Abstract

Renewable Energy Sources (RES) are increasingly being utilised as environmentally friendly and clean alternatives to meet the ever-growing global energy demand, helping to mitigate the effects of global warming and climate change, and enabling communities to achieve greater energy resilience and reliability. However, one serious drawback of RESs is their inherent intermittent nature, as their primary energy source (wind or solar) cannot be fully dispatched, unlike hydro and thermal power plants. To help improve the variable nature of most RES and provide the grid and/or microgrid with a more stable power supply, storage solutions like Battery Energy Storage Systems (BESS) are being used to improve the intermittent behaviour of RES allied to advanced control systems. Artificial Intelligence (AI) algorithms and optimisation tools represent some of those advanced techniques being employed to improve the integration of BESS and RES. Due to the novelty and complexity of this research area, some gaps still remain unaddressed. Therefore, the primary objective of this paper is to provide a concise and straightforward review of the literature on AI and optimisation tools applied to BESS and RES systems, discussing their advantages and disadvantages, as well as identifying the research gaps and opportunities in this important and emerging field. © 2025 IEEE.