Frequency-Constrained Economic Dispatch of Microgrids Considering Frequency Response Performance

Abstract

The increasing penetration of renewable energy sources (RESs) has reduced the inertia and reserve levels of microgrids, posing challenges to frequency security during power imbalances. To address these challenges, this paper proposes a multi-objective distributionally robust frequency-constrained economic dispatch (DRFC-ED) model. First, the model aims to jointly optimize generation dispatch, reserve deployment, and the virtual inertia and damping constants of inverter-based resources to achieve a comprehensive optimization of both economic efficiency and frequency response performance. Then, the model further considers the distinctions between inertia and damping in the frequency response for more effective parameter deployment. Furthermore, the model leverages deep neural networks (DNNs) to convexify non-convex frequency constraints and employs a distributionally robust chance-constrained approach with Wasserstein distance-based ambiguity sets to handle RES uncertainty. Additionally, a method of directly obtaining the compromise optimal solution is used to transform the multi-objective problem into a single-objective one. Finally, the model is formulated as a mixed-integer linear programming problem and validated through case studies, demonstrating (1) an 8.03% reduction in the frequency integral time absolute error (ITAE) with only a 2.1% increase in economic cost compared to single-objective approaches, while (2) maintaining maximum frequency deviation (MFD) < 0.5 Hz during disturbances.