Framework for Risk Identification of Renewable Energy Projects Using Fuzzy Case-Based Reasoning

Somi, Sahand, Gerami Seresht, Nima and Fayek, Aminah Robinson (2020) Framework for Risk Identification of Renewable Energy Projects Using Fuzzy Case-Based Reasoning. Sustainability, 12 (13). p. 5231. ISSN 2071-1050

[img]
Preview
Text
sustainability-12-05231-v2.pdf - Published Version
Available under License Creative Commons Attribution 4.0.

Download (1MB) | Preview
Official URL: https://doi.org/10.3390/su12135231

Abstract

Construction projects are highly risk-prone due to both internal factors (e.g., organizational, contractual, project, etc.) and external factors (e.g., environmental, economic, political, etc.). Construction risks can thus have a direct or indirect impact on project objectives, such as cost, time, safety, and quality. Identification of these risks is crucial in order to fulfill project objectives. Many tools and techniques have been proposed for risk identification, including literature review, questionnaire surveys, and expert interviews. However, the majority of these approaches are highly reliant on expert knowledge or prior knowledge of the project. Therefore, the application of such tools and techniques in risk identification for renewable energy projects (e.g., wind farm and solar power plant projects) is challenging due to their novelty and the limited availability of historical data or literature. This paper addresses these challenges by introducing a new risk identification framework for renewable energy projects, which combines case-based reasoning (CBR) with fuzzy logic. CBR helps to solve problems related to novel projects (e.g., renewable energy projects) based on their similarities to existing, well-studied projects (e.g., conventional energy projects). CBR addresses the issue of data scarcity by comparing novel types of construction projects to other well-studied project types and using the similarities between these two sets of projects to solve the different problems associated with novel types of construction projects, such as risk identification of renewable energy projects. Moreover, the integration of fuzzy logic with CBR, to develop fuzzy case-based reasoning (FCBR), increases the applicability of CBR in construction by capturing the subjective uncertainty that exists in construction-related problems. The applicability of the proposed framework was tested on a case study of an onshore wind farm project. The objectives of this paper are to introduce a novel framework for risk identification of renewable energy projects and to identify the risks associated with the construction of onshore wind farm projects at the work package level. The results of this paper will help to improve the risk management of renewable energy projects during the construction phase.

Item Type: Article
Uncontrolled Keywords: risk identification; case-based reasoning (CBR); fuzzy case-based reasoning (FCBR); renewable energy projects
Subjects: H300 Mechanical Engineering
H800 Chemical, Process and Energy Engineering
Department: Faculties > Engineering and Environment > Mechanical and Construction Engineering
Depositing User: Elena Carlaw
Date Deposited: 10 Aug 2020 09:30
Last Modified: 31 Jul 2021 12:06
URI: http://nrl.northumbria.ac.uk/id/eprint/44027

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics