Dindin Nasrudin, Agus Setiawan, Dadi Rusdiana, Liliasari
This study aims to reveal state-of-the-art, trending topics and future work in Renewable Energy Online Learning (REOL). The research used the Systematic Literature Network Analysis (SLNA) method. SLNA in this study is a combination of Systematic Literature Review (SLR) using the PRISMA protocol followed by a Bibliometric Analysis with the help of VOSviewer software. The results of the study show The REOL publications are increasing yearly. The results of the VOSviewer analysis shown by network visualization show several emerging keywords (research topics) related to REOL, including electric power systems and reinforcement learning in the first cluster, engineering education and students in the second cluster, laboratories/virtual lab and solar cells/solar energy in the third cluster, and power and wind are in the fourth cluster. The visualization of overlay output results shows several trending research topics, including machine learning, reinforcement learning, deep learning, and virtual power plants. The results of a search on one of the emerging research topics (energy storage) show future work can be done, including measuring student feedback, learning outcomes, the relationship between satisfaction with software simulations, and hardware scenarios required for Smart Grid analysis. The results of this study can guide researchers in the REOL field to select and determine REOL research topics in the future. © School of Engineering, Taylor’s University.
Universitas Pendidikan Indonesia, Jl. Dr. Setiabudi No. 229, Bandung, 40154, Indonesia; UIN Sunan Gunung Djati Bandung, Jl. AH. Nasution 105, Bandung, 40614, Indonesia
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