A review of reliability-based methods for risk analysis and their application in the offshore wind industry. (August 2018)

• Record Type: Journal Article
• Authors: Leimeister, Mareike; Kolios, Athanasios
• Is Part Of: Renewable & sustainable energy reviews. Volume 91(2018)
• Page Start: 1065
• Page End: 1076
• Publication Date: 2018-08
• Subjects: AHP Analytic Hierarchy Process -- ALARP As Low As Reasonably Practicable -- ANP Analytic Network Process -- ATF Artificial Transfer Function -- B(B)N Bayesian (Belief) Network -- BT(A/D) Bow-Tie (Analysis/Diagram) -- CPN Cost Priority Number -- DO Deterministic Optimisation -- ET(A/D) Event Tree (Analysis/Diagram) -- FM Failure Mode -- FMEA Failure Mode and Effects Analysis -- FMECA Failure Mode Effects and Criticality Analysis -- FMMA Failure Mode and Maintenance Analysis -- FORM First Order Reliability Method -- FST Fuzzy Set Theory -- FT(A/D) Fault Tree (Analysis/Diagram) -- HAZID Hazard Identification -- HAZOP Hazard and Operability Studies -- HL Hasofer and Lind -- IS(R)M Importance Sampling (Reduction) Method -- LHS Latin Hypercube Sampling -- LS(F) Limit State (Function) -- MA Markov Analysis -- MADM Multi-Attribute Decision Making -- MCDA Multi-Criteria Decision Analysis -- MCS Monte Carlo Simulation -- NPI Non-Parametric Predictive Inference -- OREDA Offshore Reliability Data -- PDMP Piecewise Deterministic Markov Process -- PNET Probability Network Evaluation Technique -- PoF Probability of Failure -- RA Reliability Analysis -- RAMS Reliability, Availability, Maintainability, and Safety -- RBD Reliability Block Diagram -- RBDO Reliability-Based Design Optimisation -- RI Reliability Index -- RIF Risk Influencing Factor -- RIV Reliability Index Vector -- RPN Risk Priority Number -- RS(M) Response Surface (Method) -- SORM Second Order Reliability Method -- SRSM Stochastic Response Surface Method -- SWIFT Structured What-If Technique -- SWOT Strengths, Weaknesses, Opportunities, and Threats -- TOPSIS Technique for Order Preference by Similarity to Ideal Solution; Reliability -- Quantitative method -- Qualitative method -- Risk analysis -- Offshore wind turbine; Renewable energy sources -- Periodicals; Power resources -- Periodicals; Énergies renouvelables -- Périodiques; Ressources énergétiques -- Périodiques; 333.794
• DOI: 10.1016/j.rser.2018.04.004
• Languages: English
• ISSNs: 1364-0321

Abstract

Abstract: Offshore and marine renewable energy applications are governed by a number of uncertainties relevant to the design process and operational management of assets. Risk and reliability analysis methods can allow for systematic assessment of these uncertainties, supporting decisions integrating associated consequences in case of unexpected events. This paper focuses on the review and classification of such methods applied specifically within the offshore wind industry. The quite broad differentiation between qualitative and quantitative methods, as well as some which could belong to both groups depending on the way in which they are used, is further differentiated, based on the most commonly applied theories. Besides the traditional qualitative failure mode, tree, diagrammatic, and hazard analyses, more sophisticated and novel techniques, such as correlation failure mode analysis, threat matrix, or dynamic fault tree analysis, are coming to the fore. Similarly, the well-practised quantitative approaches of an analytical nature, such as the concept of limit states and first or second order reliability methods, and of a stochastic nature, such as Monte Carlo simulation, response surface, or importance sampling methods, are still common practice. Further, Bayesian approaches, reliability-based design optimisation tools, multivariate analyses, fuzzy set theory, and data pooling strategies are finding more and more use within the reliability assessment of offshore and marine renewable energy assets.