{"title":"Self-Triggered Consensus-Based Strategy for Economic Dispatch in Uncertain Communication Networks","authors":"Lianghao Ji;Yuhe Dou;Cuijuan Zhang;Huaqing Li","doi":"10.1109/TNSE.2024.3466997","DOIUrl":null,"url":null,"abstract":"The communication networks of smart grids are often influenced by ubiquitous uncertainty. These uncertainties can directly influence the communication weights between generating units, consequently degrading the performance of economic dispatch (ED) algorithms. Despite this, much of the related work has been centered on ideal communication channels, thereby overlooking the impact of communication uncertainties. Consequently, this paper primarily delves into the economic dispatch problem (EDP) in smart grids with uncertain communication networks. Initially, we propose an adaptive algorithm grounded on an event-triggered strategy. This algorithm can effectively offset the communication uncertainties within a predefined upper limit, thereby facilitating optimal power allocation. Subsequently, we introduced a new self-triggered strategy. This strategy eliminates the need for continuous monitoring of neighboring statuses, leading to a reduction in controller updates and message transmissions, without negatively affecting the system's convergence performance. However, the effectiveness of the self-triggered strategy might be influenced by the accuracy of generator predictions. Finally, simulations demonstrate that the proposed approach effectively mitigates the impact of communication uncertainties on ED performance while reducing communication overhead.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"11 6","pages":"6652-6663"},"PeriodicalIF":6.7000,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10693360/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The communication networks of smart grids are often influenced by ubiquitous uncertainty. These uncertainties can directly influence the communication weights between generating units, consequently degrading the performance of economic dispatch (ED) algorithms. Despite this, much of the related work has been centered on ideal communication channels, thereby overlooking the impact of communication uncertainties. Consequently, this paper primarily delves into the economic dispatch problem (EDP) in smart grids with uncertain communication networks. Initially, we propose an adaptive algorithm grounded on an event-triggered strategy. This algorithm can effectively offset the communication uncertainties within a predefined upper limit, thereby facilitating optimal power allocation. Subsequently, we introduced a new self-triggered strategy. This strategy eliminates the need for continuous monitoring of neighboring statuses, leading to a reduction in controller updates and message transmissions, without negatively affecting the system's convergence performance. However, the effectiveness of the self-triggered strategy might be influenced by the accuracy of generator predictions. Finally, simulations demonstrate that the proposed approach effectively mitigates the impact of communication uncertainties on ED performance while reducing communication overhead.
智能电网的通信网络经常受到无处不在的不确定性的影响。这些不确定性会直接影响发电机组之间的通信权重,从而降低经济调度(ED)算法的性能。尽管如此,大部分相关工作都以理想通信通道为中心,从而忽略了通信不确定性的影响。因此,本文主要研究具有不确定通信网络的智能电网中的经济调度问题(EDP)。首先,我们提出了一种基于事件触发策略的自适应算法。该算法能在预定的上限内有效抵消通信不确定性,从而促进电力的优化分配。随后,我们引入了一种新的自触发策略。这种策略无需持续监控相邻设备的状态,从而减少了控制器更新和信息传输,同时不会对系统的收敛性能产生负面影响。不过,自触发策略的有效性可能会受到发电机预测准确性的影响。最后,模拟结果表明,所提出的方法在减少通信开销的同时,有效地减轻了通信不确定性对 ED 性能的影响。
期刊介绍:
The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.