Optimisation Methods in Renewable Energy Sources Systems—Current Research Trends

Abstract

The objective of the work was to determine the research trends and carry out a bibliometric analysis of publications concerning the application of the computational intelligence method in the research area renewable energy sources optimization. In this study the Scopus database has been used as a data source. Articles and conference papers published in the years 2011–2017 were analysed. The research consists of two research tasks: bibliometric quantitative analysis and bibliometric thematic analysis of publications. On the basis of the analyses conducted, one can state that: In years 2011–2017, the number of scientific publications regarding RES optimisation, indexed in the Scopus database, increased by 340%. However, it does not mean that optimisation studies become prevailing, since the number of RES-related publications increased as well (by 199%). A percentage share of publications concerning RES optimisation, in relation to all publications dedicated to RES, grew in years 2011–2017 by 177%. The authors of the highest number of publications (in the set of articles and conference materials searched, for years 2011–2017) were researchers from the USA, China, India and Italy. The majority of the studies described in the publications set concerned optimisation of solar energy and wind energy systems, often hybrid systems. For optimisation by means of artificial intelligence computational methods, algorithms belonging to a group of Evolutionary Computations (mainly Genetic Algorithms) and Swarm Intelligence (especially PSO) were applied most frequently. Neural networks and fuzzy systems were applied three times less frequently. The authors suggest new optimisation algorithms combining several artificial intelligence methods.