Energy loss estimation in distribution feeders

• Published in: IEEE transactions on power delivery Vol. 21; no. 3; pp. 1092 - 1100
• Main Authors: Rao, P.S.N., Deekshit, R.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01-07-2006; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Agricultural engineering; Applied sciences; Collaboration; Collection; Costs; Distribution systems; Electrical engineering. Electrical power engineering; Electrical power engineering; Energy distribution; Energy loss; Estimating; Exact sciences and technology; Feeders; Government; Instruments; loss estimation; Loss measurement; Metering; Miscellaneous; Networks; Power engineering and energy; Power generation economics; Power networks and lines; primary and secondary distribution networks; radial feeders; Thumb; Utilities; radial feeders; Instruments; Energy distribution; Expert system; Distribution systems; Energy loss; Electrical network; primary and secondary distribution networks; Reliability; Distribution network; Comparative study; loss estimation; Data gathering
• ISSN: 0885-8977; 1937-4208
• DOI: 10.1109/TPWRD.2005.861240

Energy losses in distribution systems are generally estimated rather than measured, because of inadequate metering in these systems and also due to the high cost of data collection. These estimations are generally based on some rules of thumb. This paper presents the results of a joint investigation undertaken in collaboration with a local utility to study this issue. Based on data collected from feeders specially instrumented for this purpose, true losses in some primary and secondary feeders are obtained. These losses are compared with the estimated losses obtained by the methods presently in use. In view of the large discrepancies observed between measured and estimated values, two new schemes for estimating losses in primary and secondary distribution networks have been developed. The measured values are used to highlight the reliability of the new estimation methods.