Stochastic optimisation for secure dynamic AC-load flow in multi-modal CPES

Stochastic optimisation for secure dynamic AC-load flow in multi-modal CPES

Stochastic optimisation for secure dynamic AC-load flow in hybrid multi-modal energy systems under uncertainty

 

Grid-bound resources, in the present project foremostly electricity, but also gas and water, will have a critical role in a world of increased economic activity, and so will the grids themselves. For their design and operation, the growing complexity of decision making under data uncertainty poses challenging optimisation problems for whose solution the advancement of the existing methodology is indispensable. The latter starts with conceptual work on the proper treatment of risk, nonlinearity, and the large-sale nature of resulting models. Optimal power flow (OPF) in alternate-current (AC) networks has a pivotal role, both since it is indispensable for realistic modeling and also mathematically rewarding. Another crucial aspect is the proper inclusion of external uncertainty due to volatile input from renewablesIn the core of the planned investigations there is the development of an appropriate framework of new integrated mathematical models and tailored methods of “engineering value” supporting research into those energy systems prone to forecast errors and uncertainty. In particular, the following topics are addressed:stochastic contingency management, network stability, management of congestions in AC networks under renewable infeed uncertainty, and risk aversion in multimodal energy systems are addressed.

Principal Investigator:
Prof. Dr. R├╝diger Schultz