Capacity-Margin-Guided Multi-Objective Crested Porcupine Optimization Method for Expansion Installation

To address the rapid growth of candidate connection combinations and the high proportion of infeasible solutions generated by random search in the coordinated connection of multiple business-expansion loads, a capacity-margin-guided multi-objective crested porcupine optimization method is proposed. A multi-objective optimization model is established to minimize bus voltage deviation, active power loss, and connection engineering cost. To improve the feasibility of initial solutions, a capacity-margin-guided initialization strategy is introduced to incorporate distribution-network operating information into population generation. Considering the discrete characteristics of connection-node decisions, an electrical-neighborhood-based search strategy is further developed to enhance local search capability in the discrete solution space. The final recommended scheme is selected from the Pareto-optimal solution set according to its distance to the ideal point. Case studies on the IEEE 33-bus distribution system show that CM-MOCPO achieves an initial feasible-solution ratio of 74.5%, an HV of 0.8126, and an IGD of 0.0249, outperforming MOCPO, NSGA-II, and MOPSO. The results demonstrate that the proposed method can improve feasible-region search efficiency and Pareto-front quality for coordinated connection of multiple business-expansion loads while achieving a tradeoff between distribution-network operating performance and connection economy.