Distributed economic dispatch via a predictive scheme: Heterogeneous delays and privacy preservation

被引:34
作者
Chen, Fei [1 ,2 ]
Chen, Xiaozheng [3 ]
Xiang, Linying [2 ]
Ren, Wei [4 ]
机构
[1] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110004, Peoples R China
[2] Northeastern Univ Qinhuangdao, Sch Control Engn, Qinhuangdao 066004, Hebei, Peoples R China
[3] Xiamen Univ, Dept Automat, Xiamen 361005, Fujian, Peoples R China
[4] Univ Calif Riverside, Dept Elect & Comp Engn, Riverside, CA 92521 USA
基金
美国国家科学基金会;
关键词
Economic dispatch; Heterogeneous time-delay; Privacy preservation; Predictive control; Smart grid;
D O I
10.1016/j.automatica.2020.109356
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper studies distributed economic dispatch problems for smart grids, in which a quadratic generation cost is to be minimized over a feasible set that is determined jointly by an equality constraint and a box constraint. Our primary objective is to seek a distributed design that can handle heterogeneous time-delays, while preserving agents' privacy-a fundamental prerequisite that has become gradually important for cyber-physical systems. For this purpose, we design a state predictor for each agent to compensate for the effect of heterogeneous time-delays, which allows the agents to predict the missing states between two consecutive update times. Based upon the predictor, we present a distributed gradient-descent algorithm to locally update the outputs of the generators, which guarantees that the optimal solution is attained in an asymptotic manner. Among other things, we incorporate a privacy preservation scheme to the proposed algorithm in order to preserve agents' privacy and delicately characterize its convergence, differential privacy properties, as well as accuracy. (c) 2020 Elsevier Ltd. All rights reserved.
引用
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页数:8
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