Review on Monitoring, Operation and Maintenance of Smart Offshore Wind Farms

• URL: http://arxiv.org/abs/2211.00221v1
• Date: Tue, 1 Nov 2022 02:09:51 GMT
• Title: Review on Monitoring, Operation and Maintenance of Smart Offshore Wind Farms
• Authors: Lei Kou, Yang Li, Fangfang Zhang, Xiaodong Gong, Yinghong Hu, Quande Yuan, and Wende Ke
• Abstract summary: Offshore wind farm has the advantages of stable wind speed, clean, renewable, non-polluting and no occupation of cultivated land. The operation and maintenance mode of offshore wind power is developing in the direction of digitization and intelligence. This paper will mainly analyze and summarize the monitoring, operation and maintenance of offshore wind farm.
• Score: 3.7668264632332997
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In recent years, with the development of wind energy, the number and scale of wind farms are developing rapidly. Since offshore wind farm has the advantages of stable wind speed, clean, renewable, non-polluting and no occupation of cultivated land, which has gradually become a new trend of wind power industry all over the world. The operation and maintenance mode of offshore wind power is developing in the direction of digitization and intelligence. It is of great significance to carry out the research on the monitoring, operation and maintenance of offshore wind farm, which will be of benefits to reduce the operation and maintenance cost, improve the power generation efficiency, improve the stability of offshore wind farm system and build smart offshore wind farm. This paper will mainly analyze and summarize the monitoring, operation and maintenance of offshore wind farm, especially from the following points: monitoring of "offshore wind power engineering & biological & environment", the monitoring of power equipment and the operation & maintenance of smart offshore wind farms. Finally, the future research challenges about monitoring, operation and maintenance of smart offshore wind farm are proposed, and the future research directions in this field are prospected.

Related papers

• Barely-Visible Surface Crack Detection for Wind Turbine Sustainability [0.0]
  We introduce a novel dataset of barely-visible hairline cracks collected from numerous wind turbine inspections. To prove the efficacy of our dataset, we detail our end-to-end deployed turbine crack detection pipeline.
  arXiv  Detail & Related papers  (2024-07-09T19:03:48Z)
• Global Transformer Architecture for Indoor Room Temperature Forecasting [49.32130498861987]
  This work presents a global Transformer architecture for indoor temperature forecasting in multi-room buildings. It aims at optimizing energy consumption and reducing greenhouse gas emissions associated with HVAC systems. Notably, this study is the first to apply a Transformer architecture for indoor temperature forecasting in multi-room buildings.
  arXiv  Detail & Related papers  (2023-10-31T14:09:32Z)
• Digital Twins in Wind Energy: Emerging Technologies and Industry-Informed Future Directions [75.81393574964038]
  This article presents a comprehensive overview of the digital twin technology and its capability levels, with a specific focus on its applications in the wind energy industry. It consolidates the definitions of digital twin and its capability levels on a scale from 0-5; 0-standalone, 1-descriptive, 2-diagnostic, 3-predictive, 4-prescriptive, 5-autonomous.
  arXiv  Detail & Related papers  (2023-04-16T18:38:28Z)
• Online Dynamic Reliability Evaluation of Wind Turbines based on Drone-assisted Monitoring [6.3640143289918045]
  We propose a drone-assisted monitoring based method for online reliability evaluation of wind turbines. A blade system of a wind turbine is used as an illustrative example to demonstrate the proposed approach.
  arXiv  Detail & Related papers  (2022-11-23T19:11:33Z)
• SDWPF: A Dataset for Spatial Dynamic Wind Power Forecasting Challenge at KDD Cup 2022 [42.72560292756442]
  We present a unique Spatial Dynamic Wind Power Forecasting dataset: SDWPF. This dataset includes the spatial distribution of wind turbines, as well as the dynamic context factors. We use this dataset to launch the Baidu KDD Cup 2022 to examine the limit of current WPF solutions.
  arXiv  Detail & Related papers  (2022-08-08T18:38:45Z)
• Neural-Fly Enables Rapid Learning for Agile Flight in Strong Winds [96.74836678572582]
  We present a learning-based approach that allows rapid online adaptation by incorporating pretrained representations through deep learning. Neural-Fly achieves precise flight control with substantially smaller tracking error than state-of-the-art nonlinear and adaptive controllers.
  arXiv  Detail & Related papers  (2022-05-13T21:55:28Z)
• Digital Twin Framework for Time to Failure Forecasting of Wind Turbine Gearbox: A Concept [0.0]
  Wind turbine is a complex machine with its rotating and non-rotating equipment being sensitive to faults. Fault detection in wind turbines is often supplemented with SCADA data available from wind farm operators. Time-series analysis and data representation has become a powerful tool to get a deeper understating of the dynamic processes.
  arXiv  Detail & Related papers  (2022-04-28T05:51:48Z)
• Measuring Wind Turbine Health Using Drifting Concepts [55.87342698167776]
  We propose two new approaches for the analysis of wind turbine health. The first method aims at evaluating the decrease or increase in relatively high and low power production. The second method evaluates the overall drift of the extracted concepts.
  arXiv  Detail & Related papers  (2021-12-09T14:04:55Z)
• Uncertainty Set Prediction of Aggregated Wind Power Generation based on Bayesian LSTM and Spatio-Temporal Analysis [42.68418705495523]
  This paper focuses on the uncertainty set prediction of the aggregated generation of geographically distributed wind farms. A Spatio-temporal model is proposed to learn the dynamic features from partial observation in near-surface wind fields of neighboring wind farms. Numerical testing results based on the actual data with 6 wind farms in northwest China show that the uncertainty set of aggregated wind generation is less volatile than that of a single wind farm.
  arXiv  Detail & Related papers  (2021-10-07T11:57:16Z)
• Scalable Optimization for Wind Farm Control using Coordination Graphs [5.56699571220921]
  A wind farm controller is required to match the farm's power production with a power demand imposed by the grid operator. This is a non-trivial optimization problem, as complex dependencies exist between the wind turbines. We propose a new learning method for wind farm control that leverages the sparse wind farm structure to factorize the optimization problem.
  arXiv  Detail & Related papers  (2021-01-19T20:12:30Z)
• Machine Intelligent Techniques for Ramp Event Prediction in Offshore and Onshore Wind Farms [0.0]
  Wind resource assessment for onshore and offshore wind farms aids in accurate forecasting and analyzing nature of ramp events. A large ramp event in a short time duration is likely to cause damage to the wind farm connected to the utility grid.
  arXiv  Detail & Related papers  (2020-11-28T21:21:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.