Leveraging the charging flexibility of electric vehicles in sequential electricity markets with frequency regulation limit

• A general multi-time scale optimization framework is developed for EVs. • Multiple revenue streams are captured in the energy and regulation markets. • The uncertainties from EV and FR deployment are mitigated in the real-time stage. • Frequency limit is quantified and added for realistic estimation of profit potential. As the intraday market plays an important role in absorbing uncertainty from renewable energy sources, deriving trading decisions that optimizing economic benefits across sequential day-ahead and real-time markets become increasingly complex. This paper develops a multi-time scale charging strategy for electric vehicles (EVs) to participate in different electricity market segments. The EV charging optimization is done in two stages: first in a day-ahead scheduling of energy and regulation capacity, and then refined during the day when close to real-time delivery. The EV charging energy and the capacity reserved for frequency regulation are optimized in the day-ahead market. The trading decisions for EV charging energy and regulation capacity in the real-time market are determined considering the uncertainties of EV charging behaviors and the energy deviation from actual delivery of frequency regulation. A dynamic EV control model for frequency regulation is used to quantify the regulation capacity during unforeseen contingencies, which is added to the EV charging optimization as a security constraint. Real data of market prices and regulation signals from PJM (ISO in the United States) is used to analyze the flexibility of EV charging and market revenue potentials by considering all market segments as a whole. Numerical results reveal that providing frequency regulation achieves a cost saving up to 59% for EV charging. Around 27% of the cost saving is obtained by energy transactions in the real-time market. Furthermore, the negative impacts of uncertainties from EV availability and the deployment of frequency regulation are also effectively mitigated by integrating real-time market bidding process into the proposed multi-scale optimization.