Dealing With Uncertainty: An Empirical Study On The Relevance Of Renewable Energy Forecasting Methods

DATA ANALYTICS FOR RENEWABLE ENERGY INTEGRATION (DARE 2016)(2016)

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摘要
The increasing share of fluctuating renewable energy sources on the world-wide energy production leads to a rising public interest in dedicated forecasting methods. As different scientific communities are dedicated to that topic, many solutions are proposed but not all are suited for users from utility companies. We describe an empirical approach to analyze the scientific relevance of renewable energy forecasting methods in literature. Then, we conduct a survey amongst forecasting software providers and users from the energy domain and compare the outcomes of both studies.
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关键词
Renewable energy forecasting, Practical relevance, Machine Learning
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