Dr. Asad Waqar

PhD Theme/Topic: Incorporating Flexibility into Power Distribution Grids Amid New Energy Shifts

Supervisor: Dr. Asad Waqar, Sr. Professor
Contact #: 0312-5173920
Email: asadwaqar.buic@bahria.edu.pk
Campus/School/Dept: BUIC H-11/SEAS/EE
RAC Approved Supervisor for Research Areas: Electrical Power Systems, Distributed Generation, Integration of Electric Vehicles and Renewable Energy

Supervisory Record:
PhD Produced: 02
PhD Enrolled: 02
MS/MPhil Produced: 33
MS/MPhil Enrolled: 0 

Topic Brief Description: 

Grid flexibility refers to the system’s capability to adjust generation and consumption in real time in response to operational signals, ensuring security and reliability, especially as the share of uncertain sources such as solar and wind increases.

Incorporating flexibility into power distribution grids involves deploying strategies that enable the grid to adapt to the uncertainty introduced by renewable energy sources while maintaining stability and reliability. Flexibility can be enhanced through technologies such as energy storage, demand response, plug-in electric vehicles, smart grid intelligent controls, and AI-based planning tools.

Key components include intelligent control of power flow via advanced devices, dynamic network reconfiguration, and the establishment of local flexibility markets to incentivize service providers to support the grid. AI methods play a crucial role in modeling, forecasting, and optimizing flexibility resources.

Research Objectives/Deliverables:

1. To optimize feeder and network topologies to improve power flow and enhance flexibility.
2. To employ and evaluate flexibility-enabling technologies such as storage systems, demand response, and electric vehicles for improved grid resilience.
3. To design intelligent control strategies and automation schemes for real-time management of power distribution networks.
4. To develop AI-based forecasting and decision-making tools to support planning and operation of flexibility resources.
5. To assess the feasibility and operational benefits of local flexibility markets as mechanisms for grid support and congestion mitigation.

Research Questions:

1.  How can feeder and network reconfiguration be optimized to improve power flow and enhance operational flexibility under variable renewable conditions?
2. Which combination of energy storage, demand response, and EV integration offers the greatest improvement in grid flexibility and stability?
3. What types of intelligent control and automation systems can most effectively manage power flows and maintain reliability in real time?
4. How can AI-based forecasting and optimization models improve planning, scheduling, and utilization of flexibility resources in distribution grids?
5. Under what technical and market conditions can local flexibility markets operate effectively and provide value to both the grid and service participants?

Candidate’s Eligibility Profile:

1. The applicant must have an MS/MPhil/Equivalent degree in electrical engineering with CGPA > 3.0. Besides, applicants must have a strong background in mathematics, AI, optimization theory and related fields.
2. Experience with programming languages such as Fortran, C/C++, MATLAB, or Python is a must. Candidates should thrive in an international environment and have excellent communication skills to actively contribute to team research efforts.
3. Proficiency in spoken and written English is essential. We value independence and responsibility while promoting teamwork and collaboration among colleagues.