Issues and concernsDevelopment 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 yearsScale-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.
| Objectives of the researchDevelop 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 partnersExtensive 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).
|
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
