Asset maintenance planning in electric power distribution network using statistical analysis of outage data

Adoghe, A. U. and Awosope, C. O. A. and Ekeh, J.C. (2013) Asset maintenance planning in electric power distribution network using statistical analysis of outage data. Electrical Power and Energy Systems, 47. pp. 424-435.

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Abstract

The problems faced by electric power utilities in developing countries today is that the power demand is increasing rapidly whereas the supply growth is constrained by aging generating and distributing assets, scarce resources for constructing new ones and other societal issues. This has resulted in the need for constructing new additional generating plants and a more economic ways of planning and maintaining existing Generating and Electric power distribution assets. System planning and maintenance that is based on reliability – centred asset management approach had been adopted in this paper. Maintenance of critical asset is an essential part of asset management in distribution network. In most Electric utilities, planning for maintenance constitutes an essential parts of asset management. In this paper, an enhanced RCM methodology that is based on a quantitative statistical analysis of outage data Performed at system/component level for overall system reliability was applied for the identification of distribution components critical to system reliability. The conclusion from this study shows that it is beneficial to base asset maintenance management decisions on processed, analyzed and tested outage data.

Item Type:	Article
Uncontrolled Keywords:	Maintenance planning Asset management Statistical analysis Outage data
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User:	Mrs Hannah Akinwumi
Date Deposited:	21 Mar 2015 17:59
Last Modified:	21 Mar 2015 17:59
URI:	http://eprints.covenantuniversity.edu.ng/id/eprint/4132

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