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From Market Signals to Maintenance Decisions: Grid-Informed Maintenance Optimization in Offshore Wind Farms

Keyi Wang, Robert Mieth, Ahmed Aziz Ezzat · 2026 · arXiv (Cornell University)

DOI: 10.48550/arxiv.2610.28167 · cited by 0 works (OpenAlex) · open-access PDF

Korean

현재까지 전력 생산자는 농장 수준의 정보 (예를 들어, 건강 신호, 전력 생성, 기상 조건)에 의존하여 대규모 해상 풍력 발전소의 유지 보수 계획에 큰 영향을 미치고 있습니다 전력 시스템의 유지 보수 운영에 대한 추가 네트워크 수준의 정보를 고려하는 것이 좋습니다. 현재까지, 전력 생산자는 주로 농장 수준의 정보 (예를 들어, 건강 신호, 전력 생성, 기상 조건)에 의존합니다. 우리는 유지 보수 작업에서 추가 네트워크 수준의 정보를 고려하도록 제안합니다. 생성 절단 및 시장 가격 조정과 같은 유지 보수 작업에 대한 부정적인 경제적 가치가 없다는 것을 분석적으로 입증합니다. 유형화 된 환경에서 유지 보수 계획에 대한 부정적인 기초를 제공하여 시장 및 네트워크 정보를 유지

Machine translation (Meta M2M100); the English original follows.

Abstract

The reliable and cost-effective integration of large-scale offshore wind farms into power systems is largely influenced by maintenance operations. To date, power producers primarily rely on farm-level information (e.g., health signals, power generation, weather conditions) for maintenance planning of wind turbine fleets. We propose to consider additional grid-level information in maintenance operations, such as generation curtailment and market pricing. Periods of high generation curtailment or negative electricity pricing can be viewed as opportunities for preventive maintenance, since assets are fully or partially shut down due to grid-imposed constraints. We first analytically establish that access to market information has non-negative economic value for maintenance scheduling under a stylized setting, providing a theoretical foundation for treating market and grid information as a maintenance opportunity. We then formulate a grid-informed opportunistic maintenance scheduling model as a receding-horizon mixed integer linear program that jointly leverages both farm- and grid-level signals under realistic conditions to determine a maintenance plan for offshore wind turbines. Considering a 600-MW offshore wind farm in the United States, our proposed method reduces annual maintenance costs by up to 10%, while enhancing asset availability and resource utilization, relative to advanced maintenance models that solely rely on farm-level information.

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Topics: Offshore wind power, Wind power, Grid, Turbine, Stylized fact, Scheduling (production processes)

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