Energy Demand Management of Electric Vehicles

The aim of this thesis is to investigate novel recharging schemes for energy demand management (DM) of electric vehicles (EVs). While there has been a lot of work highlighting the importance of energy DM of EVs, most of the reported works do not expand on suggesting how such a DM system may be implemented. In this thesis the focus is on two aspects of DM system implementation. At the instantaneous control time scale, an alternative mechanism for frequency regulation with the aim of neutralising sudden changes in output power of electric generators is presented. At the recharge planning time scale, the aim is to avoid congestion and undesirable voltage drops in the distribution system, and a novel approach is presented that can improve voltage profiles. The problem of considering both voltage congestion and frequency regulation in a composite DM framework is also addressed. At the instantaneous control time scale, a novel distributed recharging rate controller is presented that is based on non-linear control and that yields a real time and distributed solution. This controller minimises communication overheads and allows EVs to join and leave at arbitrary times. From the perspective of recharging rate allocation, the controller achieves a Pareto efficient allocation which is also proportionally fair. The proposed controller is then applied to a system with a single, isolated, and unregulated synchronous machine and it is shown that the frequency can be used as proxy to the imbalance between produced and consumed electric power and hence communication overhead can be eliminated in such cases. A protocol is also discussed that can modify the controller and can implement the modified controller in a multi-machine system. Simulation is used to show the frequency regulation and fairness of recharging rates of EVs when the protocol and the modified controller are used. Subsequently, the integration of the recharging rate controller with the legacy protection system is also discussed. At the recharge planning time scale, the problem of congestion in the distribution system is addressed. Most of published literature on distribution system voltage issues deals with control of various network elements, for instance, on-load tap changers or banks of shunt capacitors on the distribution feeders. In this thesis, a complementary approach 7 8 is presented that can also improve voltage profile by scheduling EV load in such a manner that undesirable voltage drops are avoided or their severity is diminished. In this context, a novel approach is presented for recharging EVs in the same geographic neighbourhood that share the same secondary circuits when recharging. The approach is based on a numerical method called Smoothed Particle Hydrodynamics (SPH) that has been previously used by other researchers to solve the equations of fluid dynamics. The characteristics of the method used for the proposed approach as well as its performance in term of improvement in the reduction of voltage drops and its adaptation to elastic and non-elastic loads is highlighted via simulation. Finally, the approach is extended to also provide a frequency control reserve service.