A Novel Utilization Factor‐Based Adaptive Coordination Strategy for Electric Vehicle‐to‐Grid and Energy Storage in Peak Load Management

Abstract

Global electric power grids are advancing through the use of Vehicle‐to‐Grid (V2G)technology, hybrid energy storage systems (HESS), and an increasing reliance on renewable energy sources (RES). This paper presents a novel utilization factor (UF)‐based power management strategy to optimally coordinate V2G support in a power system comprising RES and HESS, improving grid resiliency by reducing grid stress from uncontrolled electric vehicle (EV) charging during peak load hours. A UF‐based Power Management (UPM) module generates real‐time power schedules to optimally coordinate V2G support across the available resources. The formulated UF accounts for the proximity, availability, and priority of EVs and hybrid energy storage and provides an adaptive power reference for accurate scheduling under both normal and volatile grid conditions. Local measurements and Long Short‐Term Memory (LSTM) forecast data form the basis for accurate power sharing by the UPM module. The strategy was verified on a modified IEEE 33‐bus system representing a scaled‐down grid connected microgrid in MATLAB/Simulink. The real‐time case study analysis using hardware‐in‐the‐loop experiments on Opal‐RT and a Raspberry Pi controller. At baseload, the UF‐based approach achieved a 6.71% reduction in peak‐hour optimized cost, a 13.06% decrease in per‐unit voltage variation, and a 35.62% reduction in associated losses. At half‐load, the method achieved a 0.04% cost reduction, with a corresponding 35.71% reduction in per‐unit voltage variation and similar losses. The results verified the efficacy of the UPM module for power management, reducing grid stress, especially during peak hours, leveraging V2G, and stabilizing system parameters throughout the scheduling period.