Dealing with major power disruption during natural disasters is one of the most notable concerns in power systems. Due to renewable energy penetration and distributed generation resources in microgrids, they are considered as a potential solution to cope with severe events. Therefore, the application of microgrids in increasing and sustaining the distribution system resilience is considered. Furthermore, this purpose is pursued while maintaining the resilience of each DC microgrid connected to the distribution system, which is an essential and challenging issue. In the proposed method of this paper, a novel modeling strategy is formulated as a multi-period two-stage scenario-based stochastic mixed-integer linear programming (MPTSS-MILP) based on a multi-objective optimization problem (MOOP). In this framework, the operation associated with emergency and normal conditions, according to the influences of each situation on another one, is managed in multi-microgrids coordinately. In this regard, the technical constraints correlated to the operation of microgrids as well as the distribution system are satisfied simultaneously in specific to each condition which covers normal and critical operating under all uncertainty scenarios. Through introducing two evaluation criteria and also a resilience metric in microgrids and distribution systems, the efficiency of the proposed method is demonstrated. Meanwhile, innovative modeling is executed based on the subjective behavior of people affected by the disaster. Because the behavior of electricity consumers is one of the deciding factors in system management. The proposed scheme is implemented on a test system that involves a 34-bus distribution system with three distinct DC microgrids and its effectiveness is authenticated through various case studies.
Occurrence severe event with high-impact and low-probability (HILP), can cause significant disturbances to power grids. The strength of the system to withstand such HILP events is interpreted as system resilience. This paper proposes a novel approach for hybrid AC/DC microgrids with the aim of resilience enhancement and based on a linear stochastic two-stage scenario-based minimax relative regret (LSTS-MMRR) optimization according to the optimality robustness concept. Photovoltaic array and wind turbines, microturbines, and energy storage systems are scheduled based on the proposed approach in microgrids. Considering the uncertainty of emergency duration due to disruption from the upstream grid, the optimization problem is decomposed into standard and critical stochastic situations. This work also quantifies the importance of uncertainty with the well-known quantities named Value of Stochastic Solution (VSS) and Expected Value of Perfect Information (EVPI). For both normal and emergency circumstances, exclusive objective function and constraints are considered. Meanwhile, time-related variables maintain their continuity between normal and emergency circumstances. Therefore, the proposed approach minimized the maximum regret of objective function through defined scenarios. The proposed technique is compared with two common methods in resilience enhancement issues, and its effectiveness is demonstrated through an analysis of the VSS and EVPL.
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