DocumentCode :
1691482
Title :
Statistical distribution of customer load profiles
Author :
Seppala, Anssi
Author_Institution :
VTT Energy, Finland
Volume :
2
fYear :
1995
Firstpage :
696
Abstract :
The electric utilities need data from customer loads for many purposes. Load research has been activity to collect load data, analyse it and further distribute the results for management and engineers in an electric utility. The Finnish load research project has developed customer class hourly load models for one year with average load values and standard deviation. In many cases in distribution planning or pricing applications the confidence intervals must be approximated for distinct customers or small groups of customers. The simple use of normal distribution will not give reliable estimations for confidence intervals of one customer. Therefore more information is needed from distributions of customer load profiles. The Finnish load research project has studied the disaggregated load distributions of different customer categories. In this report the study of distribution functions of customer load profiles is reported and some results explained. Also some background theory is reviewed
Keywords :
costing; distribution networks; economics; load (electric); power system planning; statistical analysis; Finnish load research project; average load values; confidence intervals approximation; customer class hourly load models; customer load profiles; disaggregated load distributions; distinct customers; distribution planning; load research; pricing applications; statistical distribution; Data analysis; Data engineering; Distribution functions; Engineering management; Gaussian distribution; Load modeling; Power industry; Pricing; Standards development; Statistical distributions;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Energy Management and Power Delivery, 1995. Proceedings of EMPD '95., 1995 International Conference on
Print_ISBN :
0-7803-2981-3
Type :
conf
DOI :
10.1109/EMPD.1995.500813
Filename :
500813
Link To Document :
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