Structural health monitoring of offshore wind power structures based on genetic algorithm optimization and uncertain analytic hierarchy process

Zhou, Lin; Huang, Pengxiang; Chi, Shaopeng; Li, Ming; Zhou, Hu; Yu, Hao; Cao, Hongda; Chen, Kai

doi:10.1016/j.oceaneng.2020.108201

Cited by 16 publications

(5 citation statements)

References 15 publications

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“…Different data sets were also utilized to validate the applicability of HV methods for detecting short-and long-term power curve anomalies, predicting failures and outages, and monitoring performance degradation. The innovation of [98] is that it combines qualitative analysis and quantitative analysis to propose a reliable, economical, and robust condition monitoring and decisionmaking method. A low-cost and high-efficiency wind turbine condition monitoring method based on Supervisory Control and Data Acquisition (SCADA) data was proposed [99].…”

Section: Wind Power Generation Fault Diagnosis Classmentioning

confidence: 99%

“…To achieve this goal, Refs. [98,[141][142][143], respectively, proposed different optimization techniques and methods, including multi-objective optimization, meta-heuristic optimization, Monte Carlo simulation, etc., taking into account the uncertainties of the marine environment, fan failure, ship transportation, etc. Through mathematical models, simulation models, and test methods, optimal or sub-optimal maintenance strategies, logistics schemes, and access fleet schemes were generated and evaluated, and their robustness was tested.…”

Section: Preventive Maintenance Strategymentioning

confidence: 99%

See 1 more Smart Citation

Comprehensive Analysis and Evaluation of the Operation and Maintenance of Offshore Wind Power Systems: A Survey

Yang

Jia

et al. 2023

Energies

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Offshore Wind Power Systems (OWPS) offer great energy and environmental advantages, but also pose significant Operation and Maintenance (O&M) challenges. In this survey, we analyze these challenges and propose some optimization strategies and technologies for OWPS comprehensively. The existing literature review mainly focuses on a certain field of offshore wind power O&M, but lacks a comprehensive introduction to offshore wind power. We consider the energy efficiency, reliability, safety, and economy of OWPS from various aspects, such as offshore wind and wave energy utilization, offshore wind turbine components, and wind power operation parameters, and compare them with onshore wind power systems. We suggest that OWPS can benefit from advanced design optimization, digital twin, monitoring and forecasting, fault diagnosis, and other technologies to enhance their O&M performance. This paper aims to provide theoretical guidance and practical reference for the technological innovation and sustainable development of OWPS.

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Section: Wind Power Generation Fault Diagnosis Classmentioning

confidence: 99%

Section: Preventive Maintenance Strategymentioning

confidence: 99%

Comprehensive Analysis and Evaluation of the Operation and Maintenance of Offshore Wind Power Systems: A Survey

Yang

Jia

et al. 2023

Energies

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“…In addition to offshore wind turbines, power electronic converters, and submarine cables, some scholars have studied offshore booster stations, sensors, uninterruptible power supply (UPS), offshore wind power structures, and so on [188,189].…”

Section: Monitoring For Other Equipmentmentioning

confidence: 99%

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

Kou

Zhang

et al. 2022

Sensors

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In recent years, with the development of wind energy, the number and scale of wind farms have been developing rapidly. Since offshore wind farms have the advantages of stable wind speed, being clean, renewable, non-polluting, and the non-occupation of cultivated land, they have gradually become a new trend in the wind power industry all over the world. The operation and maintenance of offshore wind power has been developing in the direction of digitization and intelligence. It is of great significance to carry out research on the monitoring, operation, and maintenance of offshore wind farms, which will be of benefit for the reduction of the operation and maintenance costs, the improvement of the power generation efficiency, improvement of the stability of offshore wind farm systems, and the building of smart offshore wind farms. This paper will mainly summarize the monitoring, operation, and maintenance of offshore wind farms, with particular focus on the following points: monitoring of “offshore wind power engineering and biological and environment”, the monitoring of power equipment, and the operation and maintenance of smart offshore wind farms. Finally, the future research challenges in relation to the monitoring, operation, and maintenance of smart offshore wind farms are proposed, and the future research directions in this field are explored, especially in marine environment monitoring, weather and climate prediction, intelligent monitoring of power equipment, and digital platforms.

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“…Specifically, in the literature applied to AHP optimization, Javanbarg et al (2012) have proposed an improved PSO model to solve a multicriteria decision-making system, Zhao et al (2022) have used the AHP and quantum PSO to obtain the multi-objective optimal dispatch of microgrid, Rawa et al (2021) have used the AHP and improved grey wolf algorithm to optimize the operation of the economic and technical environment of the power networks, and Zhou et al (2020) have used the uncertain AHP and genetic algorithm to monitor the structural health of offshore wind power structures. Despite the existence of a wide variety of global optimization algorithms, the well-known Non-Free Lunch (Wolpert & Macready, 1997) theorem guarantees that all optimization algorithms maintain the same performance on average over the possible optimization problems.…”

Section: Related Workmentioning

confidence: 99%

The Construction and Optimization of an AI Education Evaluation Indicator Based on Intelligent Algorithms

Zeng

2022

International Journal of Cognitive Informatics and Natural Intelligence

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The basic tool in the analytic hierarchy process (AHP) is the complete judgment matrix. To address the weakness of the AHP in determining weight in the comprehensive evaluation system, the particle swarm optimization (PSO)-AHP model proposed in this paper is based on the PSO in the meta-heuristic algorithm. The model was used to solve the indicator weights in the evaluation system of AI education in primary and secondary schools in Fujian Province and was compared with the genetic algorithm and war strategy optimization algorithm. From the comparison results, the PSO-AHP optimization is more effective among the three algorithms, and the indicator consistency can be improved by about 30%. They are both effective in solving the problem that once the judgment matrix is given in the AHP, the weights and indicator consistency cannot be improved. Finally, the results were tested by Friedman statistics to prove the viability of the proposed algorithm.

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Structural health monitoring of offshore wind power structures based on genetic algorithm optimization and uncertain analytic hierarchy process

Cited by 16 publications

References 15 publications

Comprehensive Analysis and Evaluation of the Operation and Maintenance of Offshore Wind Power Systems: A Survey

Comprehensive Analysis and Evaluation of the Operation and Maintenance of Offshore Wind Power Systems: A Survey

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

The Construction and Optimization of an AI Education Evaluation Indicator Based on Intelligent Algorithms

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