Application of Artificial Intelligence in Renewable Energy

Alankrita, S. Srivastava
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引用次数: 5

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.
人工智能在可再生能源中的应用
最近向可再生能源的转变增加了对解决这些能源缺点的研究。由于主要问题与可再生能源供应的间歇性和不确定性有关,人工智能和机器学习等新技术为解决这些问题提供了很多机会,因为它们基本上是为了处理不确定的数据。本文分析了机器学习在可再生能源系统不同领域的应用,如预测,其中机器学习用于建立准确的模型,最大功率点跟踪,其中机器学习提供鲁棒和平滑的控制,不太容易受到输入噪声的影响,逆变器,其中机器学习可以用于提供高质量的无波动的电力,即使输入是间歇性的。尽管机器学习在解决与可再生系统相关的各种问题方面具有许多前景,但是否将其作为给定系统问题的有效解决方案取决于许多因素。本文分析了所有这些问题,并对机器学习在混合可再生能源系统中的应用及其优势和挑战进行了系统的探索。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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