Integrating renewable energy into the radial distribution network (RDN) poses challenges related to stability, reliability, and network operation. An energy storage system (ESS) incorporated into the RDN is a potential approach to addressing these challenges. Thus, we aim to optimize the allocation and operation of the ESS in this study. The multi‐objective framework aims to optimize system costs, improve voltage regulation, reduce peak demand, and minimize power losses, thereby enhancing the performance of the RDN. To achieve this, an enhanced artemisinin optimization (EAO) is proposed by incorporating the chaotic local search (CLS) into the original artemisinin optimization (AO) algorithm. The CLS enhances the optimization performance by exploring a large search space during the early run phase to prevent premature convergence and by exploiting a smaller region in the later run phase to refine the final solutions. Furthermore, the EAO parameter settings are adaptively adjusted to enhance search capability. The proposed EAO was applied to the IEEE 33‐bus and 69‐bus RDN, with various case studies to validate its performance. The results show that properly integrating an ESS can significantly enhance the performance of RDNs. Additionally, the proposed EAO method is compared with other methods to confirm its effectiveness in solving optimization problems.
Nguyen et al. (Thu,) studied this question.