Restauración del servicio en sistemas de distribución considerando clientes prioritarios y microrredes

Abstract

The distribution automation (DA) allows the implementation of the advanced application FLISR (Fault Location, Insolation, and Service Restoration). This implementation provides the network the self-healing capability to improve its resilience. Service Restoration (SR) is an essential component of the FLISR application. It allows generating and executing automatically a plan to restore the service in healthy areas using the least number of maneuvers after detecting and isolating a permanent fault in the system area. There is some research that focuses on a solution based on SR with different architectures of automatization and optimization techniques. However, the algorithms are limited and require more work to consider scenarios such as priority clients, network reconfiguration and operation of microgrids, uncertainties of distributed energy resources (DER) and loads, to achieve a smart grid capable of self-healing itself from extreme events. The present research proposes an optimization centralized algorithm based on the combination of metaheuristic techniques of Differential Evolution (DE) and Continuous Population-Based Incremental Learning (PBILc) to solve the service restoration problem in Distribution Systems. This algorithm considers priority clients and distributed generation (DG) dispatch to support the main network, or local power supply of the loads by micro-grids. In this way, the system is provided with a selfhealing capacity to meet more restoration scenarios