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The rapidly increasing utilization of renewable energy sources (RES) creates vital challenges that lead to multiple uncertainties in power generation, voltage instability, and reduced system resilience due to their intermittent nature. This paper recommends a stochastic active and reactive energy management (SAREM) framework for resilient microgrids. It is specifically developed to manage active and reactive power flows simultaneously by combining hydrogen energy storage systems (HESS) with battery energy storage systems (BESS). The SAREM model is a stochastic optimization framework which incorporates a scenario-based uncertainties handling associated with RES, hydrogen prices, utility grid costs, and demand variability due to different weather conditions. A multi-objective formulation is developed to minimize total operational cost and active power loss while enhancing system resilience through minimum use of utility grid power. The proposed SAREM model is comprehensively tested with two different sized test systems i.e. Modified IEEE-33 bus and IEEE-69 bus microgrid test Systems under four distinct weather conditions: Summer, Winter, Spring, and Autumn. It is further examined in both grid-connected and islanded (fault) modes in microgrid operations to validate its reliability and power balance capability. The simulation results signify that the proposed SAREM model is capable to provide the significantly high reductions in total operation costs up to 30.67 %, 32.66%, 33.38%, 31.91% w.r.t. a baseline for Summar, Winter, Spring and Autumn, respectively. These significant economic advantages have resulted with a recommended simultaneous active and reactive power management along with coordinated utilization of BESS and HESS during daily microgrid operations. Moreover, it further improves the grid resilience and sustainable solutions for efficient and uncertainty-resilient microgrid operation, contributing significantly to the evolution of smart and flexible power systems.
Prakash et al. (Fri,) studied this question.