Gossip-based algorithm for economic dispatch of microgrids integrating isolated and grid-connected modes

作     者：Yanmeng ZHANG Yalin ZHANG Zhongxin LIU Zengqiang CHEN 

作者机构：College of Artificial Intelligence Nankai University Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2025年第68卷第3期

页      面：258-271页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 080802[工学-电力系统及其自动化] 0808[工学-电气工程] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Natural Science Foundation of China (Grant No. 62103203) Natural Science Foundation of Tianjin (Grant No. 22JCQNJC01440) General Terminal IC Interdisciplinary Science Center of Nankai University 

主　　题：distributed optimization economic dispatch gossip algorithms multi-agent systems consensus algorithm 

摘      要：A gossip-based economic dispatch(ED) algorithm for microgrids is presented in this paper, designed to cope with communication link failures and enable smooth switching of microgrid operation modes. The algorithm is supported by the Push-Pull architecture, which allows its application to direct graphs and relaxes the initial conditions compared to many existing ED algorithms. Under an asynchronous communication network, where only one directed edge is activated at each moment,it has been shown that ED can be achieved with probability 1, provided that the communication graph is strongly ***, in a synchronous communication network, where each directed communication link is activated at each moment with a certain probability, ED is also achieved with probability 1 under the condition that the communication graph is strongly connected. This demonstrates that optimal consensus is reached under randomly switched communication networks as long as the expectation of communication graphs is strongly connected, a condition that is less stringent than the B-strongly connected requirement found in many other studies. The algorithm s use of a non-decreasing variable step size enables a transition from a sub-linear convergence rate, associated with a diminishing step size, to a linear convergence rate. This also lays the groundwork for future improvements in convergence rate through online step size optimization based on the communication topology. Finally,the algorithm s effectiveness and its potential application to anti-collusion are demonstrated through simulations.