Applications of Industrial IoT and WSNs in O&M Programmes for Offshore Wind Farms

Loughney, S ORCID: 0000-0003-0217-5739 and Edesess, AJ ORCID: 0000-0003-3448-8203 (2021) Applications of Industrial IoT and WSNs in O&M Programmes for Offshore Wind Farms. In: Tuovinen, T, Periaux, J and Neittaanmäki, P, (eds.) Computational Sciences and Artificial Intelligence in Industry New Digital Technologies for Solving Future Societal and Economical Challenges. Intelligent Systems, Control and Automation: Science and Engineering, 76 . Springer Nature, pp. 223-245. ISBN 9783030707866

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Abstract

Expanding reliance on offshore wind as a renewable energy source requires a thorough consideration of the role of remote monitoring in improving operations & maintenance of offshore wind turbines to reduce costs, increase reliability of access and improve health and safety for repair workers. Real-time collection, transfer and analysis of data relating to the sea state, and monitoring the integrity of the wind turbine structure and its individual systems and components have significant potential to reduce the Levelised Cost Of Electricity (LCOE). Advances in computational capabilities and the increasing connection of sensor networks through the Internet of Things (IoT) have allowed for an expansion in the use Wireless Sensor Networks (WSNs), capable of monitoring the condition of individual components of a wind turbine, such as temperature and vibrations or the system as a whole. This research provides a review of past experience installing WSNs to monitor several aspects influencing offshore wind energy, such as the turbine structure, components and local environment and discusses WSN technology and computing requirements. Although the experience in installing and utilising WSNs is extensive, there is a lack of coordination and standardisation for WSN systems in offshore locations. This paper seeks to clearly define the steps to follow when setting up a WSN connected by IoT, based on an example gas turbine from oil & gas and introduces suggested guidelines for implementing these systems.

Item Type:	Book Section
Uncontrolled Keywords:	4605 Data Management and Data Science; 4606 Distributed Computing and Systems Software; 46 Information and Computing Sciences; 40 Engineering; 7 Affordable and Clean Energy; 13 Climate Action
Subjects:	G Geography. Anthropology. Recreation > GE Environmental Sciences T Technology > T Technology (General) T Technology > TA Engineering (General). Civil engineering (General)
Divisions:	Engineering
Publisher:	Springer Nature
Date of acceptance:	1 February 2021
Date of first compliant Open Access:	27 April 2026
Date Deposited:	27 Apr 2026 14:22
Last Modified:	27 Apr 2026 14:22
DOI or ID number:	10.1007/978-3-030-70787-3_15
Editors:	Tuovinen, T, Periaux, J and Neittaanmäki, P
URI:	https://researchonline.ljmu.ac.uk/id/eprint/28477

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