Real-time Electric Vehicle Load Forecast to Meet Timely Energy Dispatch
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CitationTat, Thomas Ho Chee. Fränti, Pasi. (2018). Real-time Electric Vehicle Load Forecast to Meet Timely Energy Dispatch. Proceedings of the 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI 2018), 148-153. 10.1109/SOLI.2018.8476758.
Electric vehicles are more eco-friendly and energyefficient than the conventional internal combustion engine vehi-cles. This technology adds new challenge to the existing energydistribution network. Specifically, electric vehicles are allowedto start charging their batteries the moment they are parkedinto a charging lot which creates a unpredictable load on theenergy distribution network. Ideally, the energy supply systemmust always be in a state where the amount of energy consumedis equal to the amount of energy produced. This priori is also forthe reduction of energy wastage. Hence, load forecasting serves asan estimated preemption for the supply system. In this paper, timeseries techniques for electric vehicles’ load forecasting are pro-posed. Experiments are given using Singapore’s energy dispatchsystem. A framework to provide the relevant electric vehicles’load forecast to fulfill the timing criteria is also proposed.