Optimization of energy storage systems for integration of renewable energy sources — A bibliometric analysis

Abstract

Considering the critical nature of climate change mitigation, it is imperative to boost the integration of renewable energy sources (RES) into the power system. Nevertheless, increasing the utilization of these resources is hindered by their high volatility and unpredictability. Energy storage system (ESS) deployments in recent times have effectively resolved these concerns. To contribute to the body of knowledge regarding the optimization of ESS size for renewable energy integration, this article provides a bibliometric overview and analysis of the topic. Using the web of science and SCOPUS databases, a preliminary search was performed during the initial week of October 2023, resulting in the selection of 241 manuscripts for further screening. The research conducted an analysis of various factors, including the publication trend by year, the leading journals, the geographic distribution of publications, the most prolific authors, the most cited articles, and the key subject areas. A network analysis concerning the most frequently used keywords and bibliographic coupling across various countries was presented. Furthermore, an extensive examination is conducted on the content of the chosen manuscripts, resulting in a thorough discussion on various themes. These include the volume and resolution of the input data, the representative scenarios, the software tool and optimization algorithm utilized, the commonly discussed types of ESS and RES, and the operation mode of the system. Moreover, the number of studies which incorporated variations in load during the design process and the type of study are quantified. The findings indicate a positive trajectory in the number of publications pertaining to the subject of interest. The selected literature was published in a total of 61 distinct journals, with ‘Energy’ holding the most publications. China emerged as the leading contributor in terms of number of publications and the most prolific authors. Furthermore, the network analysis identified renewable energy, optimization, microgrid and battery energy storage as the most frequently used keywords. The content analysis reveals that the most frequently addressed themes in the literature are the hourly resolution of the data (81 %), representative days (94 %), meta-heuristic algorithms (46 %), MATLAB software tool (50 %), battery ESS (65 %), hybrid RES (52 %), and grid-connected mode of operation (79 %). Finally, valuable insights and future recommendations are offered based on the findings.