Research on the Optimal Configuration Model of Microgrid Energy Storage Considering Source-Load Uncertainty and Power Start-Up Characteristics

With the large-scale integration of renewable energy, the uncertainty of source-load balance and the startup characteristics of power sources impose higher requirements on the economic and reliability performance of microgrid operations. To address this, this paper proposes an optimization model for energy storage configuration in microgrids, considering source-load uncertainty and power source startup characteristics. By normalizing historical data and utilizing the K-means clustering algorithm to extract typical scenarios and their probabilities, the model quantifies source-load uncertainty. The optimization model comprehensively considers the construction and operational costs of the energy storage system, microgrid economics, renewable energy utilization rate, and power supply reliability, and establishes a multi-dimensional objective function. System operation constraints and energy storage charge/discharge constraints are introduced to ensure the stability of the energy storage system under complex operating scenarios. The model also incorporates power source startup characteristics, designing a collaborative energy storage regulation strategy for islanded operation modes, significantly improving system reliability during dynamic response processes. Case studies show that this model achieves significant results in peak shaving, improving renewable energy utilization, and reducing operating costs, providing theoretical support and practical reference for the optimization of energy storage configuration in microgrids.