MCDM guided a posteriori multi-objective techno-economic allocation of RDGs and EVCS in distribution network - Rahman, Mukhlesur; Kalam, Md. Abul; Sankar, Matta Mani (Journal of energy storage, 2025)
This paper introduces a posteriori multi-objective approach to efficiently integrate renewable distributed generation systems (RDGs) and electric vehicle charging stations (EVCS) into the distribution network (DNs). Properly placing and sizing RDGs and EVCS is essential to enhance network performance, including reduced energy loss and improved voltage profile. A multi-objective optimization problem is formulated considering the contradicting technical and economic objectives. A posteriori multi-objective artificial hummingbird algorithm (MOAHA) is employed to solve the optimization problem, generating Pareto optimal solutions. Additionally, multi-objective optimization based on ratio analysis technique is utilized to determine the ideal trade-off solution, offering multiple options based on distribution utility preferences concerning the conflicting goals. The suggested methodology is verified on IEEE 33-bus and 69-bus DNs. In-depth case studies illustrate the advantages of the proposed methodology, including minimizing energy losses, reducing voltage deviation, and maximizing voltage stability while considering investment and operational costs. Further, the MOAHA is compared with various multi-objective algorithms using the spacing metric indicator. This study provides a robust framework for integrating RDGs and EVCS, ensuring sustainable and efficient power distribution. •Optimized conflicting technical and economic objectives for WTs & PVs-based RDGs and EVCS using a posteriori method.•A multi-objective optimization problem is formulated catering techno-economic objectives.•Presented multiple trade-off solutions by using multi-objective optimization based on ratio analysis (MOORA) method.•Maiden application of the MOAHA algorithm for solving the multi-objective optimal PV-WT-EVCS allocation problem.•Compared MOAHA with NSGA-II, MOPSO, MOHHO, and MOGWO using the spacing metric.