TY - JOUR
T1 - A distributed continuous time consensus algorithm for maximize social welfare in micro grid
AU - Fu, Zao
AU - He, Xing
AU - Huang, Tingwen
AU - Abu-Rub, Haitham
N1 - Publisher Copyright:
© 2016 The Franklin Institute
PY - 2016/10/1
Y1 - 2016/10/1
N2 - This paper considers a social maximize welfare problem in a micro grid. 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 network and flywheel energy storage system. 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.
AB - This paper considers a social maximize welfare problem in a micro grid. 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 network and flywheel energy storage system. 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.
UR - https://www.scopus.com/pages/publications/84981736899
U2 - 10.1016/j.jfranklin.2016.07.009
DO - 10.1016/j.jfranklin.2016.07.009
M3 - Article
AN - SCOPUS:84981736899
SN - 0016-0032
VL - 353
SP - 3966
EP - 3984
JO - Journal of the Franklin Institute
JF - Journal of the Franklin Institute
IS - 15
ER -