Design and Development of Electric Vehicle Charging Station Infrastructure Integrated with a Solar PV-Based Microgrid for Traffic-Responsive Load Management
Year: 2026
Type: article
Abstract: The rapid proliferation of electric vehicles (EVs) is placing an increasingly non-uniform and spatially concentrated demand on distribution networks, particularly at public electric vehicle charging stations (EVCS) situated along high-traffic urban corridors. Uncoordinated charging at such locations can produce sharp power demand peaks, voltage deviations, and elevated dependency on grid-supplied energy, while simultaneously under-utilizing the significant rooftop and canopy area available for distributed solar photovoltaic (PV) generation. This paper presents the design and development of an EVCS infrastructure integrated with a solar PV-based microgrid in which the charging power allocation is dynamically governed by real-time road traffic conditions, referred to here as traffic-responsive load management (TRLM). The proposed architecture combines a rooftop/canopy-mounted PV array with maximum power point tracking (MPPT), a battery energy storage system (BESS) interfaced through a bidirectional DC-DC converter, a grid-tied bidirectional inverter, and multiple Level-2 and DC fast-charging points, all coordinated by a centralized Energy Management System (EMS). A traffic sensing layer, comprising inductive loop/camera-based vehicle counters, continuously estimates a Traffic Density Index (TDI) which modulates the expected EV arrival rate and informs a priority-weighted power allocation algorithm. Mathematical models are developed for the PV array (single-diode model with thermal derating), battery state-of-charge dynamics, the AC/DC power balance of the microgrid, a Poisson-based EV arrival process driven by traffic density, and a multi-objective charging allocation and dispatch strategy that minimizes grid energy cost subject to state-of-charge, converter, and charger-capacity constraints. A time-series simulation was carried out over a representative 24-hour operating cycle using synthesized solar irradiance and traffic density profiles. Results indicate that the proposed traffic-responsive strategy improves the PV self-consumption ratio, reduces the grid dependency ratio and evening peak grid demand relative to a non-traffic-responsive (baseline) charging strategy, and maintains the battery state of charge within safe operating bounds while reducing the average vehicle waiting time during high-traffic intervals. The findings demonstrate that coupling distributed solar generation, battery storage, and real-time traffic intelligence at the EVCS level is a technically viable and economically attractive pathway toward sustainable, grid-friendly electric mobility infrastructure.
Author: Mohammad Ali
Institution: Atlantic International University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7204247866