A healer reinforcement approach to smart grids by improving fault location function in FLISR

In this paper, a conceptual framework for self-healing ability of Smart Grid is introduced, which includes three main categories: system, component, and healer healing (or healer reinforcement). An effective healer healing approach to accelerate the fault location function of the FLISR process is realized by optimal placement of fault indicators (FIs). A multiple objective function is formulated, and solved using multi-objective particle swarm optimization (MOPSO), to simultaneously minimize indispensable economic and technical objectives. To such aim, a summation of total customers' interruption costs and the FIs installation costs are considered as the economic objective function; while, system interruption duration index (SAIDI) is assumed as technical objective function. Moreover, simulations are conducted considering uncertainties of automatic switching. The proposed healer reinforcement approach to improve overall Smart Grid reliability is examined on bus number four of the Roy Billinton test system (RBTS4). Subsequently, the results show that the algorithm can determine the set of optimal non-dominated solutions, which allows planners to select one of the non-dominated solutions based on their expertise. Also, a max-min approach is employed to select the best result among the obtained Pareto optimal set of solutions.