Risk Methods Applied to Electricity Distribution System in the UAE Electricity Markets
Ahmed Husain Al Marzooqi
Ahmed Husain Al Marzooqi, Institute of Technology Management and Entrepreneurship (IPTK), Universiti Teknikal Malaysia Melaka (UTeM), Melaka, Malaysia.
Manuscript received on January 12, 2020. | Revised Manuscript received on January 30, 2020. | Manuscript published on March 30, 2020. | PP: 80-87 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7149038620/2020©BEIESP | DOI: 10.35940/ijrte.F7149.038620
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Electricity distribution systems (EDSs) are essential pieces of infrastructure for nations worldwide. However, the key assets constituting these systems can be exposed to various forms of risk. The purpose of this research was to explore and explicate the risk management methods applied to electricity distribution system asset management in the United Arab Emirates (UAE) electricity markets. It was a secondary research that encompassed the use of the existing data to explore this issue and address the research questions. The research findings revealed the electricity distribution system asset management exists in the form of real time, mid-term, and long-term. Moreover, it was found that this system could be exposed to economic, environmental, quality, reputational, vulnerability and regulatory risks. Finally, the research findings revealed risk management methods that could be used to the system in the UAE electricity markets are categorized as simplified, standard, and model-based. This study recommended that UAE companies operating in the electricity industry should apply a holistic risk analysis in their electricity distribution system asset management.
Keywords: Electricity Distribution System, Risk Management, Asset Management, UAE.
Scope of the Article: Simulation Optimization and Risk Management