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http://dx.doi.org/10.9708/jksci.2011.16.8.137

Monitoring and Prediction of Appliances Electricity Usage Using Neural Network  

Jung, Kyung-Kwon (Korea Electronics Technology Institute)
Choi, Woo-Seung (College of Global General Education, Kyungwon University)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.8, 2011 , pp. 137-146 More about this Journal
Abstract
In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.
Keywords
Energy consumption; Wireless sensor network; Remote monitoring; Neural network; Error backpropagation;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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