CN116307955A - Photovoltaic full life cycle economic benefit measuring and calculating method and system - Google Patents
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Abstract
The invention belongs to the field of electric power, and particularly relates to a photovoltaic full life cycle economic benefit measuring and calculating method and system, wherein the method comprises the steps of setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model; constructing an economic benefit measuring and calculating framework based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model; and obtaining economic benefit data based on the economic benefit measuring and calculating architecture and photovoltaic project parameters. Setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model, and determining factors influencing economic benefit calculation can improve calculation accuracy; the economic benefit measuring and calculating architecture is constructed, so that different factors can be unified, and the accuracy and the efficiency of calculation are improved; based on the economic benefit measuring and calculating architecture and the photovoltaic project parameters, economic benefit data are obtained, and the full life cycle economic benefit of the photovoltaic can be effectively analyzed.
Description
Technical Field
The invention belongs to the field of electric power, and particularly relates to a photovoltaic full life cycle economic benefit measuring and calculating method and system.
Background
The distributed photovoltaic power generation project is mainly divided into two modes of operation, wherein the first mode is that an investor cooperates with a roof enterprise, and a contract energy management mode (EMC) is adopted according to the requirement of an energy-saving project; and the second mode is a full-scale internet surfing mode, and the electricity price of the internet surfing standard rod of the local illumination resource region is directly sold to an electric network enterprise. The most widely applied distributed photovoltaic power generation system is solar photovoltaic equipment built on the roof of a building, so that the problems of power utilization of industry and commerce in areas with energy shortage, high load density and the like in remote rural areas and residents can be effectively solved, and meanwhile, economic benefits are brought by a residual internet surfing mode. The economic benefit measurement and calculation of the roof distributed photovoltaic power generation project is more complicated than that of a ground photovoltaic power station, and multiple factors such as a local electric charge pricing mode, an electric price, an electric load of an enterprise user, a local solar irradiation resource condition, a photovoltaic output condition, and matching performance with an enterprise electric load curve are required to be considered. And the measurement of the economic benefit of the distributed photovoltaic firstly requires the estimation of the power generation capacity of the distributed photovoltaic, and two technical methods are generally adopted. The method one refers to a common calculation method for generating capacity of a photovoltaic power station, namely a peak sunlight hours estimation method deduced according to a generating capacity calculation formula in the standard of GB50797-2012 photovoltaic power station design Specification. Establishing a related relation data model by using roof distributed photovoltaic power generation capacity and local sunshine duration data observed by demonstration users, solving a daily average value by using the local sunshine duration data, substituting the daily average value into the model to calculate the daily power generation capacity and the annual power generation capacity of the local distributed photovoltaic, and obtaining the spatial distribution of the local annual power generation capacity.
However, the prior art method relies on solar observation, distributed photovoltaic installation information, distributed photovoltaic user information and other data which are difficult to obtain, so that the method has great difficulty in practical application, only the cost and benefit of a photovoltaic power generation system are considered, and compared with the conventional power generation system, the method does not consider the influence of different operation modes, different grid-connected schemes, different subsidy policies and the like on the grid-connected cost and benefit of the photovoltaic power generation. The method for measuring and calculating the economic benefits of the distributed photovoltaic mainly based on the data of the distributed photovoltaic power generation and the power consumption is not seen, and the automatic measurement and the visual display of the economic benefits of the distributed photovoltaic project are realized by a corresponding information system.
Disclosure of Invention
In order to solve or improve the problems, the invention provides a method and a system for measuring and calculating the economic benefits of a photovoltaic full life cycle, which concretely comprises the following technical scheme:
the invention provides a photovoltaic full life cycle economic benefit measuring and calculating method, which comprises the following steps: setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model; constructing an economic benefit measuring and calculating framework based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model; and obtaining economic benefit data based on the economic benefit measuring and calculating architecture and the photovoltaic project parameters.
Preferably, setting the power generation amount prediction model includes: and predicting the monthly power generation amount by using an XGBoost algorithm, wherein the data characteristics screened by combining characteristic engineering are used as model input parameters based on weather, temperature, holidays and economic development factors.
Preferably, setting the generated power prediction model includes: and predicting the daily power generation average load by using a LightGBM algorithm, wherein characteristic data comprising air temperature and air flow, weather conditions, user power utilization time length and power utilization date are screened and tidied based on two dimensions of weather parameters and user power utilization historical behaviors, and are used as model input parameters.
Preferably, setting the project investment cost model includes: total distributed project investment cost c=w× (c0+c1), where W is the installed capacity of the distributed photovoltaic power generation project, C0 is the unit investment cost, and C1 is the unit operation and maintenance cost.
Preferably, setting the project economic benefit model includes: project annual income = self-consumption amount x comprehensive subsidy electricity price + online electricity amount x online electricity price, wherein self-consumption amount = (first year generated energy × (last year generated power + current year predicted generated power)/2) x self-consumption percentage; comprehensive subsidy electricity price= ((resident or enterprise electricity price) ×self-use percentage + (1-self-use percentage) ×desulfurization coal-fired electricity price); on-line electric quantity= (first year generated energy× (last year generated power+current year predicted generated power)/2× (1-percent of self-use).
Preferably, constructing the economic benefit measuring and calculating architecture further includes: setting a data center to collect photovoltaic project parameters corresponding to distributed optical fiber projects in the area; the data center is further configured to support operations of the power generation amount prediction model, the power generation power prediction model, the project investment cost model, and the project economic benefit model.
Preferably, the distributed optical fiber items include user exclusive items, and calculating the economic benefit data of the user exclusive items includes: estimating investment cost according to the user's digestion capacity, electricity price, building available effective area and site installation conditions; estimating the self-use percentage of the user power generation according to the annual power consumption and annual power generation of the user, and calculating project annual income according to the self-use price, the internet price and the annual internet power consumption; and calculating a project static investment recovery period by combining the project annual benefits with the investment cost so as to evaluate project economic feasibility.
Preferably, the distributed optical fiber project includes a financing lease investment project, and calculating the economic benefit data of the financing lease investment project includes: calculating comprehensive investment cost according to enterprise financing conditions; estimating the self-use percentage of user power generation according to the annual power consumption and annual power generation of the enterprise, and calculating project annual income according to the self-use price, the internet price and the annual internet power consumption; and calculating a static investment recovery period through the comprehensive investment cost and the project annual income project to evaluate the project economic feasibility.
Preferably, the economic benefit data is calculated over a 20 year period.
The invention provides a photovoltaic full life cycle economic benefit measuring and calculating system, which comprises: the first module is used for setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model; the second module is used for constructing an economic benefit measuring and calculating framework based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model; and the third module is used for obtaining economic benefit data based on the economic benefit measuring and calculating framework and the photovoltaic project parameters.
The beneficial effects of the invention are as follows: setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model, and determining factors influencing economic benefit calculation can improve calculation accuracy; based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model, an economic benefit measuring and calculating framework is constructed, so that different factors can be unified, and the calculation accuracy and efficiency are improved; based on the economic benefit measuring and calculating architecture and the photovoltaic project parameters, economic benefit data are obtained, and the full life cycle economic benefit of the photovoltaic can be effectively analyzed.
Drawings
FIG. 1 is a schematic diagram of a photovoltaic full life cycle economic benefit measurement method according to the present invention;
fig. 2 is a schematic diagram of a photovoltaic full life cycle economic benefit measuring system according to the present invention.
Advantageous effects
The invention provides a method and a system architecture, which can calculate the annual average income amount, the annual average income rate and the recovery cost age of a distributed photovoltaic in real time according to data such as input installed capacity, online electricity price, average power generation utilization hour and the like, and combine the measuring and calculating parameters such as unit subsidy, online electricity price, average operation and maintenance cost, one-time cost, power generation online proportion and the like of each level, and dynamically calculate index data such as the annual average income amount, the annual generation net income, the annual income rate and the like of the distributed photovoltaic in 20 years after the distributed photovoltaic is put into operation.
According to the invention, the economic benefit measuring and calculating capability of the distributed photovoltaic slave planning, construction, operation and maintenance full life cycle can be improved, the economic benefit conditions of the current and future time period can be visually displayed, and the power-assisted distributed photovoltaic service can be efficiently developed.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be understood that the terms "comprises" and "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
In order to solve or improve the problems presented by the background, the invention provides a method for measuring and calculating the economic benefits of the full life cycle of a photovoltaic as shown in fig. 1, which comprises the following steps: s1, setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model; s2, constructing an economic benefit measuring and calculating framework based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model; and S3, obtaining economic benefit data based on the economic benefit measuring and calculating framework and the photovoltaic project parameters.
For S1, setting the power generation amount prediction model includes: predicting the month generating capacity by using an XGBoost algorithm; the data characteristics screened out by the characteristic engineering are combined based on weather, temperature, holidays and economic development factors to serve as model input parameters;
setting the generated power prediction model, including: predicting a daily power generation average load by using a LightGBM algorithm;
setting the project investment cost model, comprising: total cost of distributed project investment c=w (c0+c1); wherein W is the installed capacity of the distributed photovoltaic power generation project, c0 is the unit investment cost, and c1 is the unit operation and maintenance cost;
setting the project economic benefit model, which comprises the following steps: project annual income = self-consumption amount x comprehensive subsidy electricity price + on-line electricity amount x on-line electricity price; wherein, the self-power consumption= (first year power generation amount× (last year power generation+current year predicted power generation)/2) ×self-power consumption percentage; comprehensive subsidy electricity price= ((resident or enterprise electricity price) ×self-use percentage + (1-self-use percentage) ×desulfurization coal-fired electricity price); on-line electric quantity= (first year generated energy× (last year generated power+current year predicted generated power)/2× (1-percent of self-use).
For S2, constructing an economic benefit measuring architecture further includes: setting a data center to collect photovoltaic project parameters corresponding to distributed optical fiber projects in the area; the data center is further configured to support operations of the power generation amount prediction model, the power generation power prediction model, the project investment cost model, and the project economic benefit model.
For S3, the distributed optical fiber items include user exclusive items, and calculating the economic benefit data of the user exclusive items includes: estimating investment cost according to the user's digestion capacity, electricity price, building available effective area and site installation conditions; estimating the self-use percentage of the user power generation according to the annual power consumption and annual power generation of the user, and calculating project annual income according to the self-use price, the internet price and the annual internet power consumption; and calculating a project static investment recovery period by combining the project annual benefits with the investment cost so as to evaluate project economic feasibility.
The distributed optical fiber project comprises a financing lease investment project, and calculating the economic benefit data of the financing lease investment project comprises: calculating comprehensive investment cost according to enterprise financing conditions; estimating the self-use percentage of user power generation according to the annual power consumption and annual power generation of the enterprise, and calculating project annual income according to the self-use price, the internet price and the annual internet power consumption; and calculating a static investment recovery period through the comprehensive investment cost and the project annual income project to evaluate the project economic feasibility.
The method calculates the economic benefit data over a 20 year period.
The invention provides a photovoltaic full life cycle economic benefit measuring and calculating system as shown in fig. 2, which comprises:
a first module 1 for setting a power generation amount prediction model, a power generation power prediction model, a project investment cost model and a project economic benefit model;
a second module 2, configured to construct an economic benefit measuring and calculating architecture based on the power generation amount prediction model, the project investment cost model, and the project economic benefit model;
and the third module 3 is used for obtaining economic benefit data based on the economic benefit measuring and calculating architecture and photovoltaic project parameters.
The embodiment provides a distributed photovoltaic full life cycle economic benefit measuring and calculating method, which comprises the following steps:
1. building a power generation amount prediction model:
the XGBoost algorithm in the machine learning algorithm is used for predicting the monthly power generation amount, factors such as weather, temperature, holidays, economic development and the like are considered, and the data characteristics screened by the characteristic engineering are combined to serve as model input parameters. And selecting sample data for model calculation, and predicting an error rate histogram distribution diagram and a cumulative line diagram from a monthly power generation amount prediction model to analyze the model effectiveness.
2. And (3) constructing a generated power prediction model:
the method comprises the steps of selecting a LightGBM algorithm in a machine learning algorithm to predict daily power generation average load, screening and sorting characteristic data comprising air temperature and air flow, weather conditions, user power utilization time length and power utilization date based on two dimensions of weather parameters and user power utilization historical behaviors, and taking the characteristic data as model input parameters.
3. Project investment cost model construction:
the distributed project investment total cost (C) mainly includes an initial investment cost (C0) of the construction period and a system operation maintenance cost (C1) of the operation period. The distributed project investment total cost model is: c=w× (c0+c1), wherein W is the installed capacity of the distributed photovoltaic power generation project, C0 is the unit investment cost, and C1 is the unit operation and maintenance cost.
4. And (3) constructing a project economic benefit model:
the economic benefit of the distributed photovoltaic project is the sum of annual project benefits in the power generation years. The method for calculating the total economic benefit of the project comprises the following steps: project total benefit = first year project benefit + second year project benefit + … + nth year benefit, where n is the photovoltaic power generation duration in years;
the project annual income needs to be calculated by combining the spontaneous electricity consumption of the user, the residual online electricity consumption, the comprehensive subsidy electricity price and the online electricity price. The project year profit calculation method comprises the following steps: project annual income = self-consumption amount x comprehensive subsidy electricity price + on-line electricity amount x on-line electricity price;
the calculation method of each variable in the above formula is as follows:
(1) Comprehensive subsidy electricity price
Calculating comprehensive subsidy electricity price according to the user electricity generation self-use percentage, the user electricity use property (resident or enterprise) and the desulfurization coal-fired electricity price parameter, wherein the comprehensive subsidy electricity price= ((resident or enterprise electricity price) x self-use percentage + (1-self-use percentage) x desulfurization coal-fired electricity price);
(2) Self-power consumption
Calculating the spontaneous self-power consumption of the user according to the power generation prediction result data and the self-power consumption percentage of the user, wherein the self-power consumption is = (annual power generation is x (power generation of the last year+power generation predicted in the current year)/2) multiplied by the self-power consumption percentage;
(3) Internet power
And calculating the residual Internet surfing electric quantity of the user according to the power generation prediction result data and the user power generation self-use percentage, wherein the Internet surfing electric quantity is = (first year power generation is x (last year power generation+current year predicted power generation)/2) x (1-self-use percentage).
The first year generating capacity and the generating power which are related in the calculation formulas of the self-power consumption and the internet-surfing electric quantity are specifically:
(1) project annual energy production
Inquiring first annual theoretical generating capacity of 1kW according to parameters such as longitude and latitude, altitude, wind pressure, optimal inclination angle and the like of a geographical position where a power plant is located, wherein the first annual generating capacity of a project=1 kW first annual generating capacity×installed capacity;
(2) power generation
And calculating the generated power of the photovoltaic power station according to the generated power attenuation rate of the solar panel, wherein the generated power=1-the annual attenuation rate of the first year power is-2 to 25 years (n-1), and n is the service life of the photovoltaic (the theoretical service life of the solar panel is 25 years).
5. The economic benefit measuring and calculating system architecture is as follows:
and constructing a unified data warehouse center, converging data such as distributed photovoltaic project information, user electricity information and the like, and mainly storing a data model and analysis result data of the service by a database.
The annual income and the income ratio are automatically calculated through a distributed photovoltaic full life cycle economic benefit analysis related model according to the conditions of input installed capacity, online electricity price, average power generation utilization hour and the like.
(1) Measurement and calculation parameter input
After the region can be selected, parameters such as unit subsidy at each level, online electricity price, average operation and maintenance cost, disposable cost, interest rate, loan age, power generation and online proportion and the like are recorded.
(2) Investment income measuring and calculating
The annual average rate of return, annual average rate of return and the recovery cost period after the distributed photovoltaic power generation project is implemented are calculated in real time.
(3) Annual revenue measurement
And dynamically calculating the results of the power generation capacity, the annual power generation net income, the annual income rate and the like of each year of the photovoltaic power generation project within 20 years after the photovoltaic power generation project is put into operation. And the construction department or the distributed photovoltaic power generation project owners can know the investment income profile of the construction project according to the measuring and calculating result.
6. Economic benefit analysis:
the distributed photovoltaic power station needs to evaluate project economic feasibility by combining the self-operation condition of enterprises and project investment funds, and selects different business modes for investment construction, and the distributed photovoltaic mainly has two modes of independent investment and financing lease investment of users;
(1) The method comprises the steps that a user independently invests in projects, investment cost is estimated according to the consumption capacity, electricity price, building available effective area, site installation conditions and the like of the user, the self-use percentage of electricity generation of the user is estimated according to the annual electricity consumption, annual electricity generation amount and the like of the user, project annual income is calculated according to the self-use electricity price, internet electricity price, annual electricity surfing amount, annual electricity generation amount and the like, project annual income is calculated by combining project annual income with investment cost, and project economic feasibility is estimated;
(2) Financing and renting investment projects, financing is carried out according to enterprise credit, guarantor and the like, the enterprises and financing parties agree on the project investment pay-for-the-first proportion, the projects are paid by the enterprises for pay-for-the-first investment, and the rest investment funds are paid in stages through a financing and renting mode. Both parties agree on an installment payment period, a repayment mode, annual interest, commission and the like, and users pay according to the agreements. And calculating a static investment recovery period by integrating the investment cost and the project annual income project, and evaluating the project economic feasibility.
The embodiment provides an application process of a distributed photovoltaic economic benefit measuring and calculating method:
step 1: and (5) collecting sample data. The distributed photovoltaic economic benefit measuring and calculating various models can be accurately measured and calculated only by fully considering the difference between the region and the user type and referring to the latest data for model training. Thus, in applying the present method, it is necessary to collect relevant sample data required for model training.
Step 2: and (5) model training. Based on sample data, respectively training a power generation quantity prediction model, a power generation power prediction model, a project investment cost model and a project economic benefit model, so that the model is more applicable and more accurate.
Step 3: system architecture and development. According to the use scale and the current situation of the original related system, the model and the system architecture designed according to the invention are used for measuring and calculating the supporting system architecture, the built-in model, the development of required functions and the test verification.
Step 4: and initializing a model. Various parameters required by the model are imported into the system, the model is initialized, and the latest model is formed and is suitable for a distributed photovoltaic economic benefit measuring and calculating model in a local area.
Step 5: and (5) economic benefit analysis. And carrying out measurement and analysis application of each dimension of the distributed photovoltaic economic benefit based on the method by using the measurement and calculation support system.
Those of ordinary skill in the art will appreciate that the elements of the examples described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both, and that the elements of the examples have been described generally in terms of functionality in the foregoing description to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in this application, it should be understood that the division of units is merely a logic function division, and there may be other manners of division in practical implementation, for example, multiple units may be combined into one unit, one unit may be split into multiple units, or some features may be omitted.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention, and are intended to be included within the scope of the appended claims and description.
Claims (10)
1. The method for measuring and calculating the economic benefits of the full life cycle of the photovoltaic is characterized by comprising the following steps of:
setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model;
constructing an economic benefit measuring and calculating framework based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model;
and obtaining economic benefit data based on the economic benefit measuring and calculating architecture and the photovoltaic project parameters.
2. The method for measuring and calculating the economic benefit of the full life cycle of the photovoltaic system according to claim 1, wherein the step of setting the power generation amount prediction model comprises the following steps:
predicting the month generating capacity by using an XGBoost algorithm;
and the data characteristics screened out by the characteristic engineering are combined on the basis of weather, temperature, holidays and economic development factors to serve as model input parameters.
3. The method for measuring and calculating the economic benefit of the full life cycle of the photovoltaic system according to claim 2, wherein the step of setting the prediction model of the generated power comprises the following steps:
predicting a daily power generation average load by using a LightGBM algorithm;
the method comprises the steps of screening and sorting characteristic data comprising air temperature air flow, weather conditions, user electricity duration and electricity date based on two dimensions of weather parameters and user electricity history behaviors, and taking the characteristic data as model input parameters.
4. A method of photovoltaic full life cycle economic benefit measurement according to claim 3, wherein setting the project investment cost model comprises:
total cost of distributed project investment c=w (c0+c1); wherein W is the installed capacity of the distributed photovoltaic power generation project, c0 is the unit investment cost, and c1 is the unit operation and maintenance cost.
5. The method for measuring and calculating the economic benefit of the full life cycle of the photovoltaic system according to claim 4, wherein the step of setting the project economic benefit model comprises the following steps:
project annual income = self-consumption amount x comprehensive subsidy electricity price + on-line electricity amount x on-line electricity price;
wherein, the self-power consumption= (first year power generation amount× (last year power generation+current year predicted power generation)/2) ×self-power consumption percentage;
comprehensive subsidy electricity price= ((resident or enterprise electricity price) ×self-use percentage + (1-self-use percentage) ×desulfurization coal-fired electricity price);
on-line electric quantity= (first year generated energy× (last year generated power+current year predicted generated power)/2× (1-percent of self-use).
6. The method for measuring and calculating the economic benefit of the whole life cycle of the photovoltaic system according to claim 5, wherein the construction of the economic benefit measuring and calculating framework comprises the following steps:
setting a data center to collect photovoltaic project parameters corresponding to distributed optical fiber projects in the area;
the data center is further configured to support operations of the power generation amount prediction model, the power generation power prediction model, the project investment cost model, and the project economic benefit model.
7. The photovoltaic full life cycle economic benefit measurement method of claim 6, wherein the distributed fiber project comprises a user exclusive project, and calculating the economic benefit data for the user exclusive project comprises:
estimating investment cost according to the user's digestion capacity, electricity price, building available effective area and site installation conditions;
estimating the self-use percentage of the user power generation according to the annual power consumption and annual power generation of the user, and calculating project annual income according to the self-use price, the internet price and the annual internet power consumption;
and calculating a project static investment recovery period by combining the project annual benefits with the investment cost so as to evaluate project economic feasibility.
8. The photovoltaic full life cycle economic benefits measuring and calculating method of claim 6, wherein the distributed fiber project comprises a financing lease investment project, and calculating the economic benefits data of the financing lease investment project comprises:
calculating comprehensive investment cost according to enterprise financing conditions;
estimating the self-use percentage of user power generation according to the annual power consumption and annual power generation of the enterprise, and calculating project annual income according to the self-use price, the internet price and the annual internet power consumption;
and calculating a static investment recovery period through the comprehensive investment cost and the project annual income project to evaluate the project economic feasibility.
9. The photovoltaic full life cycle economic efficiency measurement component of claim 7 or 8, wherein the economic efficiency data is calculated over a 20 year period.
10. A photovoltaic full life cycle economic benefit measurement system, comprising:
the first module is used for setting a generating capacity prediction model, a generating power prediction model, a project investment cost model and a project economic benefit model;
the second module is used for constructing an economic benefit measuring and calculating framework based on the generating capacity prediction model, the generating power prediction model, the project investment cost model and the project economic benefit model;
and the third module is used for obtaining economic benefit data based on the economic benefit measuring and calculating framework and the photovoltaic project parameters.
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