Research on Key Technologies of Economic Optimal Scheduling Operation for Source-Load Coordination of Local Microgrid

Abstract

To address the challenges of wind and solar power intermittency, bidirectional price fluctuations in aluminum and electricity, and high curtailment and energy costs in electrolytic aluminum park microgrids equipped with self-owned thermal power and integrated wind-solar-storage systems, this paper proposes a comprehensive technical framework: “Copula-based wind-solar scenario modeling- bi-level multi-scale coordinated scheduling-electricity price-linked multi-objective optimization.” Specifically, Gaussian kernel density estimation combined with the Frank-Copula is employed to characterize the coupled stochasticity of multi-site renewable generation. A bi-level scheduling framework comprising day-ahead and 15-minute-ahead stages is established by distinguishing between discrete and continuous high-energy-consuming loads. Furthermore, a dual-objective model maximizing renewable energy accommodation and minimizing comprehensive costs is developed, subject to electricity and aluminum price constraints. Simulation verification conducted at the Huolinhe Park demonstrates 100% wind and solar accommodation, with peak-shaving costs for grid electricity and thermal power reduced by 41.3% and 32.7%, respectively. This approach effectively hedges against price risks, and the proposed methodology is readily scalable and replicable across other high-energy-consuming industrial parks.