Abstract
Maintenance optimization has received special attention among the wind energy research community over the past two decades. This is mainly because of the high degree of uncertainties involved in the execution of operation and maintenance (O&M) activities throughout the lifecycle of wind farms. The increasing complexity in offshore maintenance execution demands applied research and brings forth a need to develop problem-specific maintenance decision-making models. In this paper, a mathematical model is proposed to assist wind farm stakeholders in making critical resource- related decisions for corrective maintenance at offshore wind farms (OWFs), considering uncertainties in turbine failure information.
Highlights
The widespread availability and high technological maturity make wind energy a reliable renewable option to satisfy the future energy demands of the global population [1]
This study shows that the maintenance decisions for offshore wind farms are critical for all time horizons
During this condition monitoring (CM) system unreliability event, the information failed turbine component is not obtained from the CM systems. These random natural and human influenced events leads to situation where the operation and maintenance (O&M) team will have no direct information from the CM systems to make resource related maintenance decisions. We focus on this scenario of corrective maintenance where the information on failed turbine component and its failure classification is not known
Summary
The widespread availability and high technological maturity make wind energy a reliable renewable option to satisfy the future energy demands of the global population [1]. The limited land area and the need to reduce noise pollution is forcing the wind energy sector to shift towards offshore technologies [2,3]. Offshore wind farms (OWFs) are energy assets that have experienced a considerable growth in terms of cumulative capacity, from 4 GW to more than 18 GW over the past five years [4]. OWFs are expensive assets to build, and to operate and maintain. About 23% contribution of the operation and maintenance (O&M) to the life cycle cost (LCC) makes the O&M the second major contributor for the LCC of an OWF [5]. The high O&M cost and the unproven economic feasibility remain a hindrance for the future growth and expansion of the OWFs
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