Naveen Guguloth¹, Bishwajit Dey², Fausto Pedro García Márquez^3,*, Prasenjit Dey¹, Isaac Segovia Ramírez⁴

Energy Engineering, Vol.123, No.3, 2026, DOI:10.32604/ee.2025.073971 - 27 February 2026

Abstract The increasing integration of electric vehicle (EV) loads into power systems necessitates understanding their impact on stability. Small-magnitude perturbations, if persistent, can cause low-frequency oscillations, leading to synchronism loss and mechanical stress. This work analyzes the effect of voltage-dependent EV loads on this small-signal stability. The study models an EV load within a Single-Machine Infinite Bus (SMIB) system. It specifically evaluates the influence of EV charging through the DC link capacitor of a Unified Power Flow Controller (UPFC), a key device for damping oscillations. The system’s performance is compared to a modified version equipped with More >

Lei Su^1,2,3, Wanli Feng^1,2,3, Cao Kan^1,2,3, Mingjiang Wei^1,2,3, Jihai Wang⁴, Pan Yu⁴, Lingxiao Yang^5,*

Energy Engineering, Vol.123, No.3, 2026, DOI:10.32604/ee.2025.071006 - 27 February 2026

Abstract To address the high costs and operational instability of distribution networks caused by the large-scale integration of distributed energy resources (DERs) (such as photovoltaic (PV) systems, wind turbines (WT), and energy storage (ES) devices), and the increased grid load fluctuations and safety risks due to uncoordinated electric vehicles (EVs) charging, this paper proposes a novel dual-scale hierarchical collaborative optimization strategy. This strategy decouples system-level economic dispatch from distributed EV agent control, effectively solving the resource coordination conflicts arising from the high computational complexity, poor scalability of existing centralized optimization, or the reliance on local information… More >

Supriya Wadekar^1,*, Shailendra Mittal¹, Ganesh Wakte², Rajshree Shinde²

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.071761 - 27 December 2025

Abstract Rapid evolutions of the Internet of Electric Vehicles (IoEVs) are reshaping and modernizing transport systems, yet challenges remain in energy efficiency, better battery aging, and grid stability. Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand, thus increasing energy costs and battery aging. This study proposes a smart charging station with an AI-powered Battery Management System (BMS), developed and simulated in MATLAB/Simulink, to increase optimality in energy flow, battery health, and impractical scheduling within the IoEV environment. The system operates through… More >

Hongyu Wang¹, Wenwu Cui¹, Kai Cui¹, Zixuan Meng^2,*, Bin Li², Wei Zhang¹, Wenwen Li¹

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069576 - 27 December 2025

Abstract To achieve low-carbon regulation of electric vehicle (EV) charging loads under the “dual carbon” goals, this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multi-objective optimization. First, a dual-convolution enhanced improved Crossformer prediction model is constructed, which employs parallel 1 × 1 global and 3 × 3 local convolution modules (Integrated Convolution Block, ICB) for multi-scale feature extraction, combined with an Adaptive Spectral Block (ASB) to enhance time-series fluctuation modeling. Based on high-precision predictions, a carbon-electricity cost joint optimization model is further designed to balance economic, environmental, and grid-friendly objectives.… More > Graphic Abstract

Federico Sacchelli¹, Luca Cattani^1,2, Matteo Malavasi¹, Fabio Bozzoli^1,2,*, Corrado Sciancalepore¹

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1351-1364, 2025, DOI:10.32604/fhmt.2025.064154 - 31 October 2025

Abstract This study investigates the feasibility of a novel dual two-phase cooling system for thermal management in lithium-ion batteries used in electric vehicles (EVs). The proposed system aims to combine low-boiling dielectric fluid immersion cooling and pulsating heat pipes (PHPs), in order to leverage the advantages of both technologies for efficient heat dissipation in a completely passive configuration. Experimental evaluations conducted under different discharge conditions demonstrate that the system effectively maintains battery temperatures within the optimal range of 20–40°C, with enhanced temperature uniformity and stability. While the PHP exhibited minimal impact at low power, its role More >

Jack Kiing Teck Wei¹, Mohanad Taher Mohamed Sayed Roshdy¹, Bryan Ho Liang Hui¹, Jalal Tavalaei¹, Hadi Nabipour Afrouzi^2,*

Energy Engineering, Vol.122, No.11, pp. 4755-4775, 2025, DOI:10.32604/ee.2025.069980 - 27 October 2025

Abstract In this article, a hybrid energy storage system powered by renewable energy sources is suggested, which is connected to a grid-tied electric vehicle charging bay (EVCB) in Sarawak and is examined for its techno-economic effects. With a focus on three renewable energy sources, namely hydrokinetic power, solar power, and hydrogen fuel cells, the study seeks to minimize reliance on the electrical grid while meeting the growing demand from the growing electric vehicle (EV) infrastructure. A hybrid renewable energy storage system that combines solar power, hydrogen fuel cells, hydrokinetic power, and the grid was simulated and… More >

J. S. V. Siva Kumar¹, Mahmad Mustafa², Sk. M. Unnisha Begum³, Badugu Suresh⁴, Rajanand Patnaik Narasipuram^5,*

Energy Engineering, Vol.122, No.10, pp. 3891-3904, 2025, DOI:10.32604/ee.2025.070052 - 30 September 2025

Abstract Electric vehicle (EV) monitoring systems commonly depend on IoT-based sensor measurements to track key performance parameters such as vehicle speed, state of charge (SoC), battery temperature, power consumption, motor RPM, and regenerative braking. While these systems enable real-time data acquisition, they are often hindered by sensor noise, communication delays, and measurement uncertainties, which compromise their reliability for critical decision-making. To overcome these limitations, this study introduces a comparative framework that integrates reference signals, a digital twin model emulating ideal system behavior, and real-time IoT measurements. The digital twin provides a predictive and noise-resilient representation of More >

Pralay Roy¹, Pabitra Kumar Biswas¹, Chiranjit Sain^2,*, Taha Selim Ustun^3,*

Energy Engineering, Vol.122, No.10, pp. 4035-4060, 2025, DOI:10.32604/ee.2025.068989 - 30 September 2025

Abstract This study presents the use of an innovative population-based algorithm called the Sine Cosine Algorithm and its metaheuristic form, Quasi Oppositional Sine Cosine Algorithm, to automatic generation control of a multiple-source-based interconnected power system that consists of thermal, gas, and hydro power plants. The Proportional-Integral-Derivative controller, which is utilized for automated generation control in an interconnected hybrid power system with a DC link connecting two regions, has been tuned using the proposed optimization technique. An Electric Vehicle is taken into consideration only as an electrical load. The Quasi Oppositional Sine Cosine method’s performance and efficacy… More >

Salam Al-E’mari¹, Yousef Sanjalawe^2,*, Budoor Allehyani³, Ghader Kurdi⁴, Sharif Makhadmeh², Ameera Jaradat⁵, Duaa Hijazi⁶

CMC-Computers, Materials & Continua, Vol.85, No.2, pp. 3289-3320, 2025, DOI:10.32604/cmc.2025.067950 - 23 September 2025

Abstract Electric Vehicle Charging Systems (EVCS) are increasingly vulnerable to cybersecurity threats as they integrate deeply into smart grids and Internet of Things (IoT) environments, raising significant security challenges. Most existing research primarily emphasizes network-level anomaly detection, leaving critical vulnerabilities at the host level underexplored. This study introduces a novel forensic analysis framework leveraging host-level data, including system logs, kernel events, and Hardware Performance Counters (HPC), to detect and analyze sophisticated cyberattacks such as cryptojacking, Denial-of-Service (DoS), and reconnaissance activities targeting EVCS. Using comprehensive forensic analysis and machine learning models, the proposed framework significantly outperforms existing More >

Harendra Pratap Singh^1,2, Ishfaq Hussain Rather³, Sushil Kumar¹, Mohammad Aljaidi⁴, Omprakash Kaiwartya^5,*

CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 5577-5595, 2025, DOI:10.32604/cmc.2025.065741 - 30 July 2025

Abstract Electric Vehicles (EVs) have emerged as a cleaner, low-carbon, and environmentally friendly alternative to traditional internal combustion engine (ICE) vehicles. With the increasing adoption of EVs, they are expected to eventually replace ICE vehicles entirely. However, the rapid growth of EVs has significantly increased energy demand, posing challenges for power grids and infrastructure. This surge in energy demand has driven advancements in developing efficient charging infrastructure and energy management solutions to mitigate the risks of power outages and disruptions caused by the rising number of EVs on the road. To address these challenges, various deep… More >