Review
Engineering, Electrical & Electronic
Nuno M. A. Freire, Antonio J. Marques Cardoso
Summary: This paper provides a comprehensive review of fault detection and condition monitoring in wind turbines and PMSGs, with a focus on electromagnetic measurement-based methods. It introduces the basics of PMSG operation and terminology to serve as a reference for engineers and data scientists, and also discusses the experiences and research challenges related to stator winding failures.
Article
Engineering, Environmental
Keyang Liu, Baoping Cai, Qibing Wu, Mingxin Chen, Chao Yang, Javed Akbar Khan, Chenyushu Wang, Hasini Vidumini Weerawarna Pattiyakumbura, Weifeng Ge, Yonghong Liu
Summary: Risk management is crucial for offshore platform safety. A method for risk identification and assessment based on text mining of hidden danger data is proposed, which improves the identification of risk factors and the automation of the assessment.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2023)
Article
Mechanics
Xiang Li, Qing Xiao, Enhao Wang, Christophe Peyrard, Rodolfo T. Goncalves
Summary: In this paper, the fluid-structure interaction of floating offshore wind turbine (FOWT) platforms under complex ocean conditions is investigated. Two types of FOWT platforms, a semi-submersible platform and a barge platform, are studied for their dynamic responses to wave or current. The results show that a semi-submersible platform exhibits larger cross-flow motion and lock-in phenomenon, while a barge platform experiences smaller motion with no significant lock-in within the velocity range examined. Additionally, the study reveals that waves might lead to an enhanced vortex-induced motion (VIM) with a large angle between current and wave.
Article
Computer Science, Information Systems
Hongli Liu, Junchao Chen, Ji Li, Lei Shao, Lei Ren, Lihua Zhu
Summary: An unsupervised and supervised learning method is proposed in this paper for power transformer fault early warning based on electrical quantities and vibration signals. The method uses the Fourier levels of transformer vibration signals under different electrical conditions measured in the field, and employs a spectral clustering algorithm to cluster the vibration features. A decision tree model is then constructed for each cluster to calculate early warning values for the transformer vibration spectrum under different electrical conditions, enabling the assessment of transformer production variability. The proposed method, based on field measurement data and data mining analysis methods, is cheaper and more effective than existing transformer fault warning techniques.
Article
Engineering, Marine
Xin Fang, Honghui Wang, Wenjing Li, Guijie Liu, Baoping Cai
Summary: This paper proposes a fatigue crack growth prediction method for offshore platforms based on digital twin, which establishes a digital twin model and utilizes a finite element surrogate model approach to ensure consistency between virtual and physical models. The method is validated through a crack growth experiment under mixed-mode multi-step loading, demonstrating reduced influence of uncertain factors and accurate crack growth prediction through dynamic tracking.
Article
Engineering, Electrical & Electronic
Kun Yao, Shuangshuang Fan, Ying Wang, Jie Wan, Donghui Yang, Yong Cao
Summary: Anomaly detection of steam turbines is crucial for stable power supply by recognizing infrequent instances within sensor data. This study proposes a hierarchical pre-warning strategy that combines clustering and classification methods for anomaly detection. Experimental results suggest that gradient boosting decision tree and random forest are more precise in detecting real anomalies of steam turbines.
IET GENERATION TRANSMISSION & DISTRIBUTION
(2022)
Article
Automation & Control Systems
Guoliang Lu, Xin Wen, Guangshuo He, Xiaojian Yi, Peng Yan
Summary: In this article, a new dynamic modeling approach called GMWPCs is proposed for health monitoring of rolling element bearings (REBs) by integrating wavelet packet decomposition (WPD) and graph theory. The GMWPCs can enhance the analysis of WPD and enable early detection and fault identification in REBs, demonstrating effectiveness for real engineering applications.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Automation & Control Systems
Guoliang Lu, Xin Wen, Guangshuo He, Xiaojian Yi, Peng Yan
Summary: This article introduces a new dynamic modeling approach GMWPCs, which integrates WPD and graph theory to extract correlation information for early warning detection and fault identification. Experimental results validate the effectiveness and suitability of the proposed framework.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Engineering, Multidisciplinary
Jiaxuan Leng, Paolo Gardoni, Mengmeng Wang, Zhixiong Li, Grzegorz Krolczyk, Shizhe Feng, Atilla Incecik, Weihua Li
Summary: Structural health monitoring (SHM) is regarded as a useful tool for managing and reducing safety risks in offshore wind farms. The jacket structures of offshore wind turbines are susceptible to damages from corrosion and fatigue in complex offshore environments. Effective SHM on jacket structures can significantly reduce operation risk and costs.
STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
(2023)
Article
Engineering, Mechanical
Mingming Song, Silas Christensen, Babak Moaveni, Anders Brandt, Eric Hines
Summary: This paper presents a recursive Bayesian inference framework for joint parameter-input identification and prediction of strain time history of an offshore platform. By using sparse output-only measurements, the proposed method provides more accurate strain predictions, which is of great importance for fatigue monitoring and input estimation.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2022)
Article
Engineering, Marine
Dongxi Liu, Wenjuan Cai, Tianze Lu
Summary: Two sets of experiments were conducted to explore the characteristics of single-layer liquid sloshing in offshore dry oil storage tanks and two-layer liquid sloshing in offshore wet oil storage tanks. The experiments involved free surface sloshing in a partially filled rectangular tank with colored water and interfacial sloshing in an identical tank filled with white oil and colored water. The results showed that the frequency responses of interfacial sloshing were similar to those of free surface sloshing but with smaller amplitudes. The experiments also revealed unique phenomena in two-layer liquid sloshing, such as the generation of complex 3D gravity-capillary waves at the oil-water interface under certain conditions. Comparisons between free surface and interfacial sloshing were made in terms of viscous damping ratio, higher sloshing modes, impact pressure amplitude, and mass center displacement, showing the advantages of wet storage technology in structural safety and dynamic stability.
Article
Green & Sustainable Science & Technology
Yanhua Liu, Ron J. Patton, Shuo Shi
Summary: Offshore wind turbine (OWT) rotors are susceptible to asymmetrical loads caused by blade flapping and turbulent wind flow, leading to enhanced fatigue and reduced power conversion. Individual Pitch Control (IPC) and Collective Pitch Control (CPC) are commonly used to mitigate unbalanced loading, but can result in actuator faults and reduced power generation. This study proposes a Bayesian optimization-based pitch controller and a robust unknown input observer-based FTC scheme to improve pitch control robustness. Monte Carlo simulations confirm the effectiveness of the co-design scheme for load mitigation under various wind loading conditions and actuator faults.
Article
Environmental Sciences
Zhanxin Tang, Bangyu Wu, Weihua Wu, Debo Ma
Summary: Seismic fault structures are crucial for the exploration and exploitation of hydrocarbon resources. Deep-learning-based fault detection methods using 3D convolutional neural networks (CNNs) have been proposed and achieved state-of-the-art (SOTA) results. However, training with 3D data is computationally expensive and may lead to the loss of correlation between seismic slices. To address these issues, a 2.5D fault detection method using multiple neighboring seismic profiles and incorporating the Transformer module in U-net for feature extraction is proposed.
Article
Energy & Fuels
Zhixin Fu, Zihao Zhou, Junpeng Zhu, Yue Yuan, Davide Astolfi
Summary: Traditional machine learning methods have low prediction accuracy due to the use of a single model for input prediction. This paper proposes a combined prediction model using Bayesian-optimized LightGBM and XGBoost machine learning models to improve the accuracy of gearbox condition monitoring in offshore wind turbines. The simulation results demonstrate the effectiveness of the proposed model.
Article
Green & Sustainable Science & Technology
Xiangjing Su, Yanhao Shan, Chaojie Li, Yang Mi, Yang Fu, Zhaoyang Dong
Summary: This study proposed a normal behaviour modelling method based on the spatial-temporal attention module and the gated recurrent unit for condition monitoring of offshore wind turbine gearboxes. The method has superior performance by extracting and fusing spatial and temporal features, with the unique advantage of model interpretability.
IET RENEWABLE POWER GENERATION
(2022)
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)