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Cogeneration units use heat and electricity as the main operation mode in the heating season. It suffers the lack of peak shaving ability, resulting in intense wind curtailment. .is study presents a coordinated scheduling strategy of heat storage thermoelectric units considering the uncertainty of wind power. .e developed method performs a wind power data measurement and process system based on edge computing and deep learning to acquire operation data quickly and independently and adopts a wind power prediction method based on interval scenario. Furthermore, the coordinated control model of the thermal storage unit is established after the analysis of the characteristics of coordinated scheduling strategy of heat storage thermoelectric units based on wind heat complementation, and then the improved particle swarm optimization (PSO) is adopted to the solving process. .e proposed method is verified by applying it to two typical thermal power units.

Research on Coordinated Scheduling Strategy of Heat Storage Thermoelectric Units Based on Wind Power Data Acquisition System Using Edge Computing