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

Mikka Kisuule, Ignacio Hernando-Gil, Jonathan Serugunda, Jane Namaganda-Kiyimba and Mike Brian Ndawula
Additional contact information
Mikka Kisuule: Department of Electrical and Computer Engineering, College of Engineering Design Art and Technology, Makerere University, Kampala P.O. Box 7062, Uganda
Ignacio Hernando-Gil: ESTIA Institute of Technology, University of Bordeaux, 64210 Bidart, France
Jonathan Serugunda: Department of Electrical and Computer Engineering, College of Engineering Design Art and Technology, Makerere University, Kampala P.O. Box 7062, Uganda
Jane Namaganda-Kiyimba: Department of Electrical and Computer Engineering, College of Engineering Design Art and Technology, Makerere University, Kampala P.O. Box 7062, Uganda
Mike Brian Ndawula: Centre for Sustainable Power Distribution, Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK

Sustainability, 2021, vol. 13, issue 17, 1-22

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 was 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 were 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 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:13:y:2021:i:17:p:9579-:d:621893

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