T. H. Chee Tat and P. Fränti, "Real-time Electric Vehicle Load Forecast to Meet Timely Energy Dispatch," 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), Singapore, 2018, pp. 148-153. doi: 10.1109/SOLI.2018.8476758
Electric vehicles are more eco-friendly and energy efficient than the conventional internal combustion engine vehicles. This technology adds new challenge to the existing energy distribution network. Specifically, electric vehicles are allowed to start charging their batteries the moment they are parked into a charging lot which creates a unpredictable load on the energy distribution network. Ideally, the energy supply system must always be in a state where the amount of energy consumed is equal to the amount of energy produced. This priori is also for the reduction of energy wastage. Hence, load forecasting serves as an estimated preemption for the supply system. In this paper, time series techniques for electric vehicles' load forecasting are proposed. Experiments are given using Singapore's energy dispatch system. A framework to provide the relevant electric vehicles' load forecast to fulfill the timing criteria is also proposed.