کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
399594 1438753 2013 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Asset maintenance planning in electric power distribution network using statistical analysis of outage data
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Asset maintenance planning in electric power distribution network using statistical analysis of outage data
چکیده انگلیسی

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.


► A reliability-centred maintenance methodology based on statistical analysis adopted.
► Critical asset identified when RCM methodology was applied to distribution system.
► The identified asset posses highest risk index to the system reliability.
► This methodology lead to beneficial and informed management decisions.
► Decision that can be justified with verified and processed statistical data.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Electrical Power & Energy Systems - Volume 47, May 2013, Pages 424–435
نویسندگان
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