Restauração de sistemas de distribuição de energia elétrica utilizando evolução diferencial com árvore de ancestralidade

Abstract

Problems in Power Distribution System Restoration (PDSR), such as service restoration, power loss reduction, and expansion planning, are usually formulated as multiobjective and multi-constrained optimization problems. Several Evolutionary Algorithms (EAs) have been developed to deal with PDSR problems, but the majority of EAs still demand high running time when applied to large-scale Distribution Systems (thousands of buses and switches). This work presents a new approach for service restoration in large-scale distribution systems that employs a Discrete Differential Evolution based on List of Movements with ancestor Tree (DE-Tree), in which the Ancestor Tree is used to obtain the list of movements. The Node-Depth Encoding (NDE) is used to computationally represent the electrical topology of the system and its operators, the Preserve Ancestor Operator (PAO) and the Change Ancestor Operator (CAO), are used to evolve the population. The proposed approach makes Differential Evolution suitable for treating combinatorial optimization problems related to PDSR preserving the self-adaptive differential mutation mechanism. Results presented on Distribution System Reconfiguration Problems indicates the adequacy and fast convergence of the proposed approach.