Abstract
Power grid is one of the critical infrastructures in human society. It is highly complex in both structure and dynamics. In order to study its performance, different models, such as Kuramoto oscillator network model, power flow model, cascading load model and so on, have been suggested. In this chapter, it is to demonstrate how an evolutionary algorithm can be applied to effectively solve the topological design problem in power grid based on the Kuramoto oscillator network model. Recognizing that multiple criteria are commonly confronted in practice, a multi-objective evolutionary algorithm is developed. Two objectives, namely the network synchronizability and the cost, are considered in this work. In addition, since the design problem is complex and nonlinear, a dedicated local searching mechanism is embedded to enhance the searching capability of the algorithm. Finally, the effectiveness of the proposed algorithm is confirmed by extensive numerical simulations.
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Acknowledgements
The work described in this chapter was supported by a grant from City University of Hong Kong (Project No. 7004422) and the Alexander von Humboldt Research Group Linkage 3.4-IP-DEU/1009882.
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Bi, X., Tang, W.K.S. (2018). A Hybrid Multi-objective Evolutionary Approach for Power Grid Topology Design. In: Zelinka, I., Chen, G. (eds) Evolutionary Algorithms, Swarm Dynamics and Complex Networks. Emergence, Complexity and Computation, vol 26. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55663-4_13
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