WEC fault modelling and condition monitoring: A graph‐theoretic approach. Issue 5 (7th April 2020)

• Record Type: Journal Article
• Authors: Tang, Yufei; Huang, Yu; Lindbeck, Erica; Lizza, Sam; VanZwieten, James; Tom, Nathan; Yao, Wei
• Is Part Of: IET electric power applications. Volume 14:Issue 5(2020)
• Page Start: 781
• Page End: 788
• Publication Date: 2020-04-07
• Subjects: condition monitoring -- time series -- renewable energy sources -- power grids -- damping -- wave power generation -- power generation control -- fault location -- power generation faults -- power generation protection -- fault tolerant control -- electrical maintenance -- power generation economics -- graph theory -- springs (mechanical) -- power generation reliability -- public domain software; equipment degradation -- harsh operating environment -- WEC systems -- condition monitoring -- fault‐tolerant control -- reliability -- maintenance forecasting -- grid‐connected WEC power -- open‐source modelling platform -- WEC‐Sim -- faulty component models -- electrical faults -- mechanical faults -- WEC model -- basic controller damping -- spring forces -- graph theoretic approach -- fault detection -- multivariate time series -- WEC performance -- wave power -- renewable energy sources -- wave resources -- wave energy converter components -- estimated O&M cost -- operations and maintenance cost -- fault identification; Electric power -- Periodicals; Electric power systems -- Periodicals; 621.305
• DOI: 10.1049/iet-epa.2019.0763
• Languages: English
• ISSNs: 1751-8660

Abstract

Abstract : The nature of wave resources usually requires wave energy converter (WEC) components to handle peak loads (i.e., torques, forces, and powers) that are many times greater than their average loads, accelerating equipment degradation. Moreover, due to their isolated nature and harsh operating environment, WEC systems are projected to possess high operations and maintenance (O&M) cost, i.e., around 27% of their leveled cost of energy. As such, developing techniques to mitigate these costs through the application of condition monitoring and fault tolerant control will significantly impact the economic feasibility of grid connected WEC power. Toward this goal, models of faulty components are developed in the open source modeling platform, WEC‐Sim, to estimate the performance and measurable states of a WEC operating with likely device and sensor failures. Two types of faulty component models are then applied to a point absorber WEC model with basic controller damping and spring forces. Resulting changes in device behavior are recorded as a benchmark, and a graph‐theoretic approach is proposed for fault detection and identification utilizing multivariate time series. Simulation results demonstrate that these faults can greatly affect the WEC performance, and that the proposed method can effectively detect and classify different types of faults.