DocumentCode
2313221
Title
Load Forecasting using Fuzzy Methods
Author
Sachdeva, Sandeep ; Verma, Chander Mohan
Author_Institution
Haryana Eng. Coll., Yamuna Nagar
fYear
2008
fDate
12-15 Oct. 2008
Firstpage
1
Lastpage
4
Abstract
Today, it´s the need of developed and developing countries to consume electricity more efficiently. Though developed countries do not want to waste electricity and developing countries cannot waste electricity. Hence, the wise use of electricity is the need of hour. This leads to the concept - load forecasting. This paper is written for the short term load forecasting on daily basis. Though this can be extended to hourly or half-hourly or real time load forecasting. But as we move from daily to hourly basis of load forecasting the error of load forecasting increases. This paper is written on the practical analysis of previous year´s load data records of an Engineering College in India using the concept of fuzzy methods. The analysis has been done on Mamdani type membership functions. In order to reduce the error of load forecasting on daily basis fuzzy method has been used with artificial network (ANN) with some iteration processes. The error has been reduced to a considerable level in the range of 2-3%. Further studies are going on with fuzzy regression methods to reduce the error more.
Keywords
fuzzy set theory; iterative methods; load forecasting; neural nets; power engineering computing; regression analysis; artificial network; fuzzy methods; fuzzy regression methods; iteration processes; real time load forecasting; short term load forecasting; Artificial neural networks; Convergence; Data analysis; Energy management; Fuzzy logic; Information analysis; Load forecasting; Power system planning; Temperature; Weather forecasting; ART neural network; Fuzzy logic; Load forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Power System Technology and IEEE Power India Conference, 2008. POWERCON 2008. Joint International Conference on
Conference_Location
New Delhi
Print_ISBN
978-1-4244-1763-6
Electronic_ISBN
978-1-4244-1762-9
Type
conf
DOI
10.1109/ICPST.2008.4745206
Filename
4745206
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