Demand side management verification system for electric vehicles

Abstract

Large-scale grid integration of plug in ElectricVehicles (EVs) brings in many challenges and opportunities for electric power systems. Considering their relatively high power demand and flexibility in terms of charging time, EVs can offer opportunities for demand side management. In particular, the socalled EV Aggregators or Charge Optimization Systems (COS) can optimize the charging schedule of EVs with respect to a number of factors, such as available renewable generation and electricity market prices. However, the optimized schedules must be validated to assure that they do not lead to violation of any operational constraint of the power system. To this aim, major changes in the charging schedules to be applied by COS must be checked with the system operator. This paper describes an EV schedule verification system based on artificial neural networks. This system verifies if the COS schedules can be directly applied or if some modifications are necessary. The proposed approach is tested on two sample distribution systems.

Power Quality Improvement in Distribution Grids via Real-Time Smart Exploitation of Electric Vehicles

“…To tackle loading issues, grid line reinforcement is the long-lasting solution but the expensive one. Thanks to the controllability feature of EV battery inverters, however, these new grid inhabitants can be treated as active elements which can contribute towards improving the quality of the power system [2][3][4][5] based on power quality standards like EN 50160 [6] and EN 61000 [7] and delay the need for power line reinforcement. In this respect, [8] takes into account the loading limits of the distribution transformer and distribution lines to evaluate the maximum EV penetration that can be integrated in the upcoming years without infrastructure reinforcement.…”