TY - JOUR
T1 - Developing a risk breakdown matrix for onshore wind farm projects using fuzzy case-based reasoning
AU - Somi, Sahand
AU - Gerami Seresht, Nima
AU - Fayek, Aminah Robinson
N1 - As a part of the University of Alberta’s Future Energy Systems research initiative, this research was made possible in part thanks to funding from the Canada First Research Excellence Fund, grant number FES-T11-P01, held by Dr. Aminah Robinson Fayek.
PY - 2021/8/15
Y1 - 2021/8/15
N2 - 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.
AB - 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.
KW - Risk identification
KW - Risk breakdown matrix (RBM)
KW - Fuzzy case-based reasoning
KW - Onshore wind farm
KW - Renewable energy project
KW - Work-package–level risk
U2 - 10.1016/j.jclepro.2021.127572
DO - 10.1016/j.jclepro.2021.127572
M3 - Article
SN - 0959-6526
VL - 311
JO - Journal of Cleaner Production
JF - Journal of Cleaner Production
M1 - 127572
ER -
