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Miss Margi Shah
Teams and roles for Margi Shah
Graduate Demonstrator
Research student
Overview
Margi Shah is a PhD Canditate at Centre for Integrated Renewable Energy Generation and Supply research group at Cardiff University. Her research interests include power system demand side response, data-driven decision making,distributed optimization and control with applications to power and energy systems.
She received her B.Tech. degree in Electrical Engineering from the Gujarat Technological University-India in 2015, and her M.tech. degree in Power Systems from CSPIT, India in 2017.
She has worked as a Research Fellow in UK-India collaborative project to address system wide impacts of renewable energy sources in engineering program.
Since 2022, She is working towards her PhD (funded by EPSRC) on the thesis enititled: Quantification and Provision of Flexibility from Cyber Pysical Industrial Energy Systems.
Publication
2025
- Shah, M. et al. 2025. Deep reinforcement learning for demand response of a steel plant in energy and spinning reserve markets. Presented at: 2025 IEEE Power & Energy Society General Meeting (PESGM) Austin, TX, USA 27-31 July 2025. IEEE(10.1109/pesgm52009.2025.11225478)
2024
- Shah, M. et al. 2024. A review of reinforcement learning based approaches for industrial demand response. Presented at: 15th International Conference on Applied Energy (ICAE2023) Qatar,Doha 3-7 December 2023. Vol. 40.(10.46855/energy-proceedings-10959)
2020
- Shah, M. and Pandya, K. S. 2020. Applied computational intelligence in power electronic inverter to mitigate harmonics. Presented at: ICPCCI 2019: International Conference on Power, Control and Communication Infrastructure 2019 Ahmedabad, India 4-5 July 2019. Published in: Mehta, A. , Rawat, A. and Chauhan, P. eds. Advances in Electric Power and Energy Infrastructure: Proceedings of ICPCCI 2019. Vol. 608.Springer Science Business Media. , pp.115-127. (10.1007/978-981-15-0206-4_10)
2019
- Sarda, J. , Pandya, K. and Shah, M. 2019. Emerging heuristic optimization algorithms for expansion planning and flexibility optimization in sustainable electrical power systems. Presented at: International Conference on Power, Control and Communication Infrastructure Institute of Infrastructure Technology Research and Management, Ahmedabad, India 4-5 July 2019. Published in: Mehta, A. , Rawat, A. and Chauhan, P. eds. Advances in Control Systems and its Infrastructure. Proceedings of ICPCCI 2019. Vol. 604.Singapore: Springer Science Business Media. , pp.191-200. (10.1007/978-981-15-0226-2_15)
Conferences
- Sarda, J. , Pandya, K. and Shah, M. 2019. Emerging heuristic optimization algorithms for expansion planning and flexibility optimization in sustainable electrical power systems. Presented at: International Conference on Power, Control and Communication Infrastructure Institute of Infrastructure Technology Research and Management, Ahmedabad, India 4-5 July 2019. Published in: Mehta, A. , Rawat, A. and Chauhan, P. eds. Advances in Control Systems and its Infrastructure. Proceedings of ICPCCI 2019. Vol. 604.Singapore: Springer Science Business Media. , pp.191-200. (10.1007/978-981-15-0226-2_15)
- Shah, M. and Pandya, K. S. 2020. Applied computational intelligence in power electronic inverter to mitigate harmonics. Presented at: ICPCCI 2019: International Conference on Power, Control and Communication Infrastructure 2019 Ahmedabad, India 4-5 July 2019. Published in: Mehta, A. , Rawat, A. and Chauhan, P. eds. Advances in Electric Power and Energy Infrastructure: Proceedings of ICPCCI 2019. Vol. 608.Springer Science Business Media. , pp.115-127. (10.1007/978-981-15-0206-4_10)
- Shah, M. et al. 2024. A review of reinforcement learning based approaches for industrial demand response. Presented at: 15th International Conference on Applied Energy (ICAE2023) Qatar,Doha 3-7 December 2023. Vol. 40.(10.46855/energy-proceedings-10959)
- Shah, M. et al. 2025. Deep reinforcement learning for demand response of a steel plant in energy and spinning reserve markets. Presented at: 2025 IEEE Power & Energy Society General Meeting (PESGM) Austin, TX, USA 27-31 July 2025. IEEE(10.1109/pesgm52009.2025.11225478)
Research
Research Interests includes :
- Power system demand side response
- Data driven decision making in smart grid
- Distributed optimization and control with applications to power and energy systems.
Teaching
Demonstrating:
- EN1094-Engineering computing with MATLAB