Operational optimization for off-grid renewable building energy system using deep reinforcement learning

Yuan Gao, Yuki Matsunami, Shohei Miyata and Yasunori Akashi

Applied Energy, 2022, vol. 325, issue C, No S0306261922010625

Abstract: With the application of renewable energy in single office buildings, an increasing number of power grids require building systems coupled with renewable energy to realize off-grid operation. However, the uncertainty of renewable energy sources and the safety of the corresponding energy storage equipment have become major challenges for these systems. Reinforcement learning has made considerable progress in the field of building control as an advanced control algorithm; however, research on its application to the off-grid operation of renewable energy systems, particularly the specific reward function design is limited.

Keywords: Reinforcement learning; Off-grid operation; Operational optimization; Deep learning (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (19)

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DOI: 10.1016/j.apenergy.2022.119783

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