Abstract
Accessibility estimation is significant to the offshore wind farm operation and maintenance (O&M) due to the extremely limited weather window and its sensitive effects on O&M tasks. Wave forecasting can be one solution to help maintenance decision-making. However, the uncertain and dynamic properties of wave forecasts are seldom considered in the accessibility estimation process. This paper presents an uncertain accessibility estimation method based on a multi-step probabilistic wave height forecasting (MPWHF) model and Monte Carlo simulation. First, an MPWHF model is proposed using the wavelet decomposition and the sequence to sequence (Seq2Seq) network with quantile outputs. Second, the O&M missions are randomly given a start time and simulated in the O&M flow chart by the Monte Carlo method. Finally, several access indexes, including accessibility probability, delay time, and delay probability, are evaluated based on the simulation results. Verification of the proposed MPWHF model and uncertain accessibility estimation is based on 7-year observation data of a buoy station. The results show that the MPWHF model outperforms other counterparts and the probability of offshore accessibility is nonlinearly dependent on the weather limits and the O&M required time.
Highlights
Offshore wind energy has achieved remarkable progress in recent years[1,2,3]
Since the operation and maintenance (O&M) costs account for 15%-30% of the total cost of the offshore wind energy project [8,9], the costs associated with accessibility will directly influence the investment rewards of an offshore wind farm
In order to fill the research gap, this paper presents an uncertain accessibility estimation method for offshore wind farms based on a real-time multi-step probabilistic wave height forecasting (MPWHF) and O&M simulation
Summary
Offshore wind energy has achieved remarkable progress in recent years[1,2,3]. maintenance is still an intractable technical problem for offshore wind farms due to the harsh weather condition [4]. Many efforts have been made for the offshore wind farm accessibility estimation using measurements, reanalysis, or forecasts of the oceanic weather data. Francois [8] presents a maintenance optimisation model and estimates the maintenance delay caused by weather and work shift restriction based on Monte Carlo and measured wind and wave data. In order to fill the research gap, this paper presents an uncertain accessibility estimation method for offshore wind farms based on a real-time multi-step probabilistic wave height forecasting (MPWHF) and O&M simulation. (i) A real-time MPWHF model is proposed to obtain the uncertain and dynamic properties of wave height forecasts based on wavelet decomposition (WD) and sequence to sequence(seq2seq) network. In contrast to accessibility estimation using a deterministic pre-planned schedule, the O&M activity schedules are dynamically adjusted based on real-time multi-step probabilistic wave height forecasts.
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