Predicting electricity demands

Wednesday, April 17, 2019 - 08:40 in Mathematics & Economics

Research published in the International Journal of Energy Technology and Policy shows how a neural network can be trained with a genetic algorithm to forecasting short-term demands on electricity load. Chawalit Jeenanunta and Darshana Abeyrathna of Thammasat University, in Thani, Thailand, explain that it is critical for electricity producers to be able to estimate how much demand there will be on their systems in the next 48 hours. Without such predictions, there will inevitably be shortfalls in power generation when demand is higher than estimated or energy and resources wasted if demand is lower than expected.

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