Control parameterization for power oscillation damping via software-in-the-loop simulation

Ha Thi Nguyen, Guangya Yang, Arne Hejde Nielsen, Peter Højgaard Jensen, Carlos F. Coimbra

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

211 Downloads (Pure)


The parameter optimization of designed controllers for power systems is always a big concern and needs a lot of effort of researchers especially when the electricity grid becomes larger and more complex. The paper proposes a control parameterization using genetic algorithms (GA) for power oscillation damping (POD) incorporating in synchronous condensers via softwarein-the-loop simulation to enhance the damping and frequency stability for low inertia systems. A closed-loop interfaced setup among real-time digital simulator (RTDS), Matlab, and OLE for Process Communication (OPC) running in real time is analyzed and implemented to optimize the POD parameters of a synchronous condenser. Furthermore, a Prony technique based on the system measurement is applied to find out the frequency and damping ratio of the dominant oscillation mode. The POD optimal parameters are determined by the GA objective function that maximizes the damping ratio of the dominant oscillation mode. The effectiveness of the proposed method in damping power oscillations and frequency stability improvement is verified through simulation results of the future Western Danish power system. Simulation results demonstrate that the proposed approach offers a good performance for parameter optimization of the POD.
Original languageEnglish
Title of host publicationProceedings of 7th International Conference on Renewable Power Generation.
Number of pages5
PublisherInstitution of Engineering and Technology
Publication date2018
Publication statusPublished - 2018
Event7th International Conference on Renewable Power Generation - DTU, Kgs. Lyngby, Denmark
Duration: 26 Sep 201827 Sep 2018
Conference number: 7


Conference7th International Conference on Renewable Power Generation
CityKgs. Lyngby


  • Frequency stability
  • Genetic algorithms
  • Parameter optimization
  • Power oscillation damping
  • Software-in-the-loop simulation

Cite this