Automated control integration of solar and wind energy for sustainable DC microgrid deployment in desert environments for EV charging

Abstract In remote desert regions, where traditional energy infrastructure is often unreliable, sustainable energy solutions are crucial for meeting the power demands of electric vehicles (EVs). This study presents an integrated DC microgrid system powered by solar and wind energy to support EV charging in desert environments. The proposed microgrid uses 35 kW of solar power and 25 kW from a wind turbine, providing a combined capacity of 60 kW. The system employs the Perturb and Observe (P&O) algorithm for Maximum Power Point Tracking (MPPT), optimizing solar energy conversion efficiency. The cloud-based monitoring and control system enables real-time adjustments to system operations to accommodate fluctuating environmental conditions, ensuring a consistent power supply. Simulation and experimental validation under desert conditions demonstrated that the system can reliably deliver power to EV charging stations. The system operates efficiently under varying environmental conditions, with solar power output stabilizing at approximately 35 kW during peak sunlight hours (10 AM to 4 PM), and wind power output peaking at 25 kW during nighttime. The energy storage system, with a capacity of 1200 kWh, provides backup during periods of low solar and wind generation. The proposed system is cost-effective and scalable, offering a feasible solution for off-grid EV charging infrastructure in remote areas. Future work will focus on optimizing component sizing and performing hardware-in-the-loop (HIL) validation to enhance the system’s resilience and performance further.

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Publication Details

Journal
Discover Electronics
Published
2026-03-27
DOI
https://doi.org/10.1007/s44291-026-00192-0
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
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article

Automated control integration of solar and wind energy for sustainable DC microgrid deployment in desert environments for EV charging

Mostak Ahamed, Sajib Tripura, Ibrahim Kholilullah, Hairong Gu et al.
Discover Electronics
Electric Vehicles and Infrastructure
article

Automated control integration of solar and wind energy for sustainable DC microgrid deployment in desert environments for EV charging

Mostak Ahamed, Sajib Tripura, Ibrahim Kholilullah, Hairong Gu, Adil Hussain, Munju Mia, Md Moin Shikder
article en

Abstract

Abstract In remote desert regions, where traditional energy infrastructure is often unreliable, sustainable energy solutions are crucial for meeting the power demands of electric vehicles (EVs). This study presents an integrated DC microgrid system powered by solar and wind energy to support EV charging in desert environments. The proposed microgrid uses 35 kW of solar power and 25 kW from a wind turbine, providing a combined capacity of 60 kW. The system employs the Perturb and Observe (P&O) algorithm for Maximum Power Point Tracking (MPPT), optimizing solar energy conversion efficiency. The cloud-based monitoring and control system enables real-time adjustments to system operations to accommodate fluctuating environmental conditions, ensuring a consistent power supply. Simulation and experimental validation under desert conditions demonstrated that the system can reliably deliver power to EV charging stations. The system operates efficiently under varying environmental conditions, with solar power output stabilizing at approximately 35 kW during peak sunlight hours (10 AM to 4 PM), and wind power output peaking at 25 kW during nighttime. The energy storage system, with a capacity of 1200 kWh, provides backup during periods of low solar and wind generation. The proposed system is cost-effective and scalable, offering a feasible solution for off-grid EV charging infrastructure in remote areas. Future work will focus on optimizing component sizing and performing hardware-in-the-loop (HIL) validation to enhance the system’s resilience and performance further.

Discover ElectronicsVol. 3(1)
Chang'an University (CN), Dhaka University of Engineering & Technology (BD)
Openalex Percentile: Top 5%
Electric Vehicles and Infrastructure
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