Accurately quantifying and assessing the reliability of Offshore Renewable Energy (ORE) devices is critical for the successful commercialisation of the industry. At present, due to the nascent stage of the industry and commercial sensitivities there is very little available reliability field data. This presents an issue: how can the reliability of ORE’s be accurately assessed and predicted with a lack of specific reliability data? ORE devices largely rely on the assessment of surrogate data sources for their reliability assessment. To date there are very few published studies that empirically assess the failure rates of offshore renewable energy devices [1]. The applicability of surrogate data sources to the ORE environment is critical and needs to be more thoroughly evaluated for a robust ORE device reliability assessment. This paper tests two commonly held assumptions used in the reliability assessment of ORE devices. Firstly, the constant failure rate assumption that underpins ORE component failure rate estimations is addressed. Secondly, a model that is often used to assess the reliability of onshore wind components, the Non-Homogeneous Poisson Power Law Process (PLP) model is empirically assessed and trend tested to determine its suitability for use in ORE reliability prediction. This paper suggests that pitch systems, generators and frequency converters cannot be considered to have constant failure rates when analysed via nonrepairable methods. Thus, when performing a reliability assessment of an ORE device using non-repairable surrogate data it cannot always be assumed that these components will exhibit random failures. Secondly, this paper suggests when using repairable system methods, the PLP model is not always accurate at describing the failure behaviour of onshore wind pitch systems, generators and frequency converters whether they are assessed as groups of turbines or individually. Thus, when performing a reliability assessment of an ORE device using repairable surrogate data both model choice and assumptions should be carefully considered.
The pre-commercial development of the tidal energy sector is characterized by a diverse range of technology concepts. Within the spectrum of proposed and developed solutions the three-bladed Horizontal Axis Tidal Turbine (HATT) is one of the more dominant configurations. However, even within this “narrow” classification technology developers have chosen different design solutions and strategies. Major influences on design decisions are the maintenance and repair costs and their impact on Levelised Cost of Energy (LCOE); therefore it is critical to accurately determine reliability to support the engineering and financial decision making. This paper is based upon work done to develop techniques for the reliability analysis of tidal turbines Power Take Off (PTO) systems and proposes a simulation tool for improved reliability prediction. In brief the proposal is to utilize available methodologies and software to demonstrate how the different loading and environmental conditions experienced in tidal impact on PTO reliability. The approach utilizes a system engineering model of the powertrain augmented with physics-of-failure models. Using available surrogate reliability data and the output from the systems engineering modelling a modified probability of failure for a system or component can be generated. The model is capable to simulate the system under nominal, off-design and faulty conditions. By utilizing this approach, the reliability of the turbine can be quantitatively analyzed taking into account realistic operating conditions. An indicative case-study is presented to demonstrate the proposed approach.
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