CN113657789A - Distributed photovoltaic roof resource multi-dimensional evaluation method - Google Patents
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Abstract
The invention relates to a distributed photovoltaic roof resource multi-dimensional evaluation method which evaluates distributed photovoltaic roof resources through multiple dimensions such as natural environment attributes, building attributes and energy utilization attributes, wherein evaluation contents comprise key indexes such as maximum/economic installed capacity, generated energy, spontaneous self-use proportion, investment estimation, annual income and static investment recovery period. Compared with the traditional roof resource assessment method, the method is more comprehensive and more precise. Besides the maximum machine-installable capacity, the maximum economic installation capacity can be provided, the screening of high-quality roof resources is facilitated, and meanwhile the economic efficiency of the project is improved.
Description
Technical Field
The invention belongs to the technical field of new energy power generation, and particularly relates to a distributed photovoltaic roof resource multi-dimensional evaluation method.
Background
The distributed photovoltaic power generation system is mature in technology, flexible in deployment, close to users and good in economic benefit, and is an important technical means for realizing carbon peak reaching and carbon neutralization in China. In order to promote the development of distributed photovoltaic, roof resources need to be evaluated at first, so that investors can conveniently screen projects, and the economy of the projects is improved. The conventional roof resource assessment is usually focused on factors such as illumination resources, roof area, inclination angle and orientation, lacks assessment on an electricity load curve and photovoltaic spontaneous self-use proportion and influences of shading and dust accumulation on photovoltaic power generation, has insufficient comprehensive dimensionality, is not refined in analysis, and is difficult to provide effective support for screening and assessment of photovoltaic projects.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a distributed photovoltaic roof resource multi-dimensional evaluation method, which evaluates the distributed photovoltaic roof resources through multiple dimensions such as natural environment attributes, building attributes and energy consumption attributes, wherein evaluation contents comprise key indexes such as maximum/economic installed capacity, generated energy, spontaneous self-consumption proportion, investment estimation, annual income and static investment recovery period.
The technical problem to be solved by the invention is realized by adopting the following technical scheme:
a distributed photovoltaic roof resource multi-dimensional evaluation method comprises the following steps:
step 1, acquiring a city where a distributed photovoltaic roof is located and longitude and latitude information of the city, and acquiring solar radiation data of the city where the roof is located through meteorological station data;
step 2, evaluating influence coefficients of air pollution and dust deposition on photovoltaic power generation capacity according to different pollution degree grades by combining air pollution distribution conditions accumulated by a power system;
step 3, acquiring available area of the roof, type of the roof, orientation and inclination angle information through on-site investigation, determining a photovoltaic inclination angle and orientation, applying PVsyst photovoltaic power generation evaluation software to evaluate photovoltaic power generation of the roof, and correcting a power generation result by combining influence coefficients of air pollution and dust deposition on the photovoltaic power generation;
step 4, acquiring data of the type, load, design life and service life of the roof through field investigation, and evaluating the cost required by roof modification in a photovoltaic power generation period for many years;
step 5, obtaining the maximum machine-installable capacity according to the available area of the roof, the capacity of the transformer and the voltage grade factors;
step 6, acquiring user load, electricity price, photovoltaic internet electricity price data and a recent typical daily load curve of the user;
step 7, simulating a typical daily photovoltaic power generation load curve of each month based on solar radiation data and a PVsyst photovoltaic power generation evaluation algorithm, comparing the photovoltaic power generation curve with the load curve, analyzing to obtain local photovoltaic power consumption, further obtaining a spontaneous self-consumption proportion, and evaluating photovoltaic power generation income according to project power consumption price and photovoltaic internet power price;
step 8, calculating the investment of the photovoltaic system based on the maximum machine-installable capacity, and taking the calculated investment plus the roof reinforcement and reconstruction investment as the total investment of the photovoltaic system to obtain a project static investment recovery period;
step 9, setting the longest static investment recovery period acceptable by the project, reducing the installed photovoltaic capacity if the investment recovery period under the maximum installed capacity is larger than the longest static investment recovery period acceptable by the set project, and returning to the step 7, otherwise, performing the step 10;
and step 10, calculating the maximum photovoltaic installed capacity and the maximum economic installed capacity of the roof resource, and the spontaneous self-use proportion, the generated energy, the income and the project static investment recovery period under different capacities.
Moreover, the specific implementation method of step 5 is as follows:
PPVmax＝min(Mroof/β，0.7cosαSdt，Pv)
wherein, PPVmaxMaximum installed photovoltaic capacity of the roof, MroofRepresents the area of the roof; beta represents a roof area availability factor; 0.7 cos. alpha.Sdt70% of the transformer capacity; pvThe photovoltaic capacity limit of different voltage grades is represented, the maximum machine-installable capacity cannot exceed 70% of the capacity of the transformer, the power utilization voltage grade is 220V, and the capacity does not exceed 8 kW; the power consumption voltage grade is 380V, and the capacity does not exceed 100 kW; the capacity is not more than 2MW when the power voltage is accessed with the voltage grade of 10kV and 380V or below, and the capacity is not more than 6MW when the 10kV is accessed; the power consumption voltage level is 35kV, and the capacity is more than or equal to 6 MW.
In step 6, the daily load curve is calculated by: load data of a working day and a rest day of a sunny day in each month and a plurality of load data acquisition points every day are selected, and a photovoltaic typical day power generation load curve in each month is simulated based on solar radiation data and a PVsyst photovoltaic power generation evaluation algorithm.
Moreover, the method for calculating the profit in the step 7 is as follows: and determining the photovoltaic power generation income according to the electricity utilization price, the internet surfing price and the local consumption and internet surfing conditions of the photovoltaic power generation.
Moreover, the specific calculation method for calculating the investment of the photovoltaic system in the step 8 is as follows: unit power photovoltaic system investment photovoltaic installed capacity; the specific calculation method of the roof reinforcement and reconstruction investment comprises the following steps: investment per unit area roof renovation.
Moreover, the specific calculation method of the static investment recovery period in the step 8 is as follows: investment/profit.
Furthermore, the maximum economic installed capacity in step 10 is: the maximum available capacity is realized on the premise of meeting the economic efficiency of the project.
The invention has the advantages and positive effects that:
1. according to the method, the distributed photovoltaic roof resources are evaluated through multiple dimensions such as natural environment attributes and building attributes, and the evaluation contents comprise key indexes such as maximum/economic installed capacity, generated energy, spontaneous self-use proportion, investment estimation, annual income and static investment recovery period. Compared with the traditional roof resource assessment method, the method is more comprehensive and more precise. Besides the maximum machine-installable capacity, the maximum economic installation capacity can be provided, the screening of high-quality roof resources is facilitated, and meanwhile the economic efficiency of the project is improved.
2. According to the method, the distributed photovoltaic roof resources are evaluated through the natural environment attributes, the influence of dust accumulation on photovoltaic power generation capacity evaluation is considered, evaluation consideration factors are more comprehensive, and the power generation capacity evaluation result is more accurate than that of a traditional evaluation method.
3. According to the invention, the distributed photovoltaic roof resources are evaluated through the building attributes, and the influence of shielding on the available area of the roof is considered; in the aspect of energy consumption property, the influence of the transformer capacity and the voltage level on the maximum photovoltaic installed capacity is considered, and the maximum photovoltaic installed capacity evaluation result is more accurate.
4. According to the method, the distributed photovoltaic roof resources are evaluated by using the energy attributes, the influences of project load curves and loads of the roof and the on-line electricity price are considered, and the photovoltaic self-utilization proportion and the benefits are evaluated by combining different photovoltaic installed capacities and typical power generation loads
Drawings
FIG. 1 is a schematic diagram of the present invention for establishing an evaluation model.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
A multidimensional evaluation method for distributed photovoltaic roof resources, as shown in fig. 1, includes the following steps:
step 1, acquiring a city where a distributed photovoltaic roof is located and longitude and latitude information of the city, and acquiring solar radiation data of the city where the roof is located through meteorological station data.
And 2, evaluating the influence coefficients of air pollution and dust deposition on the photovoltaic power generation capacity by combining the air pollution distribution condition accumulated by the power system and grading according to different pollution degrees.
And 3, acquiring the available area of the roof, the type of the roof, the orientation and the inclination angle information through on-site investigation, determining the photovoltaic inclination angle and the orientation, applying PVsyst photovoltaic power generation evaluation software to evaluate the photovoltaic power generation amount of the roof, and correcting the power generation amount result by combining the influence coefficients of air pollution and dust deposition on the photovoltaic power generation amount.
And 4, acquiring the data of the type, the load, the design life and the used age limit of the roof through field investigation, and evaluating the cost required by roof reconstruction within a photovoltaic power generation period of 20 years.
And 5, obtaining the maximum installed capacity according to the available area of the roof, the capacity of the transformer and the voltage grade factor.
PPVmax＝min(Mroof/β，0.7cosαSdt，Pv)
Wherein, PPVmaxMaximum installed photovoltaic capacity of the roof, MroofRepresents the area of the roof; beta represents a roof area availability factor; 0.7 cos. alpha.Sdt70% of the transformer capacity; pvThe photovoltaic capacity limit of different voltage grades is represented, the maximum machine-installable capacity cannot exceed 70% of the capacity of the transformer, the power utilization voltage grade is 220V, and the capacity does not exceed 8 kW; the power consumption voltage grade is 380V, and the capacity does not exceed 100 kW; the capacity is not more than 2MW when the power voltage is accessed with the voltage grade of 10kV and 380V or below, and the capacity is not more than 6MW when the 10kV is accessed; the power consumption voltage level is 35kV, and the capacity is more than or equal to 6 MW.
And 6, acquiring the load of the user, the electricity price, the photovoltaic internet electricity price data and the typical daily load curve of the user in the last 1 year.
The typical daily load curve selects load data of a working day and a rest day of a sunny day in each month, 96 load data acquisition points in each day and at least 1 load data in each hour. Such as monthly second wednesday, sunday load data. Simulating a monthly photovoltaic typical daily power generation load curve based on solar radiation data and a PVsyst photovoltaic power generation evaluation algorithm
And 7, simulating a typical daily photovoltaic power generation load curve of each month based on solar radiation data and a PVsyst photovoltaic power generation evaluation algorithm, comparing the photovoltaic power generation curve with the load curve, analyzing to obtain local photovoltaic power consumption, further obtaining a spontaneous self-consumption proportion, and evaluating photovoltaic power generation benefits according to project power consumption prices and photovoltaic internet power prices.
And determining the photovoltaic power generation income according to the electricity utilization price, the internet surfing price and the local consumption and internet surfing conditions of the photovoltaic power generation.
And 8, calculating the investment of the photovoltaic system based on the maximum machine-installable capacity, and taking the calculated investment plus the roof reinforcement and reconstruction investment as the total investment of the photovoltaic system to obtain the static investment recovery period of the project.
The investment of a photovoltaic power generation system is equal to the investment of a unit power photovoltaic system and the installed photovoltaic capacity; the specific calculation method of the roof reinforcement and reconstruction investment comprises the following steps: investment per unit area roof renovation.
Static payback period is investment/revenue.
And 9, setting the longest static investment recovery period acceptable by the project, reducing the installed photovoltaic capacity if the investment recovery period under the maximum installed capacity is larger than the longest static investment recovery period acceptable by the set project, and returning to the step 7, otherwise, performing the step 10.
And step 10, calculating the maximum photovoltaic installed capacity and the maximum economic installed capacity of the roof resource, and the spontaneous self-use proportion, the generated energy, the income and the project static investment recovery period under different capacities.
The maximum economic installed capacity is: on the premise of meeting the economic performance of the project (the patent of the invention takes a static investment recovery period as an example, the period does not exceed 6 years), the maximum machine-installable capacity is realized. Different installed capacities, different power generation loads and different spontaneous self-use proportions can also lead to different project economy.
It should be emphasized that the embodiments described herein are illustrative rather than restrictive, and thus the present invention is not limited to the embodiments described in the detailed description, but also includes other embodiments that can be derived from the technical solutions of the present invention by those skilled in the art.
Claims (7)
1. A distributed photovoltaic roof resource multidimensional assessment method is characterized in that: the method comprises the following steps:
step 1, acquiring a city where a distributed photovoltaic roof is located and longitude and latitude information of the city, and acquiring solar radiation data of the city where the roof is located through meteorological station data;
step 2, evaluating influence coefficients of air pollution and dust deposition on photovoltaic power generation capacity according to different pollution degree grades by combining air pollution distribution conditions accumulated by a power system;
step 3, acquiring available area of the roof, type of the roof, orientation and inclination angle information through on-site investigation, determining a photovoltaic inclination angle and orientation, applying PVsyst photovoltaic power generation evaluation software to evaluate photovoltaic power generation of the roof, and correcting a power generation result by combining influence coefficients of air pollution and dust deposition on the photovoltaic power generation;
step 4, acquiring data of the type, load, design life and service life of the roof through field investigation, and evaluating the cost required by roof modification in a photovoltaic power generation period for many years;
step 5, obtaining the maximum machine-installable capacity according to the available area of the roof, the capacity of the transformer and the voltage grade factors;
step 6, acquiring user load, electricity price, photovoltaic internet electricity price data and a recent typical daily load curve of the user;
step 7, simulating a typical daily photovoltaic power generation load curve of each month based on solar radiation data and a PVsyst photovoltaic power generation evaluation algorithm, comparing the photovoltaic power generation curve with the load curve, analyzing to obtain local photovoltaic power consumption, further obtaining a spontaneous self-consumption proportion, and evaluating photovoltaic power generation income according to project power consumption price and photovoltaic internet power price;
step 8, calculating the investment of the photovoltaic system based on the maximum machine-installable capacity, and taking the calculated investment plus the roof reinforcement and reconstruction investment as the total investment of the photovoltaic system to obtain a project static investment recovery period;
step 9, setting the longest static investment recovery period acceptable by the project, reducing the installed photovoltaic capacity if the investment recovery period under the maximum installed capacity is larger than the longest static investment recovery period acceptable by the set project, and returning to the step 7, otherwise, performing the step 10;
and step 10, calculating the maximum photovoltaic installed capacity and the maximum economic installed capacity of the roof resource, and the spontaneous self-use proportion, the generated energy, the income and the project static investment recovery period under different capacities.
2. The multidimensional distributed photovoltaic roof resource assessment method according to claim 1, wherein: the specific implementation method of the step 5 is as follows:
PPVmax＝min(Mroof/β，0.7cosαSdt，Pv)
wherein, PPVmaxMaximum installed photovoltaic capacity of the roof, MroofRepresents the area of the roof; beta represents a roof area availability factor; 0.7cos alpha Sdt70% of the transformer capacity; pvThe photovoltaic capacity limit of different voltage grades is represented, the maximum machine-installable capacity cannot exceed 70% of the capacity of the transformer, the power utilization voltage grade is 220V, and the capacity does not exceed 8 kW; the power consumption voltage grade is 380V, and the capacity does not exceed 100 kW; the capacity is not more than 2MW when the power voltage is accessed with the voltage grade of 10kV and 380V or below, and the capacity is not more than 6MW when the 10kV is accessed; the power utilization voltage grade is 35kY, and the capacity is more than or equal to 6 MW.
3. The multidimensional assessment method for the distributed photovoltaic roof resource according to claim 4, wherein: the calculation method of the daily load curve in the step 6 comprises the following steps: load data of a working day and a rest day of a sunny day in each month and a plurality of load data acquisition points every day are selected, and a photovoltaic typical day power generation load curve in each month is simulated based on solar radiation data and a PVsyst photovoltaic power generation evaluation algorithm.
4. The multidimensional assessment method for the distributed photovoltaic roof resource according to claim 4, wherein: the method for calculating the profit in the step 7 comprises the following steps: and determining the photovoltaic power generation income according to the electricity utilization price, the internet surfing price and the local consumption and internet surfing conditions of the photovoltaic power generation.
5. The multidimensional distributed photovoltaic roof resource assessment method according to claim 1, wherein: the specific calculation method for calculating the investment of the photovoltaic system in the step 8 comprises the following steps: unit power photovoltaic system investment photovoltaic installed capacity; the specific calculation method of the roof reinforcement and reconstruction investment comprises the following steps: investment per unit area roof renovation.
6. The multidimensional distributed photovoltaic roof resource assessment method according to claim 1, wherein: the specific calculation method of the static investment recovery period in the step 8 comprises the following steps: investment/profit.
7. The multidimensional distributed photovoltaic roof resource assessment method according to claim 1, wherein: the maximum economic installed capacity in the step 10 is as follows: the maximum available capacity is realized on the premise of meeting the economic efficiency of the project.
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