A Privacy-Preserving Distributed Subgradient Algorithm for the Economic Dispatch Problem in Smart Grid

作     者：Qian Xu Chutian Yu Xiang Yuan Zao Fu Hongzhe Liu Qian Xu;Chutian Yu;Xiang Yuan;Zao Fu;Hongzhe Liu

作者机构：State Grid Zhejiang Economic Research InstituteHangzhou 310008China Beijing Yinshan Technology CO.LTD.Beijing 100871China 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2023年第10卷第7期

页      面：1625-1627页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 0839[工学-网络空间安全] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the Science and Technology Project from State Grid Zhejiang Electric Power CO.Ltd(5211JY20001Q) 

主　　题：optimization iteration preserving 

摘      要：Dear Editor,This letter aims to establish a privacy-preserving distributed optimization algorithm by combining the consensus iteration by subgradients, which not only enables the privacy preservation of optimization but also guarantees the optimality of solutions with some bias *** the setting of distributed optimization, a network of nodes, having their own objective functions depending on the global agents state, would like to distributedly optimize the sum of all objective functions through the local agent-to-agent information change.