Design and implementation of a low-cost arduino-based high-frequency AC waveform meter board for the raspberry pi

Quintana, Matias; Lange, Henning; Bergés, Mario

doi:10.1145/3137133.3141441

Cited by 5 publications

(3 citation statements)

References 3 publications

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“…Table 1 presents a comparison of various energy monitoring devices discussed in the literature. Each device is evaluated based on several criteria, including communication AMMeter [5] Acme-A [6] YoMo [7] Demo Board [8] IoT Sensor [9] MEDAL [10] YoMoPie [11] Proposed Communication…”

Section: Literature Reviewmentioning

confidence: 99%

Smart Edge Device Utilizing Power Line Communication for Energy Management and Control of Electrical Appliances

Varanasi,

Jonnalagadda,

Karri

2024

IEEE Access

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The integration of intelligent systems in various industries has led to notable advancements in energy resource utilization. Power Line Communication (PLC) is widely used in the power industry for transmitting telemetry, speech, and protective tripping commands. While Wi-Fi has limitations in remote control and monitoring applications due to cost and power consumption, Wireless Sensor Networks (WSNs) face challenges like transmission errors and data losses. Developing a scalable WSN architecture is crucial, especially in the presence of excessive network coverage or non-line-of-sight situations. Challenges persist despite efforts to enhance WSN connectivity, and conflicts with wireless local area networks (WLANs) in the 2.4 GHz ISM band lead to issues like packet losses and interference. To address these issues, the proposal suggests integrating WSN with PLC technology to create a resilient utility network. The research introduces a Master-Slave system using frequency-shift keying (FSK) based PLC modules for effective management and supervision of the intelligent utility network, with scalability for diverse industrial intelligence applications.

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Section: Literature Reviewmentioning

confidence: 99%

Smart Edge Device Utilizing Power Line Communication for Energy Management and Control of Electrical Appliances

Varanasi,

Jonnalagadda,

Karri

2024

IEEE Access

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“…Though the specific hardware used in our instrumentation setup can be costly, low-cost alternatives with similar or better specifications have become available in recent years (e.g. [25][26][27][28][29][30][31][32] ).…”

Section: # Of Buildingsmentioning

confidence: 99%

A voltage and current measurement dataset for plug load appliance identification in households

et al. 2020

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This paper presents the Plug-Load Appliance Identification Dataset (PLAID), a labelled dataset containing records of the electrical voltage and current of domestic electrical appliances obtained at a high sampling frequency (30 kHz). The dataset contains 1876 records of individually-metered appliances from 17 different appliance types (e.g., refrigerators, microwave ovens, etc.) comprising 330 different makes and models, and collected at 65 different locations in Pittsburgh, Pennsylvania (USA). Additionally, PLAID contains 1314 records of the combined operation of 13 of these appliance types (i.e., measurements obtained when multiple appliances were active simultaneously). Identifying electrical appliances based on electrical measurements is of importance in demand-side management applications for the electrical power grid including automated load control, load scheduling and nonintrusive load monitoring. This paper provides a systematic description of the measurement setup and dataset so that it can be used to develop and benchmark new methods in these and other applications, and so that extensions to it can be developed and incorporated in a consistent manner. 110 130 max 2 0 RMSThe main contributions of this paper are that it:The complete PLAID dataset and all mentioned scripts are available in 5 . In the same repository, code written to capture the data can be found. The files are two scripts, namely 'collecting_data.vi' (written with LabVIEW) and 'collecting_data.m' (written in MATLAB).

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“…These buildings include large offices, warehouses, retails or shopping malls, and as also pointed out in [2], have fundamentally different characteristics than those of residential buildings. On top of this, the use of high frequency measures (such as current waveforms) has been enabled by the development of low cost meters [3] and can significantly change the classic power based NILM approaches.…”

Section: Introductionmentioning

confidence: 99%

A generative model for non-Intrusive load monitoring in commercial buildings

Henriet

Şimşekli

Fuentes³

et al. 2018

Energy and Buildings

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In the recent years, there has been an increasing academic and industrial interest for analyzing the electrical consumption of commercial buildings.Whilst having similarities with the Non Intrusive Load Monitoring (NILM) tasks for residential buildings, the nature of the signals that are collected from large commercial buildings introduces additional difficulties to the NILM research causing existing NILM approaches to fail. On the other hand, the amount of publicly available datasets collected from commercial buildings is very limited, which makes the NILM research even more challenging for this type of large buildings. In this study, we aim at addressing these issues.We first present an extensive statistical analysis of both commercial and residential measurements from public and private datasets and show important differences. Secondly, we develop an algorithm for generating synthetic current waveforms. We then demonstrate using real measurement and quantitative metrics that both our device model and our simulations are realistic and can be used to evaluate NILM algorithms. Finally, to encourage research on commercial buildings we release a synthesized dataset.

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Design and implementation of a low-cost arduino-based high-frequency AC waveform meter board for the raspberry pi

Cited by 5 publications

References 3 publications

Smart Edge Device Utilizing Power Line Communication for Energy Management and Control of Electrical Appliances

Smart Edge Device Utilizing Power Line Communication for Energy Management and Control of Electrical Appliances

A voltage and current measurement dataset for plug load appliance identification in households

A generative model for non-Intrusive load monitoring in commercial buildings

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