Optimal Operational Scheduling and Reconfiguration coordination in Smart Grids for Extreme Weather Condition

With the increasing in frequency, intensity, and side effects of grid outages caused by weather based events, the importance of resiliency is also increased. This study presents a novel multi-objective optimization problem for improving the resilience of smart grid against natural disasters in the presence of a considerable amount of line outages occurring due to the weather conditions. The proposed model considers the management of distributed energy resources (DERs), energy storages (ESs), and dynamic topology reconfiguration of the distribution network. The main goal is based on a dynamic resilient operational planning using prediction of weather condition. The objectives in the proposed approach are defined as: to minimise operational cost of distribution network from the system operator's viewpoint, to minimise the penalty costs for energy not supplied and side effects of outages, and to maximise benefits of DER-ES owners by using flexible reconfiguration and dynamic operational planning considering weather conditions. A hybrid optimization algorithm based on genetic algorithm and -constraint method using fuzzy decision maker is employed to choose the best solution from a provided Pareto optimal set. The outcome of the Pareto solution specifies the best scheduling for DERs, ESs and switching of lines during the scheduling horizon.