Smart optimization in battery energy storage systems: An overview

• Published in: Energy and AI 2024-09, Vol.17, p.100378, Article 100378
• Main Authors: Song, Hui, Liu, Chen, Amani, Ali Moradi, Gu, Mingchen, Jalili, Mahdi, Meegahapola, Lasantha, Yu, Xinghuo, Dickeson, George
• Format: Article
• Language: English
• Subjects: Artificial intelligence based optimization techniques; Battery energy storage systems; Optimization; Renewable energy sources
• ISSN: 2666-5468; 2666-5468
• DOI: 10.1016/j.egyai.2024.100378

The increasing drive towards eco-friendly environment motivates the generation of energy from renewable energy sources (RESs). The rising share of RESs in power generation poses potential challenges, including uncertainties in generation output, frequency fluctuations, and insufficient voltage regulation capabilities. As a solution to these challenges, energy storage systems (ESSs) play a crucial role in storing and releasing power as needed. Battery energy storage systems (BESSs) provide significant potential to maximize the energy efficiency of a distribution network and the benefits of different stakeholders. This can be achieved through optimizing placement, sizing, charge/discharge scheduling, and control, all of which contribute to enhancing the overall performance of the network. In this paper, we provide a comprehensive overview of BESS operation, optimization, and modeling in different applications, and how mathematical and artificial intelligence (AI)-based optimization techniques contribute to BESS charging and discharging scheduling. We also discuss some potential future opportunities and challenges of the BESS operation, AI in BESSs, and how emerging technologies, such as internet of things, AI, and big data impact the development of BESSs. [Display omitted] •We first provide a review of BESSs operation that includes grid-scale applications, community, microgrid, and residential settings, and how they enhance the power system performance.•We summarize the BESS optimization approaches from the viewpoint of mathematical programming to AI-based optimization techniques and explain how these approaches are applied to BESS optimization scenarios.•We present some outlook on BESS optimization, how future AI contributes to BESS optimization, the issues of future BESS, and how the development of AI, big data, and internet of things (IoT) impact future BESSs.