Probabilistic scheduling of microgrid resilience: Integrating renewables, storages and demand response in unit commitment and reconfiguration

Abstract

Microgrids are essential for ensuring reliable electricity supply, especially during grid outages or extreme events. However, integrating renewable energy sources, managing fluctuating load demands, and addressing uncertainties in electricity prices introduce significant challenges in maintaining system resilience. This paper introduces a novel probabilistic scheduling framework for simultaneous unit commitment and network reconfiguration, integrating renewable energy sources, energy storage systems, and demand response programs into a unified optimization model. The framework explicitly addresses uncertainties related to renewable generation, load demand, and electricity prices, ensuring robust decision-making under real-world conditions. Additionally, the model incorporates emergency load curtailment contracts and adaptive load shedding to enhance resilience during critical conditions. The microgrid under study comprises wind turbines, micro-turbines, and battery storage systems, serving both critical and non-critical loads. The pelican optimization algorithm is employed as a solution tool to solve the optimization problem efficiently. Simulation results demonstrate significant improvements in microgrid performance, stability, and resilience, particularly under extreme conditions. By addressing critical research gaps in the integration of unit commitment, reconfiguration, and demand response, this study provides a comprehensive and adaptive solution for optimizing microgrid operations. The findings offer valuable insights for energy system planners and policymakers aiming to develop resilient and sustainable energy infrastructures.