Orchestrating Mass Deployment of Electric Vehicles in Distribution Grids

Abstract

This thesis aims to construct a systematic framework for integrating Electric Vehicles (EVs) into Low Voltage (LV) distribution grids. The ultimate goal is to develop a multi-functional, flexible and reliable smart charging (SC) algorithm enabling EV mass deployment in LV distribution grids. The framework for achieving the main research objective is segmented into several key parts:

- Conducting a thorough study on the EV mass deployment in distribution grids through grid load flow analysis.
- Performing a comparative investigation of representative heuristic EV charging tactics to establish a foundation for a smart charging algorithm.
- Developing a Power Transfer Distribution Factors (PTDF) based grid congestion prevention mechanism from the Distribution System Operator (DSO) perspective in anticipation of widespread EV connections.
- Designing, refining and validating a flexible, efficient and reliable hierarchical mixed integer programming (MIP) EV smart charging algorithm.
a. The developed algorithm is equipped with a passive stochasticity processing function and considers practical constraints in protocols such as IEC/ISO 15118 and IEC 61851-1. It is verified and assessed in a Power Hardware-In-the-Loop (PHIL) testbed.
b. Based on the experimental results, the algorithm's effectiveness is further enhanced in: charging current command levelling for a steadier charging process, upgrading grid balancing services, and acquiring a higher level of proximity to optimality. The stochasticity managing function is also upgraded for ad hoc admittance of (future) erratic charging events and self-correction of charging parameters.
c. The advanced EV smart charging algorithm is then assessed by comparing with uncontrolled and one heuristic charging method presented in part 2 above.