Optimized tuning of power oscillation damping controllers using probabilistic approach to enhance small-signal stability considering stochastic time delay
- 64 Downloads
Communication latency which inherently occurs in wide area measurement system greatly degrades small-signal stability (SSS) and is stochastic in nature, and thus, the current power oscillation damping controllers (PODCs) designed to improve SSS must consider this crucial factor. This paper proposes a probabilistic method to tune the parameters of PODCs incorporated in renewable farms to improve SSS under stochastic time delay and under other power system uncertainties arising due to renewable energy resources and loads. The proposed method is composed of two stages: The first stage quantifies the effect of time delay and other power system uncertainties on SSS, and the second stage uses this information to formulate an optimization problem. This optimization problem is solved with the help of four swarm intelligence-based optimization algorithms which are: bat algorithm, cuckoo search algorithm, firefly algorithm, and particle swarm optimization algorithm. The solutions from all these four optimization algorithms are compared, and the best result is used to optimize the parameters of the PODCs. All the analyses were conducted on a modified IEEE 68 bus system. The results show that the PODCs tuned using the proposed method greatly enhances the SSS margin under different scenarios and are probabilistically robust to the varying time delay and other power system uncertainties.
KeywordsCumulant Probability function Swarm intelligence algorithms Wide area damping controller
The authors would like to express thanks for the Petchra-Pra Jom Klao research scholarship, funded by the King Mongkut’s University of Technology Thonburi for the support.
- 16.Gurung S, Naetiladdanon S, Sangswang A (2019) Coordination of power system stabilizers and battery energy-storage system controllers to improve probabilistic small-signal stability considering integration of renewable-energy resources. Appl Sci 9(6):1109. https://doi.org/10.3390/app9061109 CrossRefGoogle Scholar
- 27.REN21 R (2018) Global Status Report, REN21 Secretariat, Paris, France. Tech. RepGoogle Scholar
- 29.Naduvathuparambil B, Valenti MC, Feliachi A (2002) Communication delays in wide area measurement systems. In: Proceedings of the thirty-fourth southeastern symposium on system theory (Cat. No. 02EX540). IEEE, pp 118–122Google Scholar
- 32.Sauer PW, Pai M (1998) Power system dynamics and stability, vol 1. Prentice Hall, LondonGoogle Scholar
- 33.Pal B, Chaudhuri B (2006) Robust control in power systems. Springer, BerlinGoogle Scholar
- 35.DIgSILENT Gmbh (2018) User Manual. http://www.digsilent.de/en/downloads.html. Accessed 1 Mar 2019
- 36.Stativa A, Gavrilaş M, Stahie V (2012) Optimal tuning and placement of power system stabilizer using particle swarm optimization algorithm. In: 2012 International conference and exposition on electrical and power engineering. IEEE, pp 242–247Google Scholar
- 37.Yang XS (2014) Cuckoo search and firefly algorithm: overview and analysis. In: Cuckoo search and firefly algorithm. Springer, Berlin, pp 1–26Google Scholar