Mannan Hassan
Southwest Jiaotong University
19 Papers
Mannan Hassan is an academic researcher from Southwest Jiaotong University. The author has contributed to research in topics: Computer science & Control theory (sociology). The author has an hindex of 2, co-authored 8 publications. Previous affiliations of Mannan Hassan include University of Engineering and Technology, Lahore.
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Papers
An in-depth analysis of electric vehicle charging station infrastructure, policy implications, and future trends
Muhammad Shahid Mastoi,Shenxian Zhuang,Hafiz Mudassir Munir,Malik Haris,Mannan Hassan,Muhammad Usman,Syed Sabir Hussain Bukhari,Jong-Suk Ro +7 more
TL;DR: In this article , a comprehensive review of the current electric vehicle scenario, the impact of EVs on grid integration, and EV optimal allocation provisioning is presented, and the optimal placement of rapid charging stations is based on economic benefits and grid impacts.
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A study of charging-dispatch strategies and vehicle-to-grid technologies for electric vehicles in distribution networks
Muhammad Shahid Mastoi,Shengxian Zhuang,Hafiz Mudassir Munir,Malik Haris,Mannan Hassan,Mohammed A. Alqarni,Basem Alamri +6 more
TL;DR: In this article , a comprehensive analysis of controlled and uncontrolled charging and discharging methods, delayed charging, indirect controlled discharging, bidirectional charging, and intelligent scheduling is presented.
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Optimal parameter estimation of 1-phase and 3-phase transmission line for various bundle conductor’s using modified whale optimization algorithm
Muhammad Suhail Shaikh,Changchun Hua,Saurav Raj,Shubash Kumar,Mannan Hassan,Muhammad Mohsin Ansari,Munsif Ali Jatoi +6 more
TL;DR: In this article , a modified whale optimization algorithm based on levy flight from four perspectives was proposed to calculate capacitance and inductance per unit length for single-phase and three-phase for the different number of bundle conductors.
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A New Frequency Adaptive Second-Order Disturbance Observer for Sensorless Vector Control of Interior Permanent Magnet Synchronous Motor
TL;DR: A comparative analysis with traditional SMO shows that the proposed FASODO can deliver a better sensorless control performance and a comparison with a frequency adaptive complex coefficient filter enhancedSMO shows a comparable result.
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