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    https://www.researchgate.net/profile/Muhammad-Ikram-18?ev=hdr_xprf
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Muhammad Ikram

Project - Multi-agent Reinforcement Learning Framework for Ancillary Services in Hybrid Power Plants

Inverter-based resources (IBRs) are gaining prominence due to the high penetration of renewable energy sources. However, they reduce power system inertia, thereby compromising power system stability and grid support services. Hybrid power plants (HPPs), which integrate multiple energy sources in a coordinated manner, offer enhanced flexibility and efficiency in providing these services. However, achieving optimal coordination between different energy sources remains a significant challenge for researchers and power system engineers. Additionally, the dynamic behaviour of IBRs within hybrid power plants poses further challenges in developing optimal coordination and control mechanisms. This project proposes a novel multi-agent reinforcement learning framework for the provision of advanced ancillary services, such as fast frequency response and black start capability.

Research Areas and Interests

  • Multi-agent Deep Reinforcement Learning
  • Distributed Control Power Grids
  • Energy Management Systems
  • Hybrid Power Plants

Qualifications

  • M.Eng. Electrical and Computer Systems, University of Engineering and Technology Peshawar, Pakistan, 2019.

Supervisors

Contact

Muhammad Ikram
School of Engineering
Email: m.ikram@ecu.edu.au

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