Peak Electricity Demand Prediction Model for Sri Lanka Power System

Accurate prediction of daily peak electricity demand is a requirement for service reliability, system stability and operating performance of a power system in the field of electrical engineering. This has now become a very important factor for Sri Lanka power system, since the available power plants are to be dispatched in an economical and reliable manner especially during the peak demand period of the chronological load profile. Therefore the prediction of next day peak electricity demand to an acceptable accuracy is useful for the system control centre (SCC) of the Ceylon Electricity Board (CEB). However, presently the unit commitment to meet the next day peak electricity demand is being mostly done by the system control engineers based on their past experience in the field of operation with respect to the day, period and other factors. This research paper carefully identifies sensitive elements which affect the daily peak demand of Sri Lanka power system and develop two forecasting models, namely linear statistical "Multiple Regression" and feed forward "Artificial Neural Network". Both models were developed and fine-tuned using recorded peak demands of Sri Lanka power system from year 2008 to 2011 taken from the SCC of CEB and tested for the calendar year 2012 and also for the first few months of 2013. Artificial Neural Network model was found to be the best fit model for the prediction of daily peak demand of Sri Lanka power system with the lowest Mean Absolute Percentage Error (MAPE).