Enhancing the Resilience of Hybrid Microgrids by Minimizing the Maximum Relative Regret in Two-Stage Stochastic Scheduling

Abstract

Occurrence of severe events 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 arrays 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 relative 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 EVPI.

Keywords

• Hybrid microgrids
• resilience enhancement
• stochastic optimization
• minimax regret
• optimality robustness