicators corresponding to each random sample, and obtain the probability distribution of the full life cycle economic indicators through multiple simulations.

8. The economic evaluation system for the entire life cycle of a photovoltaic project according to claim 6 is characterized in that: The simulation module also includes: A sensitivity analysis submodule, for calculating the sensitivity coefficient corresponding to the life cycle economic index based on the change of each input variable, and determining the sensitivity index from each input variable according to the sensitivity coefficient; The parameter optimization submodule is used to adjust the target parameters in the construction period investment cost model, operation period operation and maintenance cost model and income model according to the probability distribution and sensitivity index of the full life cycle economic indicators.

9. A method for economic evaluation of the entire life cycle of a photovoltaic project, characterized in that: include: Obtain engineering construction parameters and revenue driving parameters of the target PV project; Based on the engineering construction parameters, a construction period investment cost model and an operation and maintenance cost model are established, and the investment cost and operation cost of the target photovoltaic project are calculated using the construction period investment cost model and the operation and maintenance cost model respectively; Based on the revenue driving parameters, establishing a revenue model, and using the revenue model to calculate the investment return of the target photovoltaic project; Based on the investment cost, operating cost and investment income, a benefit analysis model is established, and the benefit analysis model is used to predict the full life cycle income of the target photovoltaic project; Based on preset uncertain variables, the full life cycle benefits of the target photovoltaic project are simulated to obtain the probability distribution of the full life cycle economic indicators, and the economic level of the target photovoltaic project is determined according to the probability distribution of the full life cycle economic indicators.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for economic evaluation of the entire life cycle of a photovoltaic project as described in claim 9 is implemented.

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