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利用智能电网中的无人机和物联网实现农村和偏远地区智能计量系统的演进

A Possible Smart Metering System Evolution for Rural and Remote Areas Employing Unmanned Aerial Vehicles and Internet of Things in Smart Grids.

机构信息

DITEN Department, University of Genoa, Genoa 16145, Italy.

出版信息

Sensors (Basel). 2021 Feb 26;21(5):1627. doi: 10.3390/s21051627.

DOI:10.3390/s21051627
PMID:33652571
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7956395/
Abstract

The way of generating and distributing energy throughout the electrical grid to all users is evolving. The concept of Smart Grid (SG) took place to enhance the management of the electrical grid infrastructure and its functionalities from the traditional system to an improved one. To measure the energy consumption of the users is one of these functionalities that, in some countries, has already evolved from a periodical manual consumption reading to a more frequent and automatic one, leading to the concept of Smart Metering (SM). Technology improvement could be applied to the SM systems to allow, on one hand, a more efficient way to collect the energy consumption data of each user, and, on the other hand, a better distribution of the available energy through the infrastructure. Widespread communication solutions based on existing telecommunication infrastructures instead of using ad-hoc ones can be exploited for this purpose. In this paper, we recall the basic elements and the evolution of the SM network architecture focusing on how it could further improve in the near future. We report the main technologies and protocols which can be exploited for the data exchange throughout the infrastructure and the pros and cons of each solution. Finally, we propose an innovative solution as a possible evolution of the SM system. This solution is based on a set of Internet of Things (IoT) communication technologies called Low Power Wide Area Network (LPWAN) which could be employed to improve the performance of the currently used technologies and provide additional functionalities. We also propose the employment of Unmanned Aerial Vehicles (UAVs) to periodically collect energy consumption data, with evident advantages especially if employed in rural and remote areas. We show some preliminary performance results which allow assessing the feasibility of the proposed approach.

摘要

整个电网向所有用户发电和供电的方式正在发生变化。智能电网 (SG) 的概念是为了增强对电网基础设施及其功能的管理,从传统系统发展到改进的系统。衡量用户的能源消耗是这些功能之一,在一些国家,已经从定期手动消耗读数发展到更频繁和自动的读数,从而产生了智能计量 (SM) 的概念。可以将技术改进应用于 SM 系统,一方面允许更有效地收集每个用户的能源消耗数据,另一方面通过基础设施更好地分配可用能源。为此,可以利用基于现有电信基础设施的广泛通信解决方案,而不是使用专用解决方案。在本文中,我们回顾了 SM 网络架构的基本要素和演进,重点介绍了它在不久的将来如何进一步改进。我们报告了可用于整个基础设施中数据交换的主要技术和协议,以及每种解决方案的优缺点。最后,我们提出了一种创新的解决方案,作为 SM 系统的可能演进。该解决方案基于一组称为低功耗广域网 (LPWAN) 的物联网 (IoT) 通信技术,可用于提高现有技术的性能并提供额外功能。我们还提议使用无人机 (UAV) 定期收集能源消耗数据,这具有明显的优势,特别是在农村和偏远地区使用时。我们展示了一些初步的性能结果,这些结果允许评估所提出方法的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/2935245a959e/sensors-21-01627-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/598a361afa03/sensors-21-01627-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/1662d31a5507/sensors-21-01627-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/777aaf628636/sensors-21-01627-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/921808a34683/sensors-21-01627-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/d6ee71920996/sensors-21-01627-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/0829a824dd4b/sensors-21-01627-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/84c3fb2844ec/sensors-21-01627-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/5dede0eb08bb/sensors-21-01627-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/2935245a959e/sensors-21-01627-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/598a361afa03/sensors-21-01627-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/1662d31a5507/sensors-21-01627-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/777aaf628636/sensors-21-01627-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/921808a34683/sensors-21-01627-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/d6ee71920996/sensors-21-01627-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/0829a824dd4b/sensors-21-01627-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/84c3fb2844ec/sensors-21-01627-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/5dede0eb08bb/sensors-21-01627-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a6ee/7956395/2935245a959e/sensors-21-01627-g009.jpg

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4
NS-kNN: a modified k-nearest neighbors approach for imputing metabolomics data.NS-kNN:一种改进的 k-最近邻方法,用于代谢组学数据插补。
Metabolomics. 2018 Nov 23;14(12):153. doi: 10.1007/s11306-018-1451-8.
5
Smart Meter Data Collection Using Public Taxis.利用公共出租车收集智能电表数据。
Sensors (Basel). 2018 Jul 16;18(7):2304. doi: 10.3390/s18072304.
6
Towards Integrating Distributed Energy Resources and Storage Devices in Smart Grid.迈向智能电网中分布式能源资源与储能设备的集成
IEEE Internet Things J. 2017 Feb;4(1):192-204. doi: 10.1109/JIOT.2016.2640563. Epub 2016 Dec 15.