“20th PSCC 2018 papers submission and review platform

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Dynamic Optimal Power Flow with Storage Restrictions Using Augmented Lagrangian Algorithm

Incorporating time-coupled storage restrictions in the nonlinear dynamic optimal power flow poses a major challenge in terms of performance and solvability. As a consequence, the application of existing works that combine AC optimal power flow with integration of storage are usually restricted to problems of small size or short periods of time coupling. In this work, an approach using an augmented Lagrangian algorithm for the decoupling of the storage component has been developed, which is suitable for solving large-scale problems. The iterative methodology, which is highly scalable and allows for parallelization up to the total amount of time steps, takes multiple storage units into account. The approach has been tested using a data set of the German transmission network consisting of 950 buses and 26 hydro storage units. The proposed method shows robust results in terms of convergence as well as a promising performance characteristic for an increasing number of simulated time steps.

Author(s):

Manuel Ruppert    
Karlsruhe Institute of Technology (KIT)
Germany

Viktor Slednev    
Karlsruhe Institute of Technology (KIT)
Germany

Armin Ardone    
Karlsruhe Institute of Technology (KIT)
Germany

Wolf Fichtner    
Karlsruhe Institute of Technology (KIT)
Germany

 

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