This paper presents a neural network (NN) based decentralized excitation controller design for large scale power systems. The proposed controller design considers not only the dynamics of generators but also the algebraic constraints of the power flow equations. The control signals are calculated using only local signals. The transient stability and the coordination of the subsystem controllers can be guaranteed. NNs are used to approximate the unknown/imprecise dynamics of the local power system and the interconnections. All signals in the closed loop system are guaranteed to be uniformly ultimately bounded (UUB). Simulation results with a 3-machine power system demonstrate the effectiveness of the proposed controller design.
W. Liu et al., "Neural Network Based Decentralized Excitation Control of Large Scale Power Systems," Proceedings of the International Joint Conference on Neural Networks, 2006. IJCNN'06, Institute of Electrical and Electronics Engineers (IEEE), Jul 2006.
The definitive version is available at https://doi.org/10.1109/IJCNN.2006.246943
International Joint Conference on Neural Networks, 2006. IJCNN'06
Electrical and Computer Engineering
Keywords and Phrases
Decentralized Control; Neural Networks; Power System Control; Large scale systems
Article - Conference proceedings
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