IEC 61851 compliant demand side management algorithm for electric vehicle charging : a MILP based decentralized approach

Abstract

Charging scheduling algorithms play a vital role in diminishing the negative consequences on electricity networks from the widespread adaptation of electro-mobility. Therefore, there is a growing interest in a pragmatic solution that requires only modest resources. To reach this goal, we propose a decentralized, IEC charging standard compliant, two-layer charging scheduling algorithm, which only requires unidirectional communication and reduced computing capabilities. The objective of the algorithm proposed is to achieve valley filling by exploiting the flexibility of electric vehicles through optimal tracking of a target signal. The IEC standard compliant, semi-continuous charging characteristic is attained with a mixed-integer linear formulation. Different formulations of the problem by forming vehicle groups and randomization in charging events are examined. The results show that the IEC 61851-compliant formulation with a semi-continuous charging characteristic for the proposed method fails to perform as good as the variable charging rate formulation, which has a 2.8 and 3.9-fold deviation in the variance of the total demand relative to the variable charging rate at 50% and 100% penetration rates, respectively. Nevertheless, the inclusion of randomization and grouping improves the performance of the IEC standard-compliant formulation. Considering four groups, the variance in demand of semi-continuous charging formulation at 50% penetration is nearly equal to that of the variable charging rate proofing the viable potential of the technically feasible solution proposed.