CN104200289A - Distributed photovoltaic installed capacity prediction method based on investment return rate - Google Patents

Abstract

The invention discloses a distributed photovoltaic installed capacity prediction method based on investment return rate. The distributed photovoltaic installed capacity prediction method comprises the following steps: determining roof resource state in a certain area; determining photovoltaic resource development potential in the area; establishing a distributed photovoltaic generating project benefit analytic model; predicting the distributed photovoltaic project annual investment return rate according to real-time market classification; utilizing the linear regression analysis method to establish a relationship model of the project annual investment return rate and the distributed photovoltaic popularizing rate; predicting the distributed photovoltaic installed capacity through the popularizing rate according to the roof resource state. Based on distributed photovoltaic project investment return rate, the distributed photovoltaic installed capacity prediction method, provided by the invention, fully complies with a current photovoltaic market mechanism, provides a new prediction method by taking photovoltaic as a new energy, fills in the gap of prediction of distributed energy, and provides reference for consideration of electric grid planning of distributed power supply.

Description

A kind of distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment

Technical field

The present invention relates to the Electric Power Network Planning technical field of distributed power source, be specifically related to a kind of distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment.

Background technology

Distributed power generation small investment, flexible operation, it is as the quality of power supply and the reliability that can strengthen electrical network of supplementing of large electrical network, and will be also the great energy system that centralized generating and distributed power generation match future.Distributed generation technology is varied at present, common are several forms such as photovoltaic generation, wind-power electricity generation and miniature gas turbine, and photovoltaic generation the most potential distributed power generation resource beyond doubt, because it has following advantage:

1) effectively utilize Roof Resources, greatly save land resource, not only operation management is comparatively simple, and individual and industry and commerce all can be installed photovoltaic generating system;

2) photovoltaic is widely distributed and the distributed power generation resource of the exploitativeness that possesses skills, and China's most areas solar energy resources is abundant, considerable benefit;

3) according to the national strategy of sustainable development, Energy restructuring strategy, photovoltaic industry is that country actively promotes the important industry of advocating, and has drafted clear and definite development plan, is the important directions of future development.

Therefore, distributed photovoltaic power generation is predicted not only significant to theCourse of PV Industry, also be can be and consider that the Electric Power Network Planning of distributed power source provides reference.

Summary of the invention

The object of the present invention is to provide a kind of distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment, fully follow current photovoltaic market mechanism, for photovoltaic has been made new Forecasting Methodology as a kind of development of novel energy, fill up the blank of distributed energy prediction, overcome the shortcoming that traditional Electric Power Network Planning only relies on load prediction, effectively improve the reliability of Electric Power Network Planning, for Utilities Electric Co. provides reference to the Electric Power Network Planning of considering distributed power source.

The technical scheme that realizes above-mentioned purpose is:

A distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment, comprises the following steps:

Step S1, determines somewhere Roof Resources situation;

Step S2, determines somewhere photovoltaic resources potentiality to be exploited;

Step S3, sets up distributed photovoltaic power generation Project Benefit model, is shown below:

$C=C_{\mathrm{ivs}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{op}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{fn}}---\left(1\right)$

I＝I _u+I _p+I _b (2)

$\mathrm{\η}=\frac{I_n+I_p+I_b-C_{\mathrm{op}}-C_{\mathrm{fn}}}{C_{\mathrm{ivs}}}\×100\%---\left(3\right)$

$\stackrel{\‾}{\mathrm{\η}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\η}}_i}{n}---\left(4\right)$

Wherein: C _ivsfor system Construction cost, C _opfor operation management cost, C _fnfor financial expense, C is distributed photovoltaic project total cost; I _ufor electricity consumption income, I _pfor power selling income, I _bfor fiscal subsidy, I is gross income; η is project year rate of return on investment; for the average investment return rate in the whole Project in Operation phase;

Step S4, classifies according to project management main body, then according to Real-time markets situation, and classification prediction distribution formula photovoltaic project year rate of return on investment;

Step S5, according to market universal law, utilizes linear regression analysis method, set up item year rate of return on investment and distributed photovoltaic popularity rate relational model;

Step S6, according to Roof Resources situation, the installed capacity of prediction distribution formula photovoltaic.

The above-mentioned distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment, wherein, in step S2, described somewhere photovoltaic resources potentiality to be exploited is according to the solar radiation condition of this area, Roof Resources and the measuring and calculating of distributed photovoltaic system effectiveness.

The above-mentioned distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment, wherein, in step S4, described project management main body comprises citizens and legal persons.

Adopt technical scheme of the present invention, can be achieved as follows beneficial effect: the present invention is directed to the research of distributed photovoltaic power generation installed capacity fundamentals of forecasting, set up the Forecasting Methodology based on rate of return on investment according to market discipline, for the Electric Power Network Planning of considering distributed power source provides reference, optimize resource distribution:

(1) distributed photovoltaic power generation project has been set up to Benefit Model, can carry out the project evaluation to distributed photovoltaic power generation project accordingly, as the judging basis of project feasibility;

(2) introduce the classification discussion to distributed photovoltaic project, the operation conditions such as individual and the distributed photovoltaic project construction operation cost of industry and commerce, electricity rates, subsidy policy are variant, cause project yield difference, therefore be necessary to be divided into individual and industry and commerce two classes and manage main bodys and analyze, also improved the accuracy of predicting;

(3) impact that the development of considering distributed power source produces operation of power networks, has overcome traditional Electric Power Network Planning and has only relied on the shortcoming of load prediction, has effectively improved the reliability of Electric Power Network Planning.

Brief description of the drawings

Fig. 1 is the process flow diagram of distributed photovoltaic installed capacity Forecasting Methodology of the present invention;

Fig. 2 is individual distributed photovoltaic power generation rate of return on investment trend prediction (2014-2020);

Fig. 3 is industry and commerce distributed photovoltaic power generation rate of return on investment trend prediction (2014-2020);

Fig. 4 is 2014-2020 Shanghai City distributed photovoltaic power generation installed capacity prediction (unit: ten thousand kW).

Embodiment

Below in conjunction with accompanying drawing, the invention will be further described.

Refer to Fig. 1, a kind of distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment of the present invention, comprises the following steps:

Step S1, determines somewhere Roof Resources situation;

Step S2, determines somewhere photovoltaic resources potentiality to be exploited; Somewhere photovoltaic resources potentiality to be exploited is according to the solar radiation condition of this area, Roof Resources and the measuring and calculating of distributed photovoltaic system effectiveness;

Step S3, sets up distributed photovoltaic power generation Project Benefit model, is shown below:

$C=C_{\mathrm{ivs}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{op}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{fn}}---\left(1\right)$

I＝I _u+I _p+I _b (2)

$\mathrm{\η}=\frac{I_n+I_p+I_b-C_{\mathrm{op}}-C_{\mathrm{fn}}}{C_{\mathrm{ivs}}}\×100\%---\left(3\right)$

$\stackrel{\‾}{\mathrm{\η}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\η}}_i}{n}---\left(4\right)$

Wherein: C _ivsfor system Construction cost, C _opfor operation management cost, C _fnfor financial expense, C is distributed photovoltaic project total cost; I _ufor electricity consumption income, I _pfor power selling income, I _bfor fiscal subsidy, I is gross income; η is project year rate of return on investment; for the average investment return rate in the whole Project in Operation phase;

Step S4, classifies according to project management main body, then according to Real-time markets situation, and classification prediction distribution formula photovoltaic project year rate of return on investment; Because the operation conditions such as the distributed photovoltaic project construction operation cost of i.e. individual and the industry and commerce of citizens and legal persons, electricity rates, subsidy policy are variant, cause project yield difference, be therefore necessary to be divided into citizens and legal persons's two classes operation main bodys to analyze;

Step S5, according to market universal law, utilizes linear regression analysis method, set up item year rate of return on investment and distributed photovoltaic popularity rate relational model;

Step S6, according to Roof Resources situation, the installed capacity of prediction distribution formula photovoltaic.

Below with a concrete case explanation:

Selecting District of Shanghai is example,

Step S1, determines District of Shanghai Roof Resources situation, according to statistics, and the existing approximately 200,000,000 square metres of Roof Resources in Shanghai, wherein individual house accounts for 70%, and industry and commerce accounts for 30%;

Step S2, determines District of Shanghai photovoltaic resources potentiality to be exploited, and the average annual solar radiation quantity in Shanghai is 4758MJ/m ², District of Shanghai for many years monthly average year radiation scale as table 1:

Table 1

Have an appointment the at present building roof resource of 200,000,000 square metres of Shanghai City, if building roof is all utilized as distributed photovoltaic power generation, photovoltaic generating system efficiency average out to 15% at present, with the average annual solar radiation quantity in District of Shanghai, the annual average power generation of containing will reach 396.5 hundred million kWh.

Step S3, sets up distributed photovoltaic power generation Project Benefit model, is shown below:

$C=C_{\mathrm{ivs}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{op}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{fn}}---\left(1\right)$

I＝I _u+I _p+I _b (2)

$\mathrm{\η}=\frac{I_n+I_p+I_b-C_{\mathrm{op}}-C_{\mathrm{fn}}}{C_{\mathrm{ivs}}}\×100\%---\left(3\right)$

$\stackrel{\‾}{\mathrm{\η}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\η}}_i}{n}---\left(4\right)$

In formula: C _ivsfor system Construction cost, C _opfor operation management cost, C _fnfor financial expense, C is distributed photovoltaic project total cost; I _ufor electricity consumption income, I _pfor power selling income, I _bfor fiscal subsidy, I is gross income; η is project year rate of return on investment; for the average investment return rate in the whole Project in Operation phase.

Step S4, classifies according to project management main body, then according to Real-time markets situation, and classification prediction distribution formula photovoltaic project year rate of return on investment, taking Shanghai Residents individual and industry and commerce as example:

1. individual distributed photovoltaic power generation system benefit is analyzed

Project management main body is citizen, and taking Shanghai 3kW resident individual distributed photovoltaic as example, estimation conditions is as table 2:

Project	Numerical value	Project	Numerical value
				Capacity	3kW	Year generating dutation at full capacity	1000h
Unit price	10 yuan/W	Personal ratio	40％
				Gross investment	30000 yuan	Year operation maintenance rate	2％
The operation phase	20 years	Value-added tax rate	17％
				Salvage value of fixed assets rate	5％	Attenuation rate (latter 10 years)	10％

Table 2

At present, Shanghai City distributed photovoltaic power generation rate for incorporation into the power network is 0.4523 yuan/kWh (containing tax, lower same), 0.42 yuan/kWh of state subsidies, 0.4 yuan/kWh of local subsidy.Because individual can not open VAT invoice, when being defined in clearing, Shanghai City directly settles accounts according to the tax rate price of deduction VAT invoice, and rate for incorporation into the power network is 0.38658 yuan/kWh, 0.359 yuan/kWh of state subsidies, 0.34188 yuan/kWh of local subsidy.Resident Electricity Price adopts ladder tou power price, because of photovoltaic generating system generating on daytime, resident's electricity consumption on daytime, therefore adopt 0.617 yuan/kWh of first grade of peak period electricity price.Calculate thus 3kW people's distributed photovoltaic project 20 years operation phase income, if table 3 is 3kW people's distributed photovoltaic evaluating project economic benefit, table 4 be 3kW people's distributed photovoltaic project year return rate table:

Project	Numerical value	Project	Numerical value
				Gross generation	57000kWh	Overall maintenance cost	12000 yuan
Electricity consumption income	14067.6 first	Gross profit	12379.836 first
				Power selling income (after-tax)	13221.036 first	Average year profit	618.99 first
Subsidy revenue (after-tax)	25591.2 first	Period of cost recovery	13.5

Table 3

	1-5	6-10	10-20	Average annual return
					Year return rate	9.8％	6.38％	5.54％	6.82％

Table 4

2. industry and commerce distributed photovoltaic power generation performance analysis

Project management main body is legal person, taking Shanghai 2MW distributed photovoltaic power generation as example, calculates financial condition as table 5:

Table 5

Enterprise whole year is 0.86 yuan/degree of average electricity price in the daytime, and rate for incorporation into the power network and state subsidies are identical with individual distributed project, and local subsidy is 0.25 yuan/kWh.Calculate thus 2MW distributed photovoltaic power generation Project Benefit, if table 6 is that 2MW distributed photovoltaic evaluating project economic benefit, table 7 are 2MW distributed photovoltaic project year return rate:

Table 6

	1-5	5-10	10-20	21-25	Average annual return
						Year return rate	13.31％	10.63％	9.17％	8.14％	10.01％

Table 7

Step S5, utilizes linear regression analysis method, set up item year rate of return on investment and distributed photovoltaic popularity rate relational model:

According to market discipline, the development scale of distributed photovoltaic power generation project and its rate of return on investment have inevitable relation, if return rate is high, certainly will attract more investments, and distributed photovoltaic power generation is more universal.Therefore by the tendency of distributed photovoltaic power generation equipment rate, can predict its installed capacity.

At this, can simplify equipment rate and project popularity rate is linear relationship.When return rate reaches 100%, the investment payback time is while being 1 year, and distributed photovoltaic power generation project realizes comprehensively universal, and roof utilization factor reaches the Roof Resources of 100%, 2 hundred million square metre can realize 2,000 ten thousand kW installed capacitys.Because individual is distributed different from the distributed rate of return on investment of industry and commerce, and individual distributed development scale is less at present, therefore sets up model according to industry and commerce distributed photovoltaic, to distributed same being suitable for of individual.

Shanghai City distributed photovoltaic power generation installed capacity 18.9 ten thousand kW in 2013, popularity rate is 3.15%, year return rate 8.74%, can obtain according to linear regression method thus:

k＝1.06125η-0.06125 (5)

Wherein, k is project popularity rate, and η is equipment rate.When return rate is lower than 5.77% time, installation amount can be ignored.

In distributed photovoltaic power generation project, photovoltaic module accounts for 60% of gross investment, it is the principal element that affects Project Benefit, along with the continuous breakthrough of photovoltaic module technology, the lower general who has surrendered of photovoltaic generation project initial outlay became the principal element that affects distributed photovoltaic power generation equipment rate in recent years.The variation tendency of distributed photovoltaic power generation project return rate can analyze initial outlay with every 5%, 10%, 15% speed decline time.If Fig. 2 is the trend prediction of 2014-2020 individual distributed photovoltaic power generation rate of return on investment; Fig. 3 is the trend prediction of 2014-2020 industry and commerce distributed photovoltaic power generation rate of return on investment.

Step S6, according to Roof Resources situation, the installed capacity of prediction distribution formula photovoltaic:

In the Roof Resources of 200,000,000 square metres, Shanghai, individual house accounts for 70%, and industry and commerce accounts for 30%, can calculate respectively distributed photovoltaic power generation installed capacity under high, medium and low rate of rise, as Fig. 4.

According to medium velocity forecast of growth, Shanghai City distributed photovoltaic power generation installed capacity in 2014 is about 42.54 ten thousand kW, and the installed capacity of the year two thousand twenty distributed photovoltaic can reach 234.3 ten thousand kW.

As fully visible, the present invention is directed to the research of distributed photovoltaic power generation installed capacity fundamentals of forecasting, set up the Forecasting Methodology based on rate of return on investment according to market discipline, for the Electric Power Network Planning of considering distributed power source provides reference, optimized resource distribution:

Above embodiment is used for illustrative purposes only, but not limitation of the present invention, person skilled in the relevant technique, without departing from the spirit and scope of the present invention, can also make various conversion or modification, therefore all technical schemes that are equal to also should belong to category of the present invention, should be limited by each claim.

Claims (3)

1. the distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment, is characterized in that, comprises the following steps:

Step S1, determines somewhere Roof Resources situation;

Step S2, determines somewhere photovoltaic resources potentiality to be exploited;

Step S3, sets up distributed photovoltaic power generation Project Benefit model, is shown below:

$C=C_{\mathrm{ivs}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{op}}+\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{C}_{\mathrm{fn}}---\left(1\right)$

I＝I _u+I _p+I _b (2)

$\mathrm{\η}=\frac{I_n+I_p+I_b-C_{\mathrm{op}}-C_{\mathrm{fn}}}{C_{\mathrm{ivs}}}\×100\%---\left(3\right)$

$\stackrel{\‾}{\mathrm{\η}}=\frac{\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\η}}_i}{n}---\left(4\right)$

Wherein: C _ivsfor system Construction cost, C _opfor operation management cost, C _fnfor financial expense, C is distributed photovoltaic project total cost; I _ufor electricity consumption income, I _pfor power selling income, I _bfor fiscal subsidy, I is gross income; η is project year rate of return on investment; for the average investment return rate in the whole Project in Operation phase;

Step S4, classifies according to project management main body, then according to Real-time markets situation, and classification prediction distribution formula photovoltaic project year rate of return on investment;

Step S5, according to market universal law, utilizes linear regression analysis method, set up item year rate of return on investment and distributed photovoltaic popularity rate relational model;

Step S6, according to Roof Resources situation, the installed capacity of prediction distribution formula photovoltaic.

2. the distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment according to claim 1, it is characterized in that, in step S2, described somewhere photovoltaic resources potentiality to be exploited is according to the solar radiation condition of this area, Roof Resources and the measuring and calculating of distributed photovoltaic system effectiveness.

3. the distributed photovoltaic installed capacity Forecasting Methodology based on rate of return on investment according to claim 1, is characterized in that, in step S4, described project management main body comprises citizens and legal persons.