Demand Response Strategy Considering Industrial Loads and Energy Storage with High Proportion of Wind-Power Integration

• Published in: Sensors (Basel, Switzerland) Switzerland), 2024-11, Vol.24 (22), p.7335
• Main Authors: Tian, Chongyi, Li, Julin, Wang, Chunyu, Lin, Longlong, Yan, Yi
• Format: Article
• Language: English
• Subjects: Alternative energy sources; Aluminum; Buildings and facilities; Carbon; Costs; Demand side management; Electric vehicles; Electricity; Energy consumption; Energy industry; energy management; Energy management systems; Energy resources; Energy storage; Flexibility; Force and energy; Green technology; hybrid energy storage; industrial loads; Industrial plant emissions; Liu, Timothy; Metallurgy; multiple time scales; Optimization; Power plants; Renewable resources; Scheduling; Supply & demand; Wind power; wind-power consumption
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s24227335

To address the challenges of reduced grid stability and wind curtailment caused by high penetration of wind energy, this paper proposes a demand response strategy that considers industrial loads and energy storage under high wind-power integration. Firstly, the adjustable characteristics of controllable resources in the power system are analyzed, and a demand response scheduling framework based on energy storage systems and industrial loads is established. Building on this foundation, a multi-scenario stochastic programming approach is employed to develop a day-ahead and intra-day multi-time-scale optimization scheduling model, aimed at maximizing economic benefits. In response to the challenges of wind-power fluctuations with high temporal resolution, a strategy for smoothing intra-day wind-power variability is further proposed. Finally, simulations are conducted to derive optimal demand response strategies for different stages. As verified by the comparison of different scheduling strategies, the demand response strategy proposed in this paper can reduce wind curtailment when there is sufficient wind power and reduce load shedding when there is insufficient wind power, which effectively reduces the system operation cost.