Faisal Alsaif

1 month ago | scijournals.onlinelibrary.wiley.com | Praveen Kumar Balachandran |Faisal Alsaif

1 Introduction Photovolatic (PV) systems or solar power systems are very important, especially in the trend toward the adoption of renewable and sustainable energy systems across the globe [1]. With the negative impacts of climate change and with shortage of fossil fuels being experienced across the globe, PV systems present a viable solution since it relays on solar power which is renewable and nonrenewable.

Dec 30, 2024 | nature.com | R. Siva Kumar |Faisal Alsaif |Mohit Bajaj |Ievgen Zaitsev |K. Reddy Madhavi |Arvind R. Singh

The integration of Electric Vehicles (EVs) into power grids introduces several critical challenges, such as limited scalability, inefficiencies in real-time demand management, and significant data privacy and security vulnerabilities within centralized architectures. Furthermore, the increasing demand for decentralized systems necessitates robust solutions to handle the growing volume of EVs while ensuring grid stability and optimizing energy utilization. To address these challenges, this paper presents the Demand Response and Load Balancing using Artificial intelligence (DR-LB-AI) framework. The proposed framework leverages Artificial intelligence (AI) for predictive demand forecasting and dynamic load distribution, enabling real-time optimization of EV charging infrastructure. Furthermore, Blockchain technology is employed to facilitate decentralized, secure communication, ensuring tamper-proof energy transactions while enhancing transparency and trust among stakeholders. The DR-LB-AI framework significantly enhances energy distribution efficiency, reducing grid overload during peak periods by 20%. Through advanced demand forecasting and autonomous load adjustments, the system improves grid stability and optimizes overall energy utilization. Blockchain integration further strengthens security and privacy, delivering a 97.71% improvement in data protection via its decentralized framework. Additionally, the system achieves a 98.43% scalability improvement, effectively managing the growing volume of EVs, and boosts transparency and trust by 96.24% through the use of immutable transaction records. Overall, the findings demonstrate that DR-LB-AI not only mitigates peak demand stress but also accelerates response times for Load Balancing, contributing to a more resilient, scalable, and sustainable EV charging infrastructure. These advancements are critical to the long-term viability of smart grids and the continued expansion of electric mobility.

Dec 2, 2024 | nature.com | Faisal Alsaif

AbstractPlain flaps (PFs) significantly increase camber, enhancing lift and aerodynamic performance when deployed. In Darrieus Vertical Axis Wind Turbines (VAWTs), which perform efficiently in low-speed, turbulent wind conditions, structural modifications like PFs can improve efficiency. This study explores plain flaps with 10-20-degree deflections at different chord lengths to enhance the NACA 2412 aerofoil’s performance.

Jun 20, 2023 | mdpi.com | Faisal Alsaif