Multi-Objective Optimal Partitioning of Active Distribution Networks Integrating Consideration of Load Balancing and Solution Efficiency of Parallel Optimization

To address the optimization challenges arising from the large-scale integration of distributed energy resources into active distribution networks, this paper proposes a multi-objective optimization partitioning method that balances system security/stability with parallel computing efficiency. To address the limitations of existing partitioning approaches, particularly their neglect of parallel computing efficiency and poor adaptability to the radial topology of distribution networks, a three-objective optimization model is constructed. This model incorporates reactive power–voltage control, load balancing, and power balance constraints, while introducing partition scale constraints and connectivity constraints. The NSGA-III algorithm is employed to solve the Pareto front, and an optimal compromise solution is obtained using a fuzzy membership function. A partition adjustment strategy ensures topological connectivity. Validation on 10 kV distribution networks with 47-node, 124-node, and 300-node systems demonstrates that this method achieves reasonable reactive power–voltage partitioning, ensures intra-partition power balance and load balancing, and exhibits significant advantages over traditional methods.