Distributed Control Enforcing Group Sparsity in Smart Grids

被引:0
|
作者
Sauerteig, Philipp [1 ]
Jiang, Yuning [1 ,2 ]
Houska, Boris [2 ]
Worthmann, Karl [1 ]
机构
[1] Tech Univ Ilmenau, Inst Math, Ilmenau, Germany
[2] Shanghai Tech Univ, Sch Informat Sci & Technol, Shanghai, Peoples R China
来源
IFAC PAPERSONLINE | 2020年 / 53卷 / 02期
关键词
Distributed control; Predictive control; Structural optimization; Smart power applications; OPTIMIZATION; ALGORITHM;
D O I
10.1016/j.ifacol.2020.12.156
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In modern smart grids, charging of local energy storage devices is coordinated within the distribution grid to compensate the volatile aggregated power demand on the time interval of interest. However, this results in a perpetual usage of all batteries which in return reduces their lifetime. In this paper, we enforce group sparsity by using an l(p, q)-regularization on the control to counteract this phenomenon. This leads to a non-smooth convex optimization problem, for which a tailored Alternating Direction Method of Multipliers algorithm is proposed. Furthermore, the algorithm is embedded in a Model Predictive Control framework. Numerical simulations show that the proposed scheme yields sparse control while achieving reasonable overall peak shaving. Copyright (C) 2020 The Authors.
引用
收藏
页码:13269 / 13274
页数:6
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