A TOPSIS based multi-objective optimal power flow approach using the artificial hummingbird algorithm for renewable energy and PEV integrated system - Avvari, Ravi Kumar; D.M., Vinod Kumar; Annamraju, Anil Kumar; Reddy, Nareddy Nageswara (Measurement : journal of the International Measurement Confederation, 2025)
•Proposed a novel MOAHA-SF method to solve the OPF problem in a renewable and PEV combined power system.•To assess the efficacy of the MOAHA-SF in resolving the stochastic MOOPF issue, four objectives are considered.•Six cases are considered on IEEE 57- and 118-bus systems to validate the robustness and suitability of MOAHA-SF.•To identify the most optimal feasible solutions, an SF-based constraint handling technique is implemented.•To identify the best-compromised value from the Pareto optimal front, a recently developed TOPSIS method is employed. In this work, a novel bio-inspired multi-objective artificial hummingbird algorithm (MOAHA) is proposed to address the optimal power flow (OPF) issue in a renewable energy and plug-in electric vehicle (PEV) integrated power system. The MOAHA mimics the unique flight abilities and intelligent foraging approaches of hummingbirds in their natural habitat. The proposed method is assessed by resolving the OPF with multiple objectives using the IEEE 57- and IEEE 118-bus systems. The objectives include minimizing the total generation cost, emission, active power loss, and voltage magnitude deviation along with various constraints. This work employs a superiority of the feasible solution (SF) based constraint handling methodology to address a variety of constraints associated with the OPF study. Additionally, a TOPSIS approach is deployed to identify the best trade-off solutions among multiple objectives in the multi-objective OPF (MOOPF) problem. These techniques further aid in optimal outcomes to be specific the proposed MOAHA-SF attains a generation cost of 35448.14$/h and emission of 0.8696ton/h in the modified IEEE 57-bus system, and 127890.64$/h for cost and 31.4611 MW for active power loss in the modified IEEE 118-bus system. As demonstrated by the results, the proposed MOAHA-SF is significantly more effective in terms of computation efficacy and solution accuracy. Furthermore, the performance of the MOAHA-SF is evaluated through the calculation of hypervolume metrics and a one-sided ANOVA.