Solar Resource Analysis Tips: Using Weather History Records

Detailed and reliable analysis of solar energy resources is very important for the feasibility study of photovoltaic power plant construction. Although the method of resource assessment has been clearly defined, there are still some special skills encountered in the analysis process. Here we briefly introduce the use of weather conditions. The method of history.

Taking a feasibility study in a certain area in Sichuan as an example, the owner observed radiation data for the entire year at the construction site from December 2015 to November 2016. The data integrity is very good. After analyzing the monthly total radiation, see the following figure. . Radiation in September is the smallest in the year!


Figure 1: Total monthly radiation measured

The monthly changes of the total amount of data (years from 1981 to 2010) of Meteonorm data in the project area are shown in the figure below. December is the smallest in the whole year!


Figure 2: Total radiation of Meteonorm data for each month (1981-2010)

The difference between the measured data of 2016 and Meteonorm's multi-year average data is significant, which is the cause of the weather change in 2016? Or is there a problem with the observation instrument? At this time, you can check the history of weather conditions in the project location (for example, China Weather Network). The rainy season in Sichuan is from June to September, but it is mainly concentrated in July and August. In September 2016, the area is almost cloudy every day. The rain, which was shown on September 11 as a sunny day, explained why the measured data had the lowest amount of radiation in the whole of September. Therefore, at least from this point, the validity of the measured data can be confirmed, so that the representative annual revision can be continued according to the methods in the specification, so that the solar energy resource data analysis results can represent the long-term level of the project construction site, and the next generation of power generation estimation , Financial evaluation provides a reliable basis.

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