Optimal open-circuit voltage (OCV) model for improved electric vehicle battery state-of-charge in V2G services

Electric vehicles (EVs) with voltage-to-grid (V2G) capability are useful in augmenting grid capability to handle high energy demand of end users during peak periods. We propose a hybrid state-of-charge (SOC) battery model with aggregator to optimize battery charging and maintain grid stability during peak periods. The proposed SOC model leverages the advantages of three well-known previously proposed battery models namely: Shepherd, Unnewehr and Nernst models. The proposed hybrid model is a combination of the merits of the three specified empirical Lithium-ion battery models to optimize slow charging. This will enhance battery performance by improving its depth-of-discharge profile. This results in enhanced V2G capability and longer driving time for EV owners. Battery parameters used in the simulation are for Nissan Leaf 2019 EV. The proposed SOC model parameters are used to optimize a two-objective function which is used by the aggregator to maximize benefits to both EV owners and DSO. Multi-objective genetic algorithm (MOGA) is used to optimize the objective function because of its ability to obtain non-dominated solutions while still maintaining diversity of the solutions. From simulation results, proposed OCV model improves battery SOC by 10% after V2G operating period (2 p.m.) compared to a case without the model. Also, proposed model earns aggregator $445 and $45 more for voltage and frequency regulation services, respectively. Voltage stability of all 5 considered grid buses of the IEEE 33-node system remains at 0.9–1.0 p.u.