A multi-objective resilience-economic stochastic scheduling method for microgrid. (October 2021) - Younesi, Abdollah; Shayeghi, Hossein; Siano, Pierluigi; Safari, Amin
Highlights: Developing a multi-objective economic-resilience scheduling model for Microgrid. Analyzing the behavior of renewable energy resources in resilience program. Analyzing the impact of resilience/economic indices through the Pareto front. Using mixed-integer linear programing to bound the optimal balance of indices. Abstract: In this paper, the applicability of Microgrids (MGs) is reviewed for power system resilience against low-probability high-impact (LPHI) events. Financial issues have been always one of the major priorities in the scheduling of MGs. Although these systems can feed their loads in islanding mode, resilient operation of them under critical situations caused by LPHI events is a challenging problem. Improving resilience increases MG costs, therefore it is necessary to establish a trade-off between resilience and economic metrics. Therefore, the main purpose of this paper is to develop a novel multi-objective resilience-economic stochastic MG scheduling model. The proposed bi-level resilience-oriented stochastic scheduling integrates the economic perspective along with resilience function simultaneously using a multi-objective mixed-integer linear programming approach. The considered MG resilience function includes various metrics such as the ability to withstand, quick recovery, and the technical criteria in the face of low-probability high-impact events. The proposed method is tested on the modified IEEE 33-bus power system with a set of distributed energy resources, energy storage systems, and electric vehicle parking lots. The results outlined that, although, the integration of the resilience metrics in the MG scheduling problem has increased the operation cost of the MG approximately 25%, but improved the MG resilience more than 70%. On the other hand, the proper management of the independent distributed energy resources enhanced the resilience of the MG approximately 16% while decreased the operation cost of the MG by at least 28%.