提出一种优化微电网需求响应的线性规划框架，降低用电成本。
Demand Response Optimization MILP Framework for Microgrids with DERs
- 用混合整数线性规划建模，结合负荷分类与动态电价阈值。
- 峰荷降低10%，电费节省13.1%至38.0%，太阳能多时达38.0%。
- 适合高比例可再生能源微电网的运行优化，实测有效。
微电网中可再生能源的间歇性及发电与用电不匹配带来显著运营挑战。有效的需量响应（DR）策略对维持系统稳定与经济高效至关重要，尤其在可再生能源渗透率高的场景下。本文提出一种综合的混合整数线性规划（MILP）框架，用于优化含光伏与储能系统的微电网中需量响应操作。该框架融合负荷分类、动态电价阈值设定与多时段协调机制，实现最优的需量响应事件调度。在七种不同运行场景下的分析表明，峰值负荷持续降低10%，能源成本节约率达13.1%至38.0%。在太阳能发电充足的场景中表现最佳，通过可再生能源与需量响应动作的协同优化，实现38.0%的节能效果。结果验证了该框架在应对多样化运行挑战的同时，保持系统稳定性与经济性的有效性。
原文摘要 · Abstract (English)
The integration of renewable energy sources in microgrids introduces significant operational challenges due to their intermittent nature and the mismatch between generation and demand patterns. Effective demand response (DR) strategies are crucial for maintaining system stability and economic efficiency, particularly in microgrids with high renewable penetration. This paper presents a comprehensive mixed-integer linear programming (MILP) framework for optimizing DR operations in a microgrid with solar generation and battery storage systems. The framework incorporates load classification, dynamic price thresholding, and multi-period coordination for optimal DR event scheduling. Analysis across seven distinct operational scenarios demonstrates consistent peak load reduction of 10\% while achieving energy cost savings ranging from 13.1\% to 38.0\%. The highest performance was observed in scenarios with high solar generation, where the framework achieved 38.0\% energy cost reduction through optimal coordination of renewable resources and DR actions. The results validate the framework's effectiveness in managing diverse operational challenges while maintaining system stability and economic efficiency.
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