Hierarchical control strategy of electric vehicles with demand response in retail electricity markets

Uncontrolled charging of numerous electric vehicles (EV) can cause problems on distribution transformer and feeder voltage. Demand response (DR) can reduce the loading by incentivizing EV owners to change their charging schedules. DR is composed of two mechanisms, price-based and incentive-based. For the price-based DR, EV owners manage their charging according to price signals to save their charging costs. However, the accumulated loads of the distribution network may unexpectedly increase. This paper develops a combination approach of price-based and incentive-based demand response in a hierarchical manner to alleviate the distribution network problems from passenger EV charging in retail electricity markets. On the bottom level, the EV owners optimize their charging schedules according to the day-ahead real-time pricing (DA-RTP). In case that the accumulated demand is larger than the regulated value, the top-level centralized control will be initiated with incentive direct load control (DLC). To manage on dynamic characteristics of the distribution loads, heuristic algorithm is applied to reduce the run times. The developed approach is simulated with two scenarios regarding structures of retail electricity markets. Both scenarios consist of agents that interact with residential customers in providing the electrical energy and balancing supplies and loads in the distribution networks. The simulation results show that the approach can relieve the problems. Uncertainties due to traffic condition, charging and driving behavior are included in the simulations. Financial aspects of stakeholders are also analyzed.