Hierarchical Volt-VAR Optimization Framework Considering Voltage Control of Smart Electric Vehicle Charging Stations Under Uncertainty

Smart electric vehicle charging stations (EVCSs) equipped with distributed energy resources (DERs), such as photovoltaic (PV) systems and storage (ESSs), are promising entities for maintaining voltage quality in power distribution networks through regulation using the smart inverters of DERs. This study proposes a hierarchical Volt-VAR optimization (VVO) framework that reflects capability EVCSs, which consists global local control stages. At stage, EVCSs cooperate conventional regulators, an on-load tap changer (OLTC) capacitor banks (CBs)), PV to minimize total active losses deviations along determination optimal parameters droop functions inverters. quickly mitigate violations dynamically varying their calculated from stage. Under uncertainties generation outputs driving patterns users, deterministic optimization-based VVO problem at stage is reformulated into chance-constrained problem. A simulation was performed IEEE 33-bus system OLTC, CBs, systems, EVCSs. The results demonstrate effectiveness proposed terms loss/voltage deviation, optimized function, probability level chance constraints.