Review on AMI technology for Smart Meter

Nimbargi, Saket R; Mhaisne, Sagar; Nangare, Samruddhi; Sinha, Manisha

doi:10.1109/icaecct.2016.7942549

Cited by 21 publications

(5 citation statements)

References 7 publications

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“…[17] Finding energy consumption patterns using smart meter data through machine learning [18] Discusses the evolution of energy meters from the past [19] A case study explaining the impact of battery storage on energy consumption using smart meter data [20] Discussion of smart meter hardware, communications, and security in terms of its contribution to the smart grid [21] Explanation of different types of non-technical losses that exist in the grid and how smart meters can help in removing them [22] Focuses on compression techniques of big data available from smart meters [23] Explains different types of smart meter communication technologies to realize smart metering connectivity [24] Use case discussion as to how residents of UK are responding to smart energy via digital comparison tools [25] Discussed three reliability prediction methods to analyze smart meter data to predict life of the meter [26] Fosters the understanding and adaption of modern deep learning methods to solve the challenges regarding energy supply [27] Discussion of challenges and opportunities of smart meters in smart grids and homes [28] LoRaWAN technology explored in detail in terms of capacity limits [29] Comprehensive review on the existing and future communication infrastructures [30] Features of IoT protocols reviewed comprehensively for smart meters and smart grids in general [31] Investigates emerging tech such as cognitive radio networks in 5G for reliable communication in smart grids [32] Review of security issues and their solutions regarding cyber-physical systems of AMI [33] Review of AMI technology for smart meters discussing different varieties of control, facilities, and features [34] Discussion on various elements of smart metering, current state of the technologies, AMI, and meter data flow with respect to smart grid [35] Thorough review of smart meter data classification of electricity consumption [36] Data analytics review paper analyzed from customer-centric perspective by discussing their technological foundations and impact Reference Comments [37] Review of how lives of people are affected by the use of smart meters, highlighting 13 socio-psychological variables [38] Extensive review of evolution of smart metering [39] Review and explanation of hardware-oriented security scheme implementation on smart meters [40] Survey highlights the key security issues of AMIs and focuses on...…”

Section: Referencementioning

confidence: 99%

Smart Energy Meters for Smart Grids, an Internet of Things Perspective

et al. 2023

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Smart energy has evolved over the years to include multiple domains integrated across multiple technology themes, such as electricity, smart grid, and logistics, linked through communication technology and processed in the cloud in a holistic way to deliver on global challenges. Advances in sensing, communication, and computation technologies have been made that enable better smart system implementations. In smart energy systems, sensing technologies have spanned multiple domains with newer techniques that are more accurate, have greater dynamic ranges, and are more reliable. Similarly, communication techniques have now evolved into very high-speed, flexible, and dynamic systems. Computation techniques have seen a quantum leap with greater integration, powerful computing engines, and versatile software stacks that are easily available and modifiable. Finally, the system integration has also seen advances in the form of management, automation, and analytics paradigms. Consequently, smart energy systems have witnessed a revolutionary transformation. The complexity has correspondingly grown exponentially. With regard to smart meters, the measurement component has to scale up to meet the demands of the evolved energy eco-system by relying on the advancements offered. The internet of things (IoT) is a key technology enabler in this scenario, and the smart meter is a key component. In recent years, metering technology has evolved in both complexity and functionality. Therefore, it must use the advances offered by IoT to deliver a new role. The internet of things (IoT) is a key technology enabler in this scenario and the smart meter a key component. In recent years, metering technology has evolved in both complexity and functionality. To deliver on its new role, it must use the advances offered by IoT. In this review, we analyze the smart meter as a combination of sensing, computing, and communication nodes for flexible and complex design paradigms. The components are, in turn, reviewed vis-à-vis the advances offered by IoT. The resultant gaps are reported for future design challenges in the conclusion. The identified gaps are the lack of usage of the full spectrum of the available technology and the lack of an inter-disciplinary approach to smart meter design.

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Section: Referencementioning

confidence: 99%

Smart Energy Meters for Smart Grids, an Internet of Things Perspective

et al. 2023

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“…Smart meter is the device enable AMIT which is installed at consumer side for collecting the data daily [24], monthly thorough communication network. The silent features of AMIT are list below.…”

Section: A Smart Meter Structurementioning

confidence: 99%

Withdrawn

2020

IJRTE

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In present scenario power quality issues and reliability are the challenges for the service providers and end users. The advancements in recent technologies like Internet of Things (IoT) provide good solutions for these challenges and strengthening the smart grid. Smart Meter Technology (SMT) and Advanced metering Infrastructure technology (AMIT) enables two way communication between service providers and end users there by exposing the power transactions between them in effective way. SMT and AMIT are discussed throughout this literature This paper discusses the role and feasibility of SMT in improving power quality and maintaining reliability in IoT enabled smart grid. At first we discuss in detail about SMT, wireless communication, routing algorithms enabling AMIT and then literature focusing on power quality and reliability in IoT enabling smart grid.

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“…erefore, smart grid achieves system efficiency, reliability, and robustness of electrical generation and distribution system. e advanced metering infrastructure (AMI) [1][2][3][4][5] is the crucial application of the smart grid which manages information between utility and clients, e.g., smart meters, through a local access point (data concentrator unit: DCU) using the two-way communication method. Once the information can be exchanged between smart meters and the DCU in both directions and in real time, the smart grid is recognized as the self-monitoring and self-healing system since simple troubleshooting and repairing can be performed automatically without technician intervention.…”

Section: Introductionmentioning

confidence: 99%

Empowered Hybrid Parent Selection for Improving Network Lifetime, PDR, and Latency in Smart Grid

Srisomboon

Dindam

Lee

2021

Mathematical Problems in Engineering

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To support the constraints of smart meters—low power and memory—of AMI network, RPL is considered as the most suitable routing protocol to be implemented in practice. Network lifetime, PDR, and latency are the critical issues to be focused on and addressed. Generally, single parent selection scheme cannot satisfy all expected performance requirements of RPL based on AMI network due to tradeoff between workload balancing and transmission performance, PDR and latency. Moreover, the single parent also suffers from the package size and transmission range. Then, multiparent solution is proposed to overcome these demerits using multipath transmission strategy. Although the existing multiparent solutions, MELT and MAHP, overcome the issue of transmission performance, they present low network lifetime since multiparent solution consumes high energy in data transmission. In this paper, we propose an “empowered hybrid parent selection (EHPS)” that exploits the merits of multiparent solution and the single parent with cognitive radio technology in a hybridizing scheme. To split the data packet efficiently under multipath transmission strategy, a fuzzy AHP (FAHP) is adopted; therefore, EHPS balances the workload effectively and maximizes the network lifetime over long transmission range and large data size. Moreover, by exploiting cognitive radio, EHPS is flexible to the transmission range and data size since it achieves the highest transmission performance, highest PDR, and lowest latency among others, while maintaining high network lifetime.

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Review on AMI technology for Smart Meter

Cited by 21 publications

References 7 publications

Smart Energy Meters for Smart Grids, an Internet of Things Perspective

Smart Energy Meters for Smart Grids, an Internet of Things Perspective

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Empowered Hybrid Parent Selection for Improving Network Lifetime, PDR, and Latency in Smart Grid

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