Photovoltaic resource assessment optimization method and system based on historical meteorological data

Abstract

The invention provides a photovoltaic resource assessment optimization method and system based on historical meteorological data. The photovoltaic resource assessment optimization method comprises the following steps: 1) acquiring the historical meteorological data on a national scale, and computing and archiving the data and converting the form of the data into a data form satisfying the requirement of mapping so as to provide the data source for the whole mapping function; 2) selecting an area on a satellite map, taking the longitude and the latitude of the coordinate point of a diagonal point within the selected area range as the parameters, and then calling a mapping interface in a background service program; 3) using a mapping interface function for background service to inquire the longitude, the latitude and the total irradiance data required by mapping of the selected area, and using the related command of an NCL (The NCAR Command Language) mapping tool to generate a resource distribution map; and 4) loading the resource distribution map, superposing the resource distribution map above the map in a semi-transparent mode, and checking the resource distribution situation by means of combination of the map. The photovoltaic resource assessment optimization method and system based on historical meteorological data can provide a creative assessment scheme for a user, and can greatly improve the efficiency of assessment, and can reduce the assessment time and the assessment cost.

Description

technical field [0001] The invention belongs to the field of photovoltaic power station design and construction, and in particular relates to a method and system for evaluating and optimizing photovoltaic resources based on historical meteorological data. Background technique [0002] In recent years, with the country's strong advocacy and support for clean energy, photovoltaic power generation has played an important role in the field of clean energy, occupying an important position, and the construction of photovoltaic power stations has also flourished. The entire life cycle of photovoltaic power plants can be roughly divided into four stages: feasibility study stage, design stage, construction stage, and production and operation stage. In the feasibility study stage, it is necessary to accurately evaluate the photovoltaic resources. The quality of photovoltaic resources determines the power generation capacity of the power station to a large extent, and also affects the ...

AI Technical Summary

Problems solved by technology

[0005] 1. Consuming a lot of manpower and material resources: It often takes a lot of time and manpower to go to the site of the planned power station for on-site survey

[0006] 2. The data collection method is inefficient: directly install irradiance meters and other equipment on site, observe and record data for a long time, which is inefficient, takes a long time, and the data collection samples are small, which cannot accurately reflect the local photovoltaic resources.

[0007] 3. The collected data is limited to local use: the results of local lighting data collection and statistics can only reflect the local photovoltaic resources

If you want to build photovoltaic power plants in other locations, you need to carry out the same data collection and statistical work for the local area. Due to limited human resources, it is impossible to collect photovoltaic resources nationwide at the same time. Therefore, it will take longer in the evaluation stage

[0008] 4. The presentation method of photovoltaic resources is not intuitive: the statistical results of photovoltaic resource collection are presented in the form of data, which is not intuitive enough, and the evaluation requires professionals to spend a lot of energy to achieve

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