Bandwidth analysis of smart meter network infrastructure

Balachandran, Kartheepan; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup

doi:10.1109/icact.2014.6779095

Cited by 15 publications

(9 citation statements)

References 7 publications

(6 reference statements)

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“…This paper assumes that one DCU is connected to several smart meters for data transmission. The bandwidth requirement for this situation is evaluated [ 40 ]. Specifically, when the individual smart meters are directly connected to the DCU, the sampling and transfer intervals are assumed as 1 second and 4 minutes, respectively.…”

Section: Experiments and Resultsmentioning

confidence: 99%

Frequency Selective Auto-Encoder for Smart Meter Data Compression

Lee

Yoon

Hwang

2021

Sensors

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With the development of the internet of things (IoT), the power grid has become intelligent using massive IoT sensors, such as smart meters. Generally, installed smart meters can collect large amounts of data to improve grid visibility and situational awareness. However, the limited storage and communication capacities can restrain their infrastructure in the IoT environment. To alleviate these problems, efficient and various compression techniques are required. Deep learning-based compression techniques such as auto-encoders (AEs) have recently been deployed for this purpose. However, the compression performance of the existing models can be limited when the spectral properties of high-frequency sampled power data are widely varying over time. This paper proposes an AE compression model, based on a frequency selection method, which improves the reconstruction quality while maintaining the compression ratio (CR). For efficient data compression, the proposed method selectively applies customized compression models, depending on the spectral properties of the corresponding time windows. The framework of the proposed method involves two primary steps: (i) division of the power data into a series of time windows with specified spectral properties (high-frequency, medium-frequency, and low-frequency dominance) and (ii) separate training and selective application of the AE models, which prepares them for the power data compression that best suits the characteristics of each frequency. In simulations on the Dutch residential energy dataset, the frequency-selective AE model shows significantly higher reconstruction performance than the existing model with the same CR. In addition, the proposed model reduces the computational complexity involved in the analysis of the learning process.

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Section: Experiments and Resultsmentioning

confidence: 99%

Frequency Selective Auto-Encoder for Smart Meter Data Compression

Lee

Yoon

Hwang

2021

Sensors

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“…For current AMI deployments, mobile systems have been supporting low duty cycle applications such as bi-weekly meter reading, data pulling from meters, and occasional system maintenance. For such low data rate applications, GPRS is sufficient to ensure appropriate quality of service (QoS) [2][4] [5].…”

Section: B Motivationmentioning

confidence: 99%

Introducing the Latest 3GPP Specifications and their Potential for Future AMI Applications

Koumadi¹,

Park²,

Myoung³

2016

KEPCO Journal on Electric Power and Energy

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Despite the exponential throughput improvement in mobile communications systems, their ability to satisfy requirements of stateof-the-art and future applications of advanced metering infrastructure (AMI) is still under investigation. Challenges are mainly due to the inadequacy of third generation partnership project (3GPP) networks to support large amounts of devices simultaneously, while the number of AMI end-devices and the frequency of their data transmission increase with new AMI-based applications. In this introductory survey, innovative and future AMI applications and their communication requirements are first reviewed. Then, we identify challenges of 3GPP long term evolution (LTE) in enabling future AMI applications. More importantly, the latest improvements to LTE-A standard release 12 and 13 are reviewed and analyzed with regards to their potential to improve the quality of LTE-enabled AMI. It is found that 3GPP enhancements on machine type communications (MTC) standards will significantly enhance AMI communications. Beyond MTC specifications, non-MTC-specific enhancements such as carrier aggregation and multi-connectivity for user equipment will also contribute greatly to improving reliability and availability of AMI devices. The paper's focus is towards improved backhaul support for innovative and future AMI applications, beyond traditional automatic meter reading.

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“…In this regard, a set of critical features were identified and chosen to qualify wireless standard suitability [1,[10][11][12]31,40,86,87]. Table 5 clearly shows that the different services of a smart home have substantial differences in communication requirements.…”

Section: Wireless Network Suitability To Functional Area Requirementsmentioning

confidence: 99%

Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources

et al. 2015

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Abstract:The paper discusses Home Area Networks (HAN) communication technologies for smart home and domestic application integration. The work is initiated by identifying the application areas that can benefit from this integration. A broad and inclusive home communication interface is analysed utilizing as a key piece a Gateway based on machine-to-machine (M2M) communications that interacts with the surrounding environment. Then, the main wireless networks are thoroughly assessed, and later, their suitability to the requirements of HAN considering the application area is analysed. Finally, a qualitative analysis is portrayed.

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Bandwidth analysis of smart meter network infrastructure

Cited by 15 publications

References 7 publications

Frequency Selective Auto-Encoder for Smart Meter Data Compression

Frequency Selective Auto-Encoder for Smart Meter Data Compression

Introducing the Latest 3GPP Specifications and their Potential for Future AMI Applications

Smart Home Communication Technologies and Applications: Wireless Protocol Assessment for Home Area Network Resources

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