Research on offshore wind power system based on Internet of Things technology

A survey of artificial neural network in wind energy systems

Fen Zhou, Xuping Tu and Qingdong Wang

International Journal of Low-Carbon Technologies, 2022, vol. 17, 645-650

Abstract: Wind power generation is considered as one of the very promising new energy power generation methods. Offshore wind farms are usually located in open spaces far from the coast, where the wind is strong enough to generate electricity efficiently and reliably. The operation and maintenance of offshore wind power generation is more important; it will greatly affect the life cycle cost, although it is more difficult. Different from the methods used in other papers, this paper uses the Internet of Things (IOT) technology to collect and analyze wind power generation data to accurately and efficiently realize the operation and maintenance of offshore wind power generation. This paper also establishes an economic model for further analysis. Estimated electricity production under real weather is integrated into the model. According to the estimated model, with IOT technology can reduce maintenance costs by ~75% compared to without IOT technology, and according to our operation and maintenance data, we found that the downtime caused by blades, gearboxes and generators accounted for more than 87% of the total unplanned downtime, and maintenance costs accounted for more than three-fourths of the total maintenance costs. These data have reference significance for the operation and maintenance of offshore wind power generation.

Keywords: maintenance cost; IOT; wind energy (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:oup:ijlctc:v:17:y:2022:i::p:645-650.

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