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

Duojiao Guan | Zendy; Xiaoyi Qian | Zendy; Shiyu Lu | Zendy; Ning An | Zendy; Peng Ye | Zendy; Mulin Zhang | Zendy; N. Zhang | Zendy

Open Access

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

Author(s) -

Duojiao Guan,

Xiaoyi Qian,

Shiyu Lu,

Ning An,

Peng Ye,

Mulin Zhang,

N. Zhang

Publication year - 2021

Publication title -

security and communication networks

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.446

H-Index - 43

eISSN - 1939-0114

pISSN - 1939-0122

DOI - 10.1155/2021/8864552

Subject(s) - computer science , thermal energy storage , scheduling (production processes) , wind power , cogeneration , electricity , particle swarm optimization , computer data storage , real time computing , power (physics) , mathematical optimization , electricity generation , electrical engineering , engineering , algorithm , computer hardware , ecology , physics , mathematics , quantum mechanics , biology

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.

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