In recent years, the overwhelming growth of solar photovoltaics (PV) energy generation as an alternative to conventional fossil fuel generation has encouraged the search for efficient and more reliable operation and maintenance practices, since PV systems require constant maintenance for consistent generation efficiency. One option, explored recently, is artificial intelligence (AI) to replace conventional maintenance strategies. The growing importance of AI in various real-life applications, especially in solar PV applications, cannot be over-emphasized. This study presents an extensive review of AI-based methods for fault detection and diagnosis in PV systems. It explores various fault types that are common in PV systems and various AI-based fault detection and diagnosis techniques proposed in the literature. Of note, there are currently fewer literatures in this area of PV application as compared to the other areas. This is due to the fact that the topic has just recently been explored, as evident in the oldest paper we could obtain, which dates back to only about 15 years. Furthermore, the study outlines the role of AI in PV operation and maintenance, and the main contributions of the reviewed literatures.
Este capítulo tem o objetivo de apresentar o desenvolvimento de um sistema de previsão da velocidade do vento com base em registros históricos, capaz de propor cenários de produção de energia elétrica.Além disso, são apresentados: o processo de conversão da energia eólica para energia elétrica e os conceitos básicos que determinam a potência elétrica produzida por uma turbina eólica em função da velocidade do vento e demais parâmetros envolvidos.
MODELAGEM DO VENTOA velocidade do vento em um determinado local pode ser modelada por uma distribuição de Weibull. A função densidade de probabilidade de uma distribuição de Weibull é dada pela equação (2) e seus parâmetros são o fator de forma k e o fator de escala λ.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.