Jessica B Whitten and Bhuvana Ramachandran
Electric Vehicles, Load Forecasting, Battery Electric Vehicles, Electric Grids
Electric Vehicles represent an important and futuristic alternative to conventional vehicles. However, the effect of charging electric vehicles on electric grids must be taken into account to prevent accidental overloading of the distribution grid due to simultaneous charging/discharging of electric vehicles. As electric vehicles gain more popularity with consumers, power companies and utilities must be prepared for the added load. To assist in this preparation, power companies will need accurate load forecasting algorithms. This paper presents the development of an algorithm that forecasts the load for Battery Electric Vehicles, or BEVs at 15 minute intervals for any day between January 1, 2011 and December 31, 2023. The forecast algorithm uses the projected BEV growth rate, the population of the parking lot or garage of inquiry, and a probability distribution which relates the state of charge (SOC) of the vehicle’s battery to the percent of EV owners that require such charging daily. After development of the algorithm, simulations of the projected load population were performed in MATLAB. These results present the BEV load from each incoming population wave as an exponentially decaying function with a peak proportional to the size of the electric vehicle population. The developed approach can be applied easily to any parking lot or garage by identifying population wave sizes and their arrival times and applying the SOC probability distribution to each incoming wave.
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