Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Stochastic Planning and Operational Constraint Assessment of System-Customer Power Supply Risks in Electricity Distribution Networks

Version 1 : Received: 29 July 2021 / Approved: 30 July 2021 / Online: 30 July 2021 (09:10:01 CEST)

A peer-reviewed article of this Preprint also exists.

Kisuule, M.; Hernando-Gil, I.; Serugunda, J.; Namaganda-Kiyimba, J.; Ndawula, M.B. Stochastic Planning and Operational Constraint Assessment of System-Customer Power Supply Risks in Electricity Distribution Networks. Sustainability 2021, 13, 9579. Kisuule, M.; Hernando-Gil, I.; Serugunda, J.; Namaganda-Kiyimba, J.; Ndawula, M.B. Stochastic Planning and Operational Constraint Assessment of System-Customer Power Supply Risks in Electricity Distribution Networks. Sustainability 2021, 13, 9579.

Journal reference: Sustainability 2021, 13, 9579
DOI: 10.3390/su13179579

Abstract

Electricity distribution network operators face several operational constraints in the provision of safe and reliable power given that investments for network area reinforcement must be commensurate with improvements in network reliability. This paper provides an integrated approach for assessing the impact of different operational constraints on distribution network reliability by incorporating component lifetime models, time-varying component failure rates as well as the monetary cost of customer interruptions in an all-inclusive probabilistic methodology that applies a time-sequential Monte Carlo simulation. A test distribution network based on the Roy Billinton test system is modelled to investigate the system performance when overloading limits are exceeded as well as when preventive maintenance is performed. Standard reliability indices measuring the frequency and duration of interruptions, and the energy not supplied are complemented with a novel monetary reliability index. The comprehensive assessment includes not only average indices but also their probability distributions to adequately describe the risk of customer interruptions. Results demonstrate the effectiveness of this holistic approach as the impacts of operational decisions are assessed from both reliability and monetary perspectives. This informs network planning decisions through optimum investments and consideration of customer outage costs.

Keywords

component lifetime models; Monte Carlo simulation; network reliability; overloading violations; preventive maintenance; risk assessment; time-varying failure rates

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