Fast frequency response constrained stochastic scheduling of flexible loads in low inertia grids

Abstract

This paper presents a modeling approach to address fast frequency response (FFR) requirements within a stochastic scheduling framework. The work integrates FFR response from flexible loads and propose advance modeling techniques to characterize renewable generation uncertainty. The study incorporates scenario-based uncertainty modeling to capture the inherent unpredictability of renewable energy resources (RES), enhancing the accuracy of scheduling in low inertia grids. Central to the proposed methodology is the integration of flexible loads such as interruptible loads (ILs), deferrable loads (DLs), and electric vehicles (EVs) strategically modeled to contribute to FFR capabilities. By embedding uncertainty modeling within the proposed stochastic scheduling framework, the research offers a comprehensive strategy to effectively handle the challenges posed by renewable generation fluctuations and reduces the RES curtailment. The paper underscores the significance of FFR in maintaining grid balancing, particularly in the presence of RES. The inclusion of flexible loads further contributes to enhancement of grid resilience by enabling rapid adjustments in response to frequency disturbances. The proposed framework not only accommodates renewable generation uncertainties but also leverages smart flexible loads to bolster FFR capabilities paving the way for a reliable and sustainable power systems.

Keywords

• Demand response
• Distributed energy resources
• Fast frequency response
• Flexible loads
• Load scheduling
• Stochastic scheduling