Kanwar et al. presented an improved particle swarm optimization technique for the simultaneous allocation of distributed energy resources (DER), focusing on enhancing the efficiency of power distribution systems while reducing energy losses and improving voltage stability.
Bibliometric analysis unveils key themes in optimizing ESS for renewables. The rise in research in this field shows that the field is constantly evolving. Hybrid RES, battery energy storage systems, and meta-heuristic algorithms are the prominent themes. MATLAB emerged as the dominant software tool.
During the evaluation of the literature for final selection, it was observed that the optimization of ESS focused on optimizing the energy management and control of the ESS, rather than optimizing the size of the ESS. More research should be directed toward ESS size optimization.
Technically, there are two approaches to address the inherent intermittency of RES: utilizing energy storage systems (ESS) to smooth the output power or employing control methods in lieu of ESS. The increased system complexity and cost associated with the latter approach render the former the most cost-effective option .
The reduction in overall costs, emissions, and reliability index, combined with improvements in voltage deviation and reduction in losses, highlights the potential of the proposed algorithm to redefine the operational paradigms of future power distribution systems.
About 10 % of the manuscripts lack an accurate description of the optimization algorithm. LP, MILP, and numerical methods comprise, respectively, 6 %, 13 %, and 8 % of the articles. Other algorithms include quadratic programming, benders decomposition, rule-based methods, and mixed integer non-linear programming.