Supply-Demand Balancing Capability Enhancement Technique for Source-Load-Storage Coordination of Smart Microgrids

Abstract

: To improve the supply–demand balancing capability of smart microgrids under multi-source uncertainty, this paper proposes a coordinated source–load–storage optimization method. First, considering forecast errors in wind power, photovoltaic power, and load demand, a multi-scenario source–load uncertainty model is developed based on Latin hypercube sampling. Second, from the perspective of temporal supply–demand matching, a balancing capability evaluation system is established, including the instantaneous normalized balance degree, adjustable energy proportion, adjustable load proportion, and renewable energy utilization rate. The Criteria Importance Through Intercriteria Correlation (CRITIC) method is applied to determine the indicator weights and quantify the balancing capability of the smart microgrid. On this basis, a two-stage source–load–storage optimization model is constructed. In the first stage, an event-driven user dynamic response model is introduced to exploit load-side regulation potential. In the second stage, a multi-objective energy storage coordination model considering balance degree constraints is established to further improve supply–demand matching. The IEEE 33-node system is used for case validation. The results show that the proposed method effectively improves the temporal matching among sources, loads, and storage, thereby enhancing the supply–demand balancing capability of smart microgrids.