文章基本信息

标题：Weather data errors analysis in solar power stations generation forecasting
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作者：Stanislav Eroshenko ; Alexandra Khalyasmaa
期刊名称：E3S Web of Conferences
印刷版ISSN：2267-1242
电子版ISSN：2267-1242
出版年度：2018
卷号：51
页码：2002-2007
DOI：10.1051/e3scconf/20185102002
出版社：EDP Sciences
摘要：The paper presents a short-term forecasting model for solar power stations (SPS) generation developed by the authors. This model is based on weather data and built into the existing software product as a separate short-term forecasting module for the SPS generation. The main problems associated with forecasting the SPS generation on cloudy days were revealed in the framework of authors' research, which is due not to the error of the developed model but to the use of the same learning sample for both solar and cloudy days. This paper contains analysis of the main problems related to the learning sampling, samples pattern, quality and representativeness for forecasting the SPS generation on cloudy days. Besides, the paper includes a calculation example performed for the existing SPS and a detailed analysis of the forecast generation on cloudy days based on the actual weather provider data.