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Power System Planning Using ANN with Fuzzy Logic and Wavelet Analysis


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1 Department of Information Technology, PSG College of Technology, India
     

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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.

Keywords

Power System Planning, Artificial Neural Networks, Regression Analysis, Fuzzy Logic, Wavelet Analysis.
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  • Power System Planning Using ANN with Fuzzy Logic and Wavelet Analysis

Abstract Views: 236  |  PDF Views: 2

Authors

V. Dharma Dharshin
Department of Information Technology, PSG College of Technology, India
R. Rekha
Department of Information Technology, PSG College of Technology, India
R. Vidhyapriya
Department of Information Technology, PSG College of Technology, India

Abstract


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.

Keywords


Power System Planning, Artificial Neural Networks, Regression Analysis, Fuzzy Logic, Wavelet Analysis.