Towards optimal post-fault self-healing in future smart distribution grids

Abstract

Abstract. This paper deals with a key functionality of the future distribution smart grids namely the automatic post-fault network self-healing. To this end we propose an optimization approach that aims finding the post-fault grid topology that minimizes the amount of unsupplied energy to consumers. The approach extends existing optimization models, developed in the context of losses minimization, for our particular application and proposes ways to overcome their limitations. We prove the interest of the approach on a 33-bus benchmark distribution system as well as on a 61-bus real-life distribution grid.

Control model for distributed generation and network automation for microgrids operation

“…Among the mathematical methods, mixed integer linear program (MILP) is one of the powerful techniques, as shown in [8][9][10][11][12]. Among the meta-heuristic methods, which genetic algorithm is one of them, several techniques, such as: tabu search, particle swarm optimization, or evolutionary method, could be used to solve this problem [13][14][15][16][17].…”

Towards more resilient electrical networks in urban areas

“…According to the United Nations [3], 66% of the population will live in urban areas by 2050 and therefore under natural disasters, an Urban Power System (UPS) with an automatic reconfiguration, or self-healing, of the network would enhance resilience under climate change event and consequently, continuity of supply to customers would be ensured [4]. Various self-healing strategies have been defined for the restoration of a power system assuming the latter is formed by is automated and remotely controlled equipment [5][6][7][8][9]. However, these studies also assume a radial network topology, which evidences the need of developing a strategy for meshed urban networks.…”