NDLI: Reliability worth evaluation for distribution system planning and operation using improved actual performance data

Content Provider	IEEE Xplore Digital Library
Author	Eua-Arporn, B. Yokoyama, A. Audomvongseree, K.
Copyright Year	2002
Description	Author affiliation: Electr. Eng. Dept., Chulalongkorn Univ., Bangkok, Thailand (Eua-Arporn, B.)
Abstract	It is widely known that in reliability cost/worth analysis, customer outage cost should be taken into account for the delivery of energy services. Several methodologies have been proposed. However, these methods require a lot of long term statistical data e.g. failure and repair rates, which may not be available at present in developing countries. There are some researches considering reliability cost/worth in term of Actual Performance data. Nevertheless, this method can only evaluate the past performance indices according to its past actual performance data. From this reason, it may not be possible to make a reasonable decision in distribution system planning and design. This paper proposes an approach to cope with this problem. The past performance data and the targets of system planning, customer average interruption duration index (CAIDI) and average power not supplied (APNS), will be used to generate the expect interruption events. To handle the uncertainty in setting the system targets, fuzzy concept is then applied. In this paper the proposed method together with Thailand's customer damage model (CCDF), obtained from the study conducted in the years 2000-2001, is employed to evaluate the reliability worth of the distribution system in Thailand.
Starting Page	74
Ending Page	79
File Size	555841
Page Count	6
File Format	PDF
ISBN	0780375254
DOI	10.1109/TDC.2002.1178263
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-10-06
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Fuzzy sets Costs Uncertainty Power supplies Investments Ear Power system planning Power system modeling Power generation Fuzzy systems
Content Type	Text
Resource Type	Article

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