EV Smart Charging in Distribution Grids–Experimental Evaluation Using Hardware in the Loop Setup

Abstract

The rising demand for electric vehicles (EVs) in the face of limited grid capacity encourages the development and implementation of smart charging (SC) algorithms. Experimental validation plays a pivotal role in advancing this field. This paper formulates a hierarchical mixed integer programming (MIP) EV SC algorithm designed for low voltage (LV) distribution grid applications. A flexible receding horizon scheme is introduced in response to system uncertainties. It also considers the practical constraints in protocols such as IEC/ISO 15118 and IEC 61851-1. The proposed algorithm is verified and assessed in a Power Hardware-in-the-Loop (PHIL) testbed that incorporates models of real LV distribution grids. Furthermore, the algorithm's capabilities are examined through eight scenarios, out of which four focus on the uncertainties of the input data and two address the engagement of extra grid capacity restrictions. The results demonstrate that the SC algorithm adequately lowers the EV charging cost while fulfilling the charging demand, and substantially reduces the peak power as well as the overloading duration, even when faced with input data uncertainty. The additional grid restrictions in place are proven to improve peak demand reduction and overloading mitigation further. Finally, the limitations and potentials of the developed algorithm are scrutinised.