• Title/Summary/Keyword: Smart metering networks

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A Study of an Efficient ZigBee Address Assignment Scheme for Home Area Networks of Smart Grid

  • Choi, Dongmin;Chung, Ilyong
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.566-576
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    • 2013
  • In Home Area Network (HAN) of the smart grid, Power Line Communication (PLC) technology and ZigBee communication technology can be used in the communication among the Advanced Metering Infrastructure (AMI) devices. However, according to performance evaluation results of the PLC technology, we find that using the PLC technology is unsuitable for the remote meter reading service. It is worth noting that some parts of the PLC are converted to the ZigBee communication technology in Jeju, Korea. Compared with PLC, ZigBee has no restriction of the place, where the equipments can be freely set up, due to the advantage of radio communication. However, number of usable devices will impact the network performance which is depended on the address assignment. In addition, due to the restriction of transmission range among devices, it is difficult to apply the ZigBee address assignment method to the practical circumstance. In this paper, we examine the previous ZigBee address assignment schemes and the corresponding routing algorithms, and propose a novel address assignment scheme compared with the existing methods, the performance of the proposed one is improved. In particular, evaluation results show that the proposed scheme reduces the average number of hop count, the transfer time and the processing time.

Developing Smart Grids Based on GPRS and ZigBee Technologies Using Queueing Modeling-Based Optimization Algorithm

  • de Castro Souza, Gustavo Batista;Vieira, Flavio Henrique Teles;Lima, Claudio Ribeiro;de Deus, Getulio Antero Junior;de Castro, Marcelo Stehling;de Araujo, Sergio Granato;Vasques, Thiago Lara
    • ETRI Journal
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    • v.38 no.1
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    • pp.41-51
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    • 2016
  • Smart metering systems have become widespread around the world. RF mesh communication systems have contributed to the creation of smarter and more reliable power systems. This paper presents an algorithm for positioning GPRS concentrators to attain delay constraints for a ZigBee-based mesh network. The proposed algorithm determines the number and placement of concentrators using integer linear programming and a queueing model for the given mesh network. The solutions given by the proposed algorithm are validated by verifying the communication network performance through simulations.

A Study of Time Synchronization Methods for IoT Network Nodes

  • Yoo, Sung Geun;Park, Sangil;Lee, Won-Young
    • International journal of advanced smart convergence
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    • v.9 no.1
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    • pp.109-112
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    • 2020
  • Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.

Building Energy Time Series Data Mining for Behavior Analytics and Forecasting Energy consumption

  • Balachander, K;Paulraj, D
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.1957-1980
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    • 2021
  • The significant aim of this research has always been to evaluate the mechanism for efficient and inherently aware usage of vitality in-home devices, thus improving the information of smart metering systems with regard to the usage of selected homes and the time of use. Advances in information processing are commonly used to quantify gigantic building activity data steps to boost the activity efficiency of the building energy systems. Here, some smart data mining models are offered to measure, and predict the time series for energy in order to expose different ephemeral principles for using energy. Such considerations illustrate the use of machines in relation to time, such as day hour, time of day, week, month and year relationships within a family unit, which are key components in gathering and separating the effect of consumers behaviors in the use of energy and their pattern of energy prediction. It is necessary to determine the multiple relations through the usage of different appliances from simultaneous information flows. In comparison, specific relations among interval-based instances where multiple appliances use continue for certain duration are difficult to determine. In order to resolve these difficulties, an unsupervised energy time-series data clustering and a frequent pattern mining study as well as a deep learning technique for estimating energy use were presented. A broad test using true data sets that are rich in smart meter data were conducted. The exact results of the appliance designs that were recognized by the proposed model were filled out by Deep Convolutional Neural Networks (CNN) and Recurrent Neural Networks (LSTM and GRU) at each stage, with consolidated accuracy of 94.79%, 97.99%, 99.61%, for 25%, 50%, and 75%, respectively.

Implementation of Smart Meter Applying Power Consumption Prediction Based on GRU Model (GRU기반 전력사용량 예측을 적용한 스마트 미터기 구현)

  • Lee, Jiyoung;Sun, Young-Ghyu;Lee, Seon-Min;Kim, Soo-Hyun;Kim, Youngkyu;Lee, Wonseoup;Sim, Issac;Kim, Jin-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.19 no.5
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    • pp.93-99
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    • 2019
  • In this paper, we propose a smart meter that uses GRU model, which is one of artificial neural networks, for the efficient energy management. We collected power consumption data that train GRU model through the proposed smart meter. The implemented smart meter has automatic power measurement and real-time observation function and load control function through power consumption prediction. We determined a reference value to control the load by using Root Mean Squared Error (RMS), which is one of performance evaluation indexes, with 20% margin. We confirmed that the smart meter with automatic load control increases the efficiency of energy management.

Leakage detection and management in water distribution systems

  • Sangroula, Uchit;Gnawali, Kapil;Koo, KangMin;Han, KukHeon;Yum, KyungTaek
    • Proceedings of the Korea Water Resources Association Conference
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    • 2019.05a
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    • pp.160-160
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    • 2019
  • Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

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An Efficient Channel Selection and Power Allocation Scheme for TVWS based on Interference Analysis in Smart Metering Infrastructure

  • Huynh, Chuyen Khoa;Lee, Won Cheol
    • Journal of Communications and Networks
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    • v.18 no.1
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    • pp.50-64
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    • 2016
  • Nowadays, smart meter (SM) technology is widely effectively used. In addition, power allocation (PA) and channel selection (CS) are considered problems with many proposed approaches. In this paper, we will suggest a specific scenario for an SM configuration system and show how to solve the optimization problem for transmission between SMs and the data concentrator unit (DCU), the center that collects the data from several SMs, via simulation. An efficient CS with PA scheme is proposed in the TV white space system, which uses the TV band spectrum. On the basic of the optimal configuration requirements, SMs can have a transmission schedule and channel selection to obtain the optimal efficiency of using spectrum resources when transmitting data to the DCU. The optimal goals discussed in this paper are the maximum capacity or maximum channel efficiency and the maximum allowable power of the SMs used to satisfy the quality of service without harm to another wireless system. In addition, minimization of the interference to the digital television system and other SMs is also important and needs to be considered when the solving coexistence scenario. Further, we propose a process that performs an interference analysis scheme by using the spectrum engineering advanced Monte Carlo analysis tool (SEAMCAT), which is an integrated software tool based on a Monte-Carlo simulation method. Briefly, the process is as follows: The optimization process implemented by genetic evolution optimization engines, i.e., a genetic algorithm, will calculate the best configuration for the SM system on the basis of the interference limitation for each SM by SEAMCAT in a specific configuration, which reaches the solution with the best defined optimal goal satisfaction.

Design and Application of a LonRF Device based Sensor Network for an Ubiquitous Home Network (유비쿼터스 홈네트워크를 위한 LonRF 디바이스 기반의 센서 네트워크 설계 및 응용)

  • Ro Kwang-Hyun;Lee Byung-Bog;Park Ae-Soon
    • Journal of the Institute of Convergence Signal Processing
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    • v.7 no.3
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    • pp.87-94
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    • 2006
  • For realizing an ubiquitous home network(uHome-net), various sensors should be able to be connected to an integrated wire/wireless sensor network. This paper describes an application case of applying LonWorks technology being widely used in control network to wire/wireless sensor network in uHome-net and the design and application of LonRF device that consists of a neuron chip including LonTalk protocol, a 433.92MHz RF transceiver, a sensor, and application programs. As an application example of the LonRF device, the LonRF smart badge that can measure the 3D location of objects in indoor environment and interwork with the uHome-net was developed. LonRF device based home network services were realized on the uHome-net testbed such as indoor positioning service, remote surveillance service and remote metering service were realized. This research shows that LonWorks technology based sensor network could be applicable to the control network in an ubiquitous home network and the LonRF device can be used as a wireless node in various sensor networks.

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