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A distributed continuous time consensus algorithm for maximize social welfare in micro grid. (English) Zbl 1345.93008

Summary: This paper considers a social maximize welfare problem in a microgrid. Firstly, to enhance capacity ability and the output stability of generators in a micro grid, a novel social welfare optimization problem is modeled using wavelet neural networks and flywheel energy storage systems. Based on augmented Lagrangian function, a continuous time distributed gradient algorithm is proposed for the novel model. In the framework of nonsmooth analysis and algebraic graph theory, we prove that with the algorithm, the optimal solution can always be found asymptotically. Simulation results on 14-bus and 100-bus systems are presented to substantiate the performance and characteristics of the proposed algorithm.

MSC:

93A14 Decentralized systems
92B20 Neural networks for/in biological studies, artificial life and related topics
93A30 Mathematical modelling of systems (MSC2010)
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