{"title":"Voltage Regulation Service Pricing in Cyber-Physical Distribution Networks With Multi-Dimensional Meteorological Uncertainties","authors":"Zhaobin Wei;Zhenyu Huang;Zhiyuan Tang;Huiming Chen;Xianwang Zuo;Haotang Li;Haoqiang Liu;Jichun Liu;Alberto Borghetti","doi":"10.1109/TNSE.2024.3512580","DOIUrl":null,"url":null,"abstract":"Uncertainties of distributed renewable energy and load demand induced by meteorological factors pose a significant challenge to the voltage quality of the distribution network. This paper addresses this issue from a cyber-physical perspective, by proposing a novel voltage regulation (VR) service pricing for the distribution network. Specifically, an improved nonparametric kernel density estimation method characterized by adaptive variable bandwidth is proposed to measure the coupling among different meteorological factors. The intervals of photovoltaic power and air-conditioning load are defined by a novel affine algorithm with high performance, integrated with mandatory boundary and space approximation techniques. The distribution-level VR market is based on an affiliated layered communication architecture characterized by cloud-edge-terminal collaboration and message queue telemetry transport protocol. A grid-aware voltage regulation interval optimization model is proposed to determine the voltage regulation service price through an electrical distance-based rule. Case studies show that the proposed price can significantly facilitate robust VR decisions, promote the voltage-friendly behavior of VR service providers, and reduce the VR cost by about 20.96% compared to the currently adopted pricing mechanisms.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 2","pages":"710-726"},"PeriodicalIF":6.7000,"publicationDate":"2024-12-09","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/10786310/","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
Uncertainties of distributed renewable energy and load demand induced by meteorological factors pose a significant challenge to the voltage quality of the distribution network. This paper addresses this issue from a cyber-physical perspective, by proposing a novel voltage regulation (VR) service pricing for the distribution network. Specifically, an improved nonparametric kernel density estimation method characterized by adaptive variable bandwidth is proposed to measure the coupling among different meteorological factors. The intervals of photovoltaic power and air-conditioning load are defined by a novel affine algorithm with high performance, integrated with mandatory boundary and space approximation techniques. The distribution-level VR market is based on an affiliated layered communication architecture characterized by cloud-edge-terminal collaboration and message queue telemetry transport protocol. A grid-aware voltage regulation interval optimization model is proposed to determine the voltage regulation service price through an electrical distance-based rule. Case studies show that the proposed price can significantly facilitate robust VR decisions, promote the voltage-friendly behavior of VR service providers, and reduce the VR cost by about 20.96% compared to the currently adopted pricing mechanisms.
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.