The electricity load required for the forthcoming years are predetermined by means of power system planning. Accuracy is the crucial factor that must be taken care of in the power system planning. Electricity is generally volatile, that is it changes and hence appropriate estimation must be done without leading to overestimation or underestimation. The aim of the project is to do appropriate power estimation with the help of the economic factors. The 9 input factors used are GDP, industry, imports, CO2 emission, exports, services, manufacturing, population, per capita consumption. The proposed methodology is done by means of Neural Network concept and Wavelet Analysis. Regression Analysis is also performed and the comparisons are done using Fuzzy Logic. The nonlinear model, Artificial Neural Network and the Wavelet Analysis are found to be more accurate and effective.
V. Dharma Dharshin, R. Rekha, R. Vidhyapriya
PSG College of Technology, India
Power System Planning, Artificial Neural Networks, Regression Analysis, Fuzzy Logic, Wavelet Analysis | Published By :
ICTACT
Published In :
ICTACT Journal on Soft Computing
( Volume: 7 , Issue: 1 )
Date of Publication :
October 2016
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