Reliability Improvement on Power Distribution Systems by Network Reconfiguration: A Matheuristic Approach to Clustering Electrical Consumers

Abstract

This paper proposes the clustering of consumers into subsets through network reconfiguration procedures, combining mathematical and heuristic methods. The mixed-integer linear programming (MILP) model consists of two submodels applied separately to the electrical network, focusing on solving the consumer clustering problem. The modeling framework is divided into two interdependent and mutually influenced levels. At the upper level, the goal is to preserve the radial topology of the network, while the lower level is responsible for the electrical validation of the proposed clusters, ensured through power flow calculations. Mathematically, the upper level ensures the radial configuration of the network based on load flow, while the lower level confirms the electrical magnitudes associated with the new load allocations. The objective of the proposed approach is to minimize the line loading rate and the system reliability indices. To indirectly represent the clustering of consumers, a generalized minimum-cost multi-flow network model was adopted, directly reflecting the new topological structure of the electrical circuits. Network modification corresponds to the degree of each consumer’s association with the power sources and is guided by a heuristic evaluation based on minimum-cost energy paths. Additionally, a path construction strategy was implemented to maximize energy delivery at the lowest cost. The computational implementation of the model demonstrates its effectiveness in generating solutions that reduce line loading costs and significantly improve system reliability. The combination of MILP modeling, the use of multiple flows, and the validation of results through power flow simulations represents a technically relevant contribution compared to existing literature. The results obtained demonstrate the benefits of the proposed matheuristic for the planning and efficient operation of radial distribution systems.