Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/3637
Title: LONG TERM ELECTRICITY DEMAND FORECASTING FOR UTTARAKHAND
Authors: Gupta, Nitin Kumar
Keywords: WATER RESOURCES DEVELOPMENT AND MANAGEMENT;LONG TERM ELECTRICITY;FORECASTING;UTTARAKHAND
Issue Date: 2011
Abstract: Long term electricity demand forecasting is one of the most important issues in the operation and system planning. Long term forecast involved identification of both energy and demand changes over a period extending 2 years. The energy requirement besides the type of generating unit (peak or base load unit), expansion and demand of the peak power requirement so as to make strategic investment in the -capacity addition. Long-term electricity demand forecasting plays an important role in the context of generation, transmission and distribution network planning, and future recurred investment cost in a power system. Forecasting the future electrical energy demand of a system is a challenging assignment. As the future is covered with uncertainties, efforts should be made to assess the demands as accurate as possible. The _effects of over and under estimation on the power system and the economic development of the area served by it are to be made. It is important to study and analysis the major factors affecting the magnitude and characteristics of the electrical energy demand. Some forecasting techniques are to be studied. Though several forecasting methods are in use, it is seen that no technique would yield full proof results because of uncertainties of the future. Each of the forecasting method has its own limitations. Accuracy of the forecast depends on the accuracy of the data used. It is necessary to formulate an appropriate and reliable forecasting procedure, suitable for the specific place of interest. In this dissertation work attempt has • been made to formulate by Auto Regressive Integrated Moving Average (ARIMA) model, which could be useful in the estimating the long term requirements and using the future electrical demand for uttrakhand power system has been estimated.
URI: http://hdl.handle.net/123456789/3637
Other Identifiers: M.Tech
Research Supervisor/ Guide: Kansal, M. L.
Das, Devadutta
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (WRDM)

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