Abstract

Recent shift towards renewable energy resources has increased research for addressing shortcomings of these energy resources. As major issues are related to intermittency and uncertainty of renewable supply, new technologies like artificial intelligence and machine learning offers lot of opportunity to address these issues as they are basically meant for processing of uncertain data. This paper analyses application of machine learning in different areas of renewable energy system like forecasting where machine learning is used to build accurate models, maximum power point tracking where machine learning provides robust and smooth control which is not much susceptible to noise in input, inverter where machine learning can be used to provide high quality power without fluctuation even when input is intermittent. Even though machine learning has many prospects which can be used to address different issues associated with renewable system, whether to employ it as effective solution to problem for given system or not depends on host of factors. This paper analyses all these issues and present a methodical exploration of applications of machine learning, its advantages and challenges in hybrid renewable energy system.

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