PhD: Energy management for hybrid PV systems


​As a leading research institute, imec has always been pushing the boundaries of PV cell and module technology development, resulting in increasing performance and reliability figures at decreasing cost. Owing to these developments, we will soon reach a point where PV will become an abundant source of clean energy. However, due to its intermittent and non-dispatchable nature, it will present additional challenges in terms of system stability and grid congestions and will fundamentally challenge the conventional (central) way of operating a power system. Integrating and operating distributed PV in a system-efficient way will be the next big challenge to evolve to a (near) 100% renewable energy system. The solution lies in a more flexible and decentralized system, where local energy management will be key. Local energy management will be required at different levels; from single buildings, over districts to utility scale hybrid PV plants. The focus of the Ph.D. candidate, will be on the latter. 

Hybrid PV plants have the potential to become dispatchable assets thanks to the addition of cost-effective storage solutions. Very short-term and fine-grain forecasts (also known as nowcasting), able to predict high ramp-rates caused by rapid changes in weather conditions due to cloud movement will be crucial for storage management and grid stability. The use of advanced forecasting techniques for proactive power plant control will allow to further boost the growth potential of PV in next generation grid and power system architectures. 

The Ph.D. candidate will expand imec’s multi-scale energy management framework, in order to optimize operation of local, hybrid PV systems equipped with renewable generators and storage. Modelling of system components, integrating short-term forecasting of renewable generation and developing adequate control strategies considering different use cases, will represent an important part of the work of the Ph.D. candidate. Finally, implementation of these developments into imec’s energy management framework and testing the developed algorithms in real life conditions with our industrial partners will be required. 


Required background: Electrical or software engineer with a strong background in modelling and simulation of energy systems in Matlab and/or Python.

Type of work: 40% modelling, 30% implementation of models and simulations, 30% experimental validation

Supervisor: Jef Poortmans

Daily advisor: Joris Lemmens

Apply here