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Issues and concerns
- Development of control algorithms and real-time testing.
- Scaling and testing algorithms for diverse geographical locations and energy systems.
- Validation of control algorithms and real-time testing.
Foresight for the next five years
- Scale-up case studies with real-time system testing.
- Expansion of research scope to address more challenging energy scenarios.
- Contribution to energy-related SDGs by accelerating flexibility in energy resilience.
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Objectives of the research
- Develop an intelligent energy modelling framework for low carbon resilient power grids.
- Focus on multi-criteria decision-making models, AI algorithms, and optimization techniques for hybrid energy systems.
- Develop algorithms for integrating renewable energy sources, conventional generators, and storage.
- Risk assessment methodologies for smart energy systems with resilience against physical, cyber, and extreme event threats.
Collaboration with other entities in the Faculty and external partners
- Extensive collaboration with globally recognised top institutions in South Africa (UI, Wits, NRF), USA and China (Zhejiang University), etc.
- Additional collaboration with international funding agencies (including government like SANEDI, DEDAT, ESKDM, and CSR).
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UP Staff involved: Prof. Ramesh C. Bansal, Prof. R. Naidoo
UP Entities involved: Department of Electrical, Electronic and Computer Engineering, Power Group
Timeline of the entity: Start Date: 2023, End Date: 2027
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