Optimizing Electric Vehicle Chargers
Electric vehicles are becoming more and more common, and consequently, the demand for electric vehicle charging stations has increased. While this is commonly viewed as a positive trend, how these chargers affect our environment and consume energy has become a relevant concern. Our goal is to improve existing electric vehicle systems to minimize their operational costs and prioritize renewable energy sources. The objective of our research project is to develop and implement an algorithm for scheduling the charging of electric vehicles at the SLAC National Accelerator Laboratory parking lot in San Mateo. First, we make use of historical data, such as how the users generally behave, electricity prices, and solar outputs from power grids. Second, using existing optimization techniques, we are writing an algorithm that controls the chargers such that they output different power levels based on the current electricity prices, the current solar outputs, and a prediction of the user’s stay duration, calculated from the historical data. Making use of historical data to optimize the charging process of EVs at the SLAC parking lot will give us insight into the challenges of implementing such an algorithm and will aid us in designing future algorithms for larger sustainable systems.