Sep 2026· International Journal of Power Electronics and Drive Systems (IJPEDS)· 0 citations· 27 references
Abstract
The growing adoption of electric vehicles (EVs) necessitates intelligent charging strategies to alleviate grid congestion and control rising operational costs. This study introduces an IoT-enabled centralized energy management framework for a PV-BESS-EV integrated smart parking system, leveraging real-time data on carbon emissions, grid pricing, and solar irradiance. A key innovation is its bi-objective optimization model, which simultaneously minimizes both cost and carbon footprint, setting it apart from traditional single-objective approaches. The study evaluates teaching-learning-based optimization (TLBO) and particle swarm optimization (PSO) for addressing the system’s nonlinear challenges. Results indicate that TLBO offers faster convergence and greater robustness, leading to improved load flattening, enhanced PV utilization, and stable battery energy storage system (BESS) state of charge (SoC). Overall, the framework provides a scalable solution that effectively balances economic and environmental objectives for modern grid-integrated EV charging systems.
Electric vehicle (EV) adoption is outpacing grid-only charging infrastructure, which aggravates peak demand, causes voltage instability, and is difficult to deploy in weak-grid or remote regions. Renewable-integrated charging - combining solar, wind, and hybrid generation with storage, power electronics, and intelligen...
Aryan Aurangpure, Manthan Somankar, Parth Kolte et al.· 2026 International Conferenc...· 0 citations
The rapid adoption of electric vehicles (EVs) requires charging infrastructure that is sustainable, power-electronically efficient, and grid-compatible. This study presents a techno-economic and environmental optimization of a hybrid renewable energy-based EV charging station near Guru Nanak Dev Engineering College (GN...
Jeyagopi Raman, S. N. Baskara, Harpreet Kaur Channi· International Journal of Pow...· 0 citations
The widespread adoption of EVs is expected to intensify peak demand, stress distribution networks, and increase carbon emissions if traditional grid-based charging models continue. Therefore, this study proposes a smart-grid-connected microgrid (MG) architecture for EV charging stations (EVCSs) that integrates renewabl...
Kotb M. Kotb, Mohamad E. Zayed, M. Ghazy et al.· World Electric Vehicle Journ...· 0 citations
With the rapid development of the electric vehicle (EV) industry, large-scale integration of EVs into the power grid has led to increasingly prominent problems such as low charging efficiency, intensified load fluctuations, and reduced economic benefits for users. To address these issues, an optimization model is const...
Li-Kui Yi, Jia-Xuan Li, Yu-Qi Sun et al.· Energies· 0 citations
The proposed framework improves operational stability, reduces computational burden, and enhances charging coordination compared with conventional forecasting and heuristic scheduling approaches, and demonstrates the feasibility and scalability of integrating Machine Learning (ML) based forecasting with real-time optim...
D. Janyavula, V. G. Kumar, S. N. Saxena· Engineering, Technology &...· 0 citations
To address the challenges posed by the increasing penetration of renewable energy and electric vehicles (EVs)—such as output fluctuations, time-varying electricity prices, and battery degradation—this study proposes a multi-timescale optimal scheduling method for microgrids that incorporates vehicle–grid interaction-ba...
Shang-Da Xie, Shao-Yuan Li, Gen-Ke Yang· Journal of Renewable and Sus...· 0 citations
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