Coordinated EV charging for correlated EV and grid loads and PV output using a novel, correlated, probabilistic model

Conventional deterministic electric vehicles (EV) charging coordination is performed assuming the EV and grid loads and PV output are known advance. In contrast, conventional probabilistic EV charging coordination takes into account the uncertainties of EV and grid loads and PV output without considering their mutual correlations. The major drawbacks of these methods are that the conventional deterministic charging increases the probability of voltage and current noncompliance (PVCN), while the conventional probabilistic charging decreases the quality of service (QoS). Therefore, this paper proposes a novel correlated probabilistic model for EV charging loads in coordination with a solar photovoltaic (PV)-rich commercial grid. In this model, correlated samples are generated from uncorrelated samples, which contain various random variables associated with EVs, battery energy storage (BES) and PV. The generated samples are subsequently incorporated in the proposed coordinated EV charging method, where the power factors of BES and PV are also controlled, to maximize QoS while minimizing PVCN. The effectiveness and practicability of the developed model are validated on an IEEE 37-bus unbalanced distribution system, which is associated with the real data of vehicles and solar PV collected from a campus of the University of Queensland.