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Efficient Load Forecasting Optimized by Fuzzy Programming and OFDM Transmission
Author(s) -
Sandeep Sachdeva,
Maninder Singh,
Umesh Singh,
Ajat Shatru Arora
Publication year - 2011
Publication title -
advances in fuzzy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 19
eISSN - 1687-711X
pISSN - 1687-7101
DOI - 10.1155/2011/326763
Subject(s) - orthogonal frequency division multiplexing , computer science , fuzzy logic , transmission (telecommunications) , electricity , artificial neural network , real time computing , econometrics , telecommunications , artificial intelligence , engineering , mathematics , electrical engineering , channel (broadcasting)
Today, it is very important for developed and developing countries to consume electricity more efficiently. Though developed countries do not want to waste electricity and developing countries cannot waste electricity. This leads to the concept: load forecasting. This paper is written for the short-term load forecasting on daily basis, hourly, or half-hourly basis or real time load forecasting. But as we move from daily to hourly basis of load forecasting, the error of load forecasting increases. The analysis of this paper is done on previous year's load data records of an engineering college in India using the concept of fuzzy methods. The analysis has been done onMamdani-type membership functions and OFDM (Orthogonal Frequency Division Multiplexing) transmission scheme. Toreduce the error of load forecasting, fuzzy method has been used with Artificial Neural Network (ANN) and OFDM transmission is used to get data from outer world and send outputs to outer world accurately and quickly. The error has been reduced to a considerable level in the range of 2-3%. For further reducing the error, Orthogonal Frequency Division Multiplexing (OFDM) can be used with Reed-Solomon (RS) encoding. Further studies are going on with Fuzzy Regression methods to reduce the error more

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