Developing a risk breakdown matrix for onshore wind farm projects using fuzzy case-based reasoning

Somi, Sahand, Gerami Seresht, Nima and Fayek, Aminah Robinson (2021) Developing a risk breakdown matrix for onshore wind farm projects using fuzzy case-based reasoning. Journal of Cleaner Production, 311. p. 127572. ISSN 0959-6526

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Abstract

As worldwide goals for sustainable development expand, numerous countries are investing in renewable energy projects, particularly onshore and offshore wind farm projects, which have low adverse environmental impacts. Since onshore wind farm projects are novel types of energy infrastructure projects in many countries worldwide, the literature lacks a comprehensive list of risks that affect such projects. The first goal of this paper is to fill the research gap by identifying the work-package–level risks that affect onshore wind farm construction projects and developing a risk breakdown matrix suitable to these projects. However, the application of existing risk identification techniques in these projects is usually hindered by the lack of comprehensive research in the literature, scarcity of historical data, and high cost of acquiring expert knowledge. Consequently, the second goal of this paper is developing a new risk identification technique based on case-based reasoning and fuzzy logic suitable to onshore wind farm projects. The case-based reasoning component enables the identification of risks associated with a given type of construction project based on its similarities to the other types of projects. Moreover, the application of fuzzy logic in the proposed technique allows users to assess the similarities between different types of projects using linguistic variables, and it facilitates the capture of partial similarities between the different types of construction projects. In addition to the novel risk identification technique, this paper presents a risk breakdown matrix of onshore wind farm projects representing 169 risk factors, which are mapped to 11 construction work packages of onshore wind farm projects to improve the risk management process for these projects. The results of this paper and the proposed risk identification technique are compared with conventional techniques, confirming that the proposed technique is suitable to novel types of construction projects like onshore wind farms.

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