Peak load forecasting of Electricity Generating Authority of Thailand by Gaussian Process

This paper use Gaussian Process: GP to present about the peak electricity (Peak load) forecasting for the highest demand of electricity since 2011 to 2012 of “Electricity Generating Authority of Thailand” (EGAT) by use the data since 2000 to 2010 as a the training data. The four important variables are 1) time per month, 2) peak load per month, 3) GDP 4) GNP and present about how to compute the hyper - parameter θ which is the important variable that cause an efficiency forecast. The result of experiment has shown that the process which give few error and has more efficiency than Neural Network (NN).