Autonomous Demand Side Management of Electric Vehicles

Muhandiram Arachchige Subodha Tharangi Ireshika will defend the thesis for Autonomous Demand Side Management of Electric Vehicles for the PhD degree.

Ireshika has followed the PhD programme at the faculty of Engineering and Science, with Specialization in Renewable Energy.

Summary of the thesis

The increasing number of Electric Vehicles (EVs) presents new challenges in the planning and operation of electric grids, particularly for low voltage distribution grids. Uncoordinated and random charging of EVs could significantly stress the distribution grids causing increased peak demands, voltage fluctuations, increased losses, and overloading in the cables and transformers. These undesirable impacts can be prevented by proper coordination of EV charging using demand side management (DSM) strategies. EVs offer high temporal flexibility since they are available for charging over prolonged periods of time, providing an opportunity for grid-friendly integration.

This thesis presents a systematic investigation of DSM strategies for EV charging management. First, two typically employed DSM strategies are investigated: a voltage droop control-based and a market-driven approach. Then, an optimal power tracking-based method is proposed and investigated. This method aims to flatten the load curve using a unidirectionally communicated grid-induced power signal. To investigate the feasibility of the proposed method in practical environments, model predictive control is proposed to minimize the impact of the estimation errors associated with the uncertainties due to grid-load conditions and user behaviour.

A set of time series load flow simulations is performed within the context of representative Austrian distribution grids to assess the impact on the operation of the distribution grids resulting from the DSM algorithms investigated.

See more information about the thesis, disputation and how to follow online.