Reliability Enhancement in Power Networks under Uncertainty from Distributed Energy Resources

Mike Brian Ndawula, Sasa Z. Djokic and Ignacio Hernando-Gil
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Mike Brian Ndawula: Centre for Sustainable Power Distribution, Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK
Sasa Z. Djokic: Institute for Energy Systems, University of Edinburgh, King’s Buildings, Mayfield Road, Edinburgh EH9 3JL, UK
Ignacio Hernando-Gil: Centre for Sustainable Power Distribution, Department of Electronic and Electrical Engineering, University of Bath, Bath BA2 7AY, UK

Energies, 2019, vol. 12, issue 3, 1-24

Abstract: This paper presents an integrated approach for assessing the impact that distributed energy resources (DERs), including intermittent photovoltaic (PV) generation, might have on the reliability performance of power networks. A test distribution system, based on a typical urban MV and LV networks in the UK, is modelled and used to investigate potential benefits of the local renewable generation, demand-manageable loads and coordinated energy storage. The conventional Monte Carlo method is modified to include time-variation of electricity demand profiles and failure rates of network components. Additionally, a theoretical interruption model is employed to assess more accurately the moment in time when interruptions to electricity customers are likely to occur. Accordingly, the impact of the spatio-temporal variation of DERs on reliability performance is quantified in terms of the effect of network outages. The potential benefits from smart grid functionalities are assessed through both system- and customer-oriented reliability indices, with special attention to energy not supplied to customers, as well as frequency and duration of supply interruptions. The paper also discusses deployment of an intelligent energy management system to control local energy generation-storage-demand resources that can resolve uncertainties in renewable-based generation and ensure highly reliable and continuous supply to all connected customers.

Keywords: demand profiles; demand response; distributed (PV) generation; energy storage; failure rate; Monte Carlo simulation; network reliability; renewable resources (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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