Congratulations Daniel Kwegyir

Daniel Kwegyir is a graduating PhD student from the Department of Electrical and Electronic Engineering at KNUST.

His research interests are energy management systems, optimisation, and machine learning applications in power systems.

He proposed a rule-based peak-shaving algorithm with dynamic mismatch thresholds for scheduling thermostatically controlled loads (TCLs) in peak demand shaving in power systems in an IoT-enabled environment. The proposed algorithm employs a two-level approach: day-ahead optimisation and intra-day real-time adjustments to control TCLs. The research, which aligns with Goal 7 of the Sustainable Development Goals (SDGs), is a significant step towards ensuring access to affordable, reliable, sustainable, and modern energy for all by 2030.

Daniel is deeply grateful for the support and encouragement he has received from the staff and management of the KNUST Engineering Education Project (KEEP). Their financial support has been instrumental in his academic success.

He plans to continue his research in the development of smart energy systems and machine learning applications in power systems.