Electric power demand forecasting: A case study of Lucknow city

Bhardwaj, A. K. and Bansal, R. C. (2011) Electric power demand forecasting: A case study of Lucknow city. Research Journal of Applied Sciences, Engineering and Technology, 3 3: 149-152.

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Author Bhardwaj, A. K.
Bansal, R. C.
Title Electric power demand forecasting: A case study of Lucknow city
Journal name Research Journal of Applied Sciences, Engineering and Technology   Check publisher's open access policy
ISSN 2040-7459
2040-7467
Publication date 2011
Year available 2011
Sub-type Article (original research)
Open Access Status File (Publisher version)
Volume 3
Issue 3
Start page 149
End page 152
Total pages 4
Place of publication Oklahoma City, OK United States
Publisher Maxwell Science Publications
Collection year 2012
Language eng
Subject 1700 Computer Science
2200 Engineering
Abstract The study of forecasting identifies the urgent need for special attention in evolving effective energy policies to alleviate an energy famine in the near future. Since power demand is increasing day by day in entire world and it is also one of the fundamental infrastructure input for the development, its prospects and availability sets significant constraints on the socio-economic growth of every person as well as every country. A care full long-term power plan is imperative for the development of power sector. This need assumes more importance in the state of Uttar Pradesh where the demand for electrical energy is growing at a rapid pace. This study analyses the requirement of electricity with respect to the future population for the major forms of energy in the Lucknow city in Uttar Pradesh state of India. A model consisting of significant key energy indicators have been used for the estimation. Model wherever required refined in the second stage to remove the effect of auto-correlation. The accuracy of the model has been checked using standard statistical techniques and validated against the past data by testing for 'expost' forecast accuracy.
Keyword Energy forecasting
Energy modeling
Power demand
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Information Technology and Electrical Engineering Publications
 
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