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Neuro-Fuzzy Logic Approach for Electric Load Forecasting of CSPGCL Thermal Units


Author : Rahul Baghel, Yashwant Kashyap and Rahul Pandey

Pages : 1549-1552
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Abstract

The demand of electricity in India is increasing exponentially at the rate of 8-9% per annum. However, the installed power generation capacity of India as on 31st October 2012 was 209276 MW with a peak power shortage of more than 12%. In addition, the demand of electricity is increasing due to increased population, urbanization and comfort level of the peoples. These indicate that India’s future energy requirements are going to be very high. In this paper an attempt has been made for generation forecasting by using a hybrid model of neural networks and fuzzy logic, for the hybrid model input monthly generation of CSPGCL Thermal Unit of CG has been collected from Chhattisgarh State Electricity Board , India .The results obtained from hybrid model has been validated with the actual value and found accurate. The average testing error in the forecasted value is 0.064 in comparison with the desired value.

Keywords: Neuro-Fuzzy Logic; generation Forecasting; Energy Management, neuro-fuzzy

Article published in International Journal of Current  Engineering  and Technology, Vol.3,No.4(Oct- 2013)

 

 

 

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