On modeling insights for emerging engineering problems: A case study on the impact of climate uncertainty on the operational performance of offshore wind farms. (October 2018)

• Record Type: Journal Article
• Authors: Dinwoodie, Iain; McMillan, David; Lazakis, Iraklis; Dalgic, Yalcin; Revie, Matthew
• Other Names: Revie Matthew guest-editor.; Walls Lesley guest-editor.; Bedford Tim guest-editor.
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 232:Number 5(2018:Oct.)
• Page Start: 524
• Page End: 532
• Publication Date: 2018-10
• Subjects: Life cycle engineering -- modeling/simulation -- probabilistic methods -- risk analysis -- Monte Carlo simulation; Reliability (Engineering) -- Mathematical models -- Periodiclals; Risk assessment -- Mathematical models -- Periodicals; Engineering design -- Mathematical models -- Periodicals; 620.00452
• DOI: 10.1177/1748006X17751493
• Languages: English
• ISSNs: 1748-006X

Abstract

This article considers the technical and practical challenges involved in modeling emerging engineering problems. The inherent uncertainty and potential for change in operating environment and procedures add significant complexity to the model development process. This is demonstrated by considering the development of a model to quantify the uncertainty associated with the influence of the wind and wave climate on the energy output of offshore wind farms which may result in sub-optimal operating decisions and site selection due to the competing influence of wind speed on power production and wave conditions on availability. The financial profitability of current and future projects may be threatened if climate uncertainty is not included in the planning and operational decision-making process. A comprehensive climate and wind farm operational model was developed using Monte Carlo operation to model the performance of offshore wind farms, identifying non-linear relationships between climate, availability and energy output. This model was evaluated by engineers planning upcoming offshore wind farms to determine its usefulness for supporting operational decision making. From this, consideration was given to the challenges in applying the Monte Carlo simulation for this decision process and in practice.