Courses Offered
Undergraduate Courses
- EE212 | Electrical Network Analysis
- EE312 | Power Distribution and Utilization
- EE313 | Power Generation and Transmission
- PE452 | Power System Protection
- PE453 | Power System Operation and Control
- PE445 | Power Plant Engineering
Graduate Courses
- EE517 | Power Distribution System Modeling and Simulation
Refereed Journal Publications
14) F. Ahmed, A. Arshad, A. U. Rehman, M. H. Alqahtani, & K. Mahmoud,” Effective Incentive-Based Demand Response with Voltage Support Capability Via Reinforcement Learning Based Multi-Agent Framework”, Energy Reports (Accepted).
13) S. A. Khan, A. U. Rehman, A. Arshad, M. H. Alqahtani, K. Mahmoud and M. Lehtonen, “Effective Voting-based Ensemble Learning for Segregated Load Forecasting with Low Sampling Data,” IEEE Access, https://doi: 10.1109/ACCESS.2024.3413679.
12) N. Qamar, A. Arshad, R.J. Millar, K. Mahmoud, & M. Lehtonen, “Probabilistic Hosting Capacity Assessment Towards Efficient PV-Rich Low -Voltage Distribution Networks”, Electric Power System Research (EPSR), https://doi.org/10.1016/j.epsr.2023.109940.
11) N. Qamar, A. Arshad, R.J. Millar, K. Mahmoud, & M. Lehtonen, “Machine Learning Based Hosting Capacity Determination Methodology for Low Voltage Distribution Networks”, IET Generation, Transmission and Distribution, https://doi.org/10.1049/gtd2.12933.
10) N. Qamar, A. Arshad, K. Mahmoud, & M. Lehtonen, “Hosting capacity in distribution grids: A review of definitions, performance indices, determination methodologies, and enhancement techniques”, Energy Science & Engineering, 11(4), 1536-1559, 2023.
9) D. A. Khan, A. Arshad, M. Lehtonen, and K. Mahmoud, “Combined DR Pricing and Voltage Control Using Reinforcement Learning Based Multi-Agents and Load Forecasting,” in IEEE Access, vol. 10, pp. 130839-130849, 2022.
8) M. Zakir, A. Arshad, H. A. Sher, A. Al-Durra,” Design and implementation of a fault detection method for a PV-fed DC-microgrid with power control mechanism,” IET Electric Power Applications, vol. 16, no. 9, p. 1057-1071, Sept. 2022
7) Muhammad Zakir, Hadeed Ahmed Sher, Ammar Arshad, Matti Lehtonen, “A fault detection, localization, and categorization method for PV fed DC-microgrid with power-sharing management among the nano-grids”, International Journal of Electrical Power & Energy Systems, Volume 137, 2022, 107858, ISSN 0142-0615, https://doi.org/10.1016/j.ijepes.2021.107858.
6) Fatima, Samar, Verner Püvi, Ammar Arshad, Mahdi Pourakbari-Kasmaei, and Matti Lehtonen. 2021. “Comparison of Economical and Technical Photovoltaic Hosting Capacity Limits in Distribution Networks” Energies 14, no. 9: 2405.
5) A. Arshad and M. Lehtonen, “A comprehensive voltage control strategy with voltage flicker compensation for highly PV penetrated distribution networks,” Electric Power System Research, vol. 172, pp. 105-113, 2019.
4) A. Arshad and M. Lehtonen, “A stochastic assessment of PV hosting capacity enhancement in distribution network utilizing voltage support techniques,” IEEE Access, vol. 7, pp. 46461-46471, 2019.
3) A. Arshad, J. Ekstrom, and M. Lehtonen, “Multi-agent based distributed voltage regulation scheme with grid-tied inverters in active distribution networks,” Electric Power System Research, vol. 160, pp. 180-190, 2018.
2) A. Arshad, V. Püvi and M. Lehtonen, “Monte Carlo based comprehensive assessment of PV hosting capacity and energy storage impact in realistic Finnish low voltage networks,” Energies, vol. 11, issue 6, 1467, 2017.
1) A. Arshad, M. Lindner, and M. Lehtonen, “An analysis of photo-voltaic hosting capacity in Finnish low voltage distribution networks,” Energies, vol. 10, issue 11, 1702, 2017.
Selected Conference Publications
11) A. Maqbool, A. U. Rehman, & A. Arshad,” Effective Deep Learning-based Load Forecasting at Segregated and Aggregated Levels with Low Data Granularity” Accepted in ICPSE 2024.
10) F. Ahmed, A. Arshad, & A. U. Rehman, “Comparative Analysis of Time Series Forecasting of a Household Load Consumption with LSTM Neural Networks and XG-Boost Model” 3rd International Conference on Engineering & Computing Technologies, ICECT 2024.
9) Waleed, M. M. Ashraf, A. Arshad “Artificial hummingbird algorithm based dynamic generation expansion planning considering renewable energy sources,” International Conference on Emerging Power Technologies (ICEPT), Topi, Pakistan, 2023.
8) Haseeb, M. M. Ashraf, A. Arshad “Emission constrained generation expansion planning considering site dependent renewable energy sources of Pakistan,” International Conference on Emerging Power Technologies (ICEPT), Topi, Pakistan, 2023.
7) D. A. Khan, A. Arshad, and Z. Ali, “Performance Analysis of Machine Learning Techniques for Load Forecasting,” 2021 16th International Conference on Emerging Technologies (ICET), 2021, pp. 1-6, DOI: 10.1109/ICET54505.2021.9689903.
6) M. Zakir, A. Arshad, H. Sher, and M. Lehtonen, “An Optimal Power Management System Based on Load Demand and Resources Availability for PV Fed DC-Microgrid with Power-Sharing among Multiple Nanogrids” IEEE PES ISGT Conference Europe, Helsinki, 18-21 Oct. 2021.
5) S. O. Shah, A. Arshad, and S. Alam, “Reactive Power Compensation Utilizing FACTS Devices,” 2021 International Conference on Emerging Power Technologies (ICEPT), 2021, pp. 1-6.
4) A. Arshad and M. Lehtonen, “Instantaneous Flicker Control Strategy with OLTC-Fitted Distribution Transformers in LV Networks,” 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 2020, pp. 544-548,
3) A. Arshad and M. Lehtonen, “Probabilistic Assessment of Photovoltaic Hosting Capacity in Finnish LV Network,” IEEE PES ISGT Conference Europe, Bucharest, 29th Sept. 2nd Oct. 2019.
2) A. Arshad and M. Lehtonen, “Instantaneous Active/Reactive Power Control Strategy for Flicker Mitigation under High PV Penetration,” IEEE PES ISGT Conference Europe, Sarajevo, 21st-25th Oct. 2018.
1) A. Arshad and M. Lehtonen, “Multi-agent system based distributed voltage control in medium voltage distribution systems,” 17th International Scientific Conference on Electric Power Engineering (EPE), Prague, 16th-18th May 2016.
Graduate Supervision
MS Students
| Sr. # | Student name | Thesis | Role | Published work |
|---|
| 6) | M. Fayaz (2024) | Reinforcement Learning Based Multi-Agent System Utilization for Voltage Control and Demand Response in Distribution networks | Supervisor | J14, C10 |
| 5) | M. Shazaib (2024) | Segregated Load Forecasting Utilizing Machine Learning Techniques | Co-Supervisor | J13 |
| 4) | Naveed Qamar (2023) | Machine Learning-Based PV Hosting Capacity Determination of Low Voltage Distribution Networks | Supervisor | J10, J11, J12 |
| 3) | Danyal Afghan(2022) | Multi-Agent-Based Demand Response and Voltage Control in Distribution Networks | Supervisor | C7, J9 |
| 2) | M. Zakir (2021) | A Fault Finding Method for DC Microgrid | Co-Supervisor | J7, C6, J8 |
| 1) | Syed Osama Shah (2020) | Reactive Power Compensation Utilizing FACTS Devices | Co-Supervisor | C5 |
