Review
Green & Sustainable Science & Technology
Zhengru Ren, Amrit Shankar Verma, Ye Li, Julie J. E. Teuwen, Zhiyu Jiang
Summary: Operations and maintenance of offshore wind turbines (OWTs) are essential for the development of offshore wind farms. Maintenance, in particular, plays a crucial role in the overall cost of energy due to practical constraints and high costs associated with offshore operations. The impact of maintenance on the life cycle of offshore wind farms is complex and uncertain, with maintenance strategies significantly affecting efficiency, profitability, safety, and sustainability. Onsite maintenance involves intricate marine operations that rely on practical factors for efficiency and safety, while potential negative environmental impacts also need to be considered.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Energy & Fuels
Yazid Aafif, Anis Chelbi, Lahcen Mifdal, Sofiene Dellagi, Ilias Majdouline
Summary: This paper investigates two maintenance strategies for wind turbine gearboxes, one based on temperature monitoring and the other based on imperfect preventive maintenance. Mathematical models are developed for optimizing the renewal period and the number of preventive maintenance actions. The economic feasibility of the two strategies is compared.
Article
Green & Sustainable Science & Technology
Waqar Hussain, Sadia Khan, Ather Hussain Mover
Summary: This research has designed an integrated QEHS management system in compliance with national and international standards, providing a tool for evaluating the EHS culture of onshore wind farms in Pakistan and enhancing the organization's business and market competitiveness.
Article
Energy & Fuels
Javier Contreras Lopez, Athanasios Kolios
Summary: Blades, as crucial components of wind turbines, have significant impact on both capital and operational costs. However, the failure modes and processes of the composite materials used in the blades are not well understood. Therefore, conducting a systematic study to analyze the failure modes and their criticalities is essential for reducing operational and maintenance costs. The results of this study can provide insights into maintenance strategies and risk mitigation techniques, contributing to the development of dynamic decision support systems.
Article
Engineering, Multidisciplinary
M. El-Naggar, A. Sayed, M. Elshahed, M. EL-Shimy
Summary: This paper proposes a detailed approach for maintenance decisions based on failure analysis to select the optimum maintenance strategy for different subassemblies of wind turbines, aiming to improve their performance and efficiency.
AIN SHAMS ENGINEERING JOURNAL
(2023)
Article
Energy & Fuels
Christian Willberg, Rakesh Ravi, Johannes Rieke, Falk Heinecke
Summary: The full-scale 20 m rotor blade for the NREL CART3 wind turbine was designed, built and tested in the Smartblades and Smartblades 2 projects, with experiments and simulations providing proof for the technology. A reference finite element model for the rotor blade was described and published, along with validation procedures and limitations. The experimental data, analysis scenarios, and corresponding finite element models were presented in multiple software formats as a reference dataset.
Article
Management
Thijs Nicolaas Schouten, Rommert Dekker, Mustafa Hekimoglu, Ayse Sena Eruguz
Summary: This paper introduces a new model for maintenance optimization in offshore wind turbine maintenance, which addresses time-varying costs. The authors extend the standard maintenance policies and prove that the optimal maintenance policy under time-varying costs is a time-dependent strategy. They also present linear programming models for parameter optimization. By applying these models, they demonstrate significant cost savings in maintenance planning.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Mathematics
Hongyan Dui, Yulu Zhang, Yun-An Zhang
Summary: Wind farms are gaining attention as a source of unlimited and clean energy. However, the reliability of wind turbine systems can be reduced by subsystem failures in harsh conditions. This paper proposes a grouping maintenance policy considering the variable cost (GMP-VC) to improve direct-drive permanent magnet (DPM) turbine systems. The proposed maintenance policy shows potential for saving maintenance costs over baseline plans.
Article
Computer Science, Information Systems
Xisheng Xiao, Jin Sun, Jinxin Yang
Summary: This paper introduces an intelligent anomaly detection method based on machine learning, called ELPI, which divides the data set and establishes an online/offline algorithm module to detect abnormal data, with the results showing that this method is more accurate and stable than traditional methods.
COMPUTER COMMUNICATIONS
(2021)
Article
Energy & Fuels
Fraser Anderson, Rafael Dawid, David McMillan, David Garcia-Cava
Summary: This article introduces a Bayesian reliability modelling approach that considers time-dependent variables. The approach is used to investigate the impact of annual services on wind turbine failure intensity over time. The study also explores the effects of seasonality, year of operation, and position in the array on failure intensity. The results demonstrate a spike in failure intensity before annual servicing and a reduction afterwards. There is also a significant decrease in failure intensity year-on-year and a preference for modeling time to failure using a Weibull distribution. The study highlights the benefits of employing a Bayesian regime for uncertainty quantification.
Article
Green & Sustainable Science & Technology
Xiao Chen, Martin A. Eder, Asm Shihavuddin, Dan Zheng
Summary: This paper introduces a novel concept for an intelligent and semi-autonomous human-cyber-physical system (HCPS) to operate future wind turbines in Industry 5.0. It emphasizes the importance of artificial intelligence in operating next-generation wind turbines and the application of digital twin technology in machine learning. Additionally, it highlights the supervisory role of human intelligence in high-level decision-making.
Article
Energy & Fuels
Junqiang Zhang, Souma Chowdhury, Jie Zhang, Weiyang Tong, Achille Messac
Summary: This paper addresses the issue of preventive maintenance for offshore wind farms and optimizes the maintenance time windows using a power generation model and genetic algorithm to minimize downtime energy losses. The influence of wake effects and weather conditions on the maintenance plan is considered.
Article
Computer Science, Information Systems
Wisdom Udo, Yar Muhammad
Summary: The analysis predicts a significant increase in offshore wind capacity by 2026, emphasizing the need for complex maintenance of wind turbines. Offshore wind operation and maintenance costs make up a substantial portion of the total electricity cost, highlighting the importance of exploring predictive maintenance methods and optimizing production output. The proposed approach of monitoring critical components using historical SCADA data and advanced models shows promise in improving operational reliability and reducing maintenance costs of wind turbines.
Article
Energy & Fuels
F. Abderrahmane, S. Bouslikhane, Z. Hajej, S. Dellagi, W. Trabelsi
Summary: This study aims to develop an optimized integrated maintenance strategy and spare parts management plan for wind turbine systems with observable degradation. The strategy integrates a spare parts policy and considers the random production of energy. By modeling the failure rate of the wind turbine systems as a function of the current operating mode, an improved maintenance strategy is developed and optimized to switch between perfect and imperfect preventive maintenance actions. The objective is to optimize the total cost of maintenance actions and spare parts management over a finite planning horizon, taking into account the impact of production rate on the failure rate of the wind turbine systems.
Review
Acoustics
Jan Helsen
Summary: The paper discusses trends in condition monitoring of modern offshore wind turbines. It gives an overview of design changes and data source availability evolution, and introduces ongoing research activities in the field along with highlighting the requirements for innovations towards prognostic frameworks, particularly in advanced signal processing.
ACOUSTICS AUSTRALIA
(2021)
Article
Energy & Fuels
Bowen Li, Sukanta Basu, Simon J. Watson, Herman W. J. Russchenberg
Summary: This study investigated a Dunkelflaute event near the coast of Belgium and simulated it using the WRF model. Validation with measured data and sensitivity experiments revealed the potential and reliability of the WRF model in reproducing and forecasting boundary layer evolution during such events.
Article
Thermodynamics
Marvin Rhey Quitoras, Pedro Cabrera, Pietro Elia Campana, Paul Rowley, Curran Crawford
Summary: Policy and investment decisions for developing clean energy strategies in remote communities are influenced by multiple uncertainties, requiring robust modeling approaches to clarify potential outcomes. This study introduces a novel modeling framework that considers decision-maker attitudes towards uncertainties and energy solution philosophies, enhancing decision making in energy systems planning.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Editorial Material
Energy & Fuels
Simon Watson
Article
Energy & Fuels
Bedassa R. Cheneka, Simon J. Watson, Sukanta Basu
Summary: The study found that wind power production and wind power ramps are related to different weather patterns, suggesting that the type of transition between weather patterns determines ramp up or ramp down events.
Article
Green & Sustainable Science & Technology
Nurseda Y. Yurusen, Bahri Uzunoglu, Ana P. Talayero, Andres Llombart Estopinan
Summary: This study analyzed hourly simulation data using machine learning algorithms and association rules to address spatio-temporal operational balancing constraints for solar PV. The proposed model serves as a fast and effective decision-making tool for system operators with minimal expert knowledge and can be integrated into optimal power flow analysis constraints.
Article
Energy & Fuels
Bowen Li, Sukanta Basu, Simon J. Watson, Herman W. J. Russchenberg
Summary: This study investigates Dunkelflaute events occurring in eleven countries surrounding the North and Baltic Sea areas, finding that they mainly occur in November, December, and January with an average of 50-100 hours per year in each country. These events are mainly driven by large-scale high-pressure systems and extensive low-cloud coverage.
Article
Acoustics
Yanan Zhang, Francesco Avallone, Simon Watson
Summary: With the development of the wind power industry, the condition monitoring and damage detection of wind turbine blades have become increasingly important. This study investigates a new non-contact approach for damage detection based on the measurement of airfoil aerodynamic noise. Experimental results show that the size of trailing edge cracks has a significant impact on the noise level at small angles of attack and low turbulence intensities.
Article
Mechanics
S. Khoshmanesh, S. J. Watson, D. Zarouchas
Summary: This study investigates changes in the stiffness and damping of a thick adhesive joint test specimen during a fatigue test. The results show different phases of damage and the corresponding changes in stiffness and damping.
COMPOSITE STRUCTURES
(2022)
Article
Energy & Fuels
Ana P. Talayero, Julio J. Melero, Andres Llombart, Nurseda Y. Yurusen
Summary: In recent years, photovoltaic (PV) energy development has mainly focused on large utility-scale plants comprising numerous panels connected to high-power inverters. Accurate estimation of power production is necessary for failure detection, identifying production deviations, and integrating the plants into the power grid. This study utilizes machine learning models developed using data from large utility-scale PV plants, incorporating information on non-uniform radiation distribution across the solar field. The optimized models achieved better performance, with random forest technique exhibiting the lowest RMS error ranging from 1.9% to 5.4%, compared to previous models developed for small PV plants.
Article
Green & Sustainable Science & Technology
Sarah J. Ollier, Simon J. Watson
Summary: This study investigates the potential impact of trapped lee waves (TLWs) on a UK near-coastal offshore wind farm, showing that TLWs can significantly alter the wind speeds and power output of individual turbines and the whole wind farm.
WIND ENERGY SCIENCE
(2023)
Proceedings Paper
Energy & Fuels
Julio J. Melero, Jorge Bruna, Javier Leiva
Summary: This paper presents a small part of the Living Lab of Smartcity Malaga, a real low-voltage DC grid, where the authors will carry out metrology-grade measurement to understand the power quality phenomena occurring in the grid.
2022 20TH INTERNATIONAL CONFERENCE ON HARMONICS & QUALITY OF POWER (ICHQP 2022)
(2022)
Proceedings Paper
Energy & Fuels
Ana P. Talayero, Nurseda Y. Yurusen, Francisco Jose Sanchez Ramos, Roberto Lazaro Gaston
Summary: Data preprocessing is a crucial phase in wind resource assessment and wind power curve performance analysis. It involves ensuring high quality and representative data availability to make reliable investment decisions. The current practice relies on manual scanning of data by experts using fixed rules, which is time-consuming and inefficient. This study proposes the use of machine learning algorithms to generate efficient classifiers for unfiltered and filtered data, with tree-based classifiers performing better.
WINDEUROPE ANNUAL EVENT 2022
(2022)
Review
Green & Sustainable Science & Technology
Amir R. Nejad, Jonathan Keller, Yi Guo, Shawn Sheng, Henk Polinder, Simon Watson, Jianning Dong, Zian Qin, Amir Ebrahimi, Ralf Schelenz, Francisco Gutierrez Guzman, Daniel Cornel, Reza Golafshan, Georg Jacobs, Bart Blockmans, Jelle Bosmans, Bert Pluymers, James Carroll, Sofia Koukoura, Edward Hart, Alasdair McDonald, Anand Natarajan, Jone Torsvik, Farid K. Moghadam, Pieter-Jan Daems, Timothy Verstraeten, Cedric Peeters, Jan Helsen
Summary: This paper reviews the development of wind turbine drivetrain technology and identifies future challenges and research gaps, including drivetrain dynamic responses in large or floating turbines, aerodynamic and farm control effects, use of rare-earth material in generators, improving reliability through prognostics, and the use of advances in digitalization.
WIND ENERGY SCIENCE
(2022)
Article
Green & Sustainable Science & Technology
Bedassa R. Cheneka, Simon J. Watson, Sukanta Basu
WIND ENERGY SCIENCE
(2020)
Article
Green & Sustainable Science & Technology
Mark Schelbergen, Peter C. Kalverla, Roland Schmehl, Simon J. Watson
WIND ENERGY SCIENCE
(2020)
Article
Engineering, Industrial
Mateusz Oszczypala, Jakub Konwerski, Jaroslaw Ziolkowski, Jerzy Malachowski
Summary: This article discusses the issues related to the redundancy of k-out-of-n structures and proposes a probabilistic and simulation-based optimization method. The method was applied to real transport systems, demonstrating its effectiveness in reducing costs and improving system availability and performance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Wencheng Huang, Haoran Li, Yanhui Yin, Zhi Zhang, Anhao Xie, Yin Zhang, Guo Cheng
Summary: Inspired by the theory of degree entropy, this study proposes a new node identification approach called Adjacency Information Entropy (AIE) to identify the importance of nodes in urban rail transit networks (URTN). Through numerical and real-world case studies, it is found that AIE can effectively identify important nodes and facilitate connections among non-adjacent nodes.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Liwei Chen
Summary: This paper discusses the four phases of the system life cycle and the different costs associated with each phase. It proposes an improvement importance method to optimize system reliability and analyzes the process of failure risk under limited resources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Xian Zhao, Chen Wang, Siqi Wang
Summary: This paper proposes a new rebalancing strategy for balanced systems by switching standby components. Different switching rules are provided based on different balance conditions. The system reliability is derived using the finite Markov chain imbedding approach, and numerical examples and sensitivity analysis are presented for validation.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Fengyuan Jiang, Sheng Dong
Summary: Corrosion defects are the primary causes of pipeline burst failures. The traditional methodologies ignore the effects of random morphologies on failure behaviors, leading to deviations in remaining strength estimation and reliability analysis. To address this issue, an integrated methodology combining random field, non-linear finite element analysis, and Monte-Carlo Simulation was developed to describe the failure behaviors of pipelines with random defects.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Guoqing Cheng, Jiayi Shen, Fang Wang, Ling Li, Nan Yang
Summary: This paper investigates the optimal joint inspection and mission abort policies for a multi-component system with failure interaction. The proportional hazards model is used to characterize the effect of one component's deterioration on other components' hazard rates. The optimal policy is studied to minimize the expected total cost, and some structural properties of the optimal policy are obtained.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Hongyan Dui, Yaohui Lu, Shaomin Wu
Summary: A new resilience model is proposed in this paper for systems under competing risks, and related indices are introduced for evaluating the system's resilience. The model takes into account the degradation process, external shocks, and maintenance interactions of the system, and its effectiveness is demonstrated through a case study.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yang Li, Jun Xu
Summary: This paper proposes a translation model based on neural network for simulating non-Gaussian stochastic processes. By converting the target non-Gaussian power spectrum to the underlying Gaussian power spectrum, non-Gaussian samples can be generated.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yanyan Liu, Keping Li, Dongyang Yan
Summary: This paper proposes a new random walk method, CBDRWR, to analyze the potential risk of railway accidents. By combining accident causation network, we assign different restart probabilities to each node and improve the transition probabilities. In the case study, the proposed method effectively quantifies the potential risk and identifies key risk sources.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Nan Hai, Daqing Gong, Zixuan Dai
Summary: The current risk management of utility tunnel operation and maintenance is of low quality and efficiency. This study proposes a theoretical model and platform that offer effective decision support and improve the safety of utility tunnel operation and maintenance.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Tomoaki Nishino, Takuya Miyashita, Nobuhito Mori
Summary: A novel modeling methodology is proposed to simulate cascading disasters triggered by tsunamis considering uncertainties. The methodology focuses on tsunami-triggered oil spills and subsequent fires and quantitatively measures the fire hazard. It can help assess and improve risk reduction plans.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Mingjiang Xie, Yifei Wang, Jianli Zhao, Xianjun Pei, Tairui Zhang
Summary: This study investigates the effect of rockfall impact on the health management of pipelines with fatigue cracks and proposes a crack propagation prediction algorithm based on rockfall impact. Dynamic SIF values are obtained through finite element modeling and a method combining multilayer perceptron with Paris' law is used for accurate crack growth prediction. The method is valuable for decision making in pipeline reliability assessment and integrity management.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Saeed Jamalzadeh, Lily Mettenbrink, Kash Barker, Andres D. Gonzalez, Sridhar Radhakrishnan, Jonas Johansson, Elena Bessarabova
Summary: This study proposes an integrated epidemiological-optimization model to quantify the impacts of weaponized disinformation on transportation infrastructure and supply chains. Results show that disinformation targeted at transportation infrastructure can have wide-ranging impacts across different commodities.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Jiaxi Wang
Summary: This paper investigates the depot maintenance packet assignment and crew scheduling problem for high-speed trains. A mixed integer linear programming model is proposed, and computational experiments show the effectiveness and efficiency of the improved model compared to the baseline one.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
Article
Engineering, Industrial
Yuxuan Tian, Xiaoshu Guan, Huabin Sun, Yuequan Bao
Summary: This paper proposes a DFMs searching algorithm based on the graph neural network (GNN) to improve computational efficiency and adaptively identify DFMs. The algorithm terminates prematurely when unable to identify new DFMs.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2024)
