Modeling &amp; designing of smart energy meter for smart grid applications

Jaiswal, Devendra M; Thakre, Mohan P.

doi:10.1016/j.gltp.2022.03.017

Cited by 15 publications

(9 citation statements)

References 11 publications

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“…According to the Institute of Standards and Technology (NIST) [47], the concept of smart grid or energy grid refers to the set of six aspects related to energy: bulk generation, transmission, distribution, customers, service providers, operations, and markets. This topic is highly relevant and for this reason it is widely discussed in the bibliography [2,[48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63]. 8 Monitor energy consumption in Smart Cities [15,43,64]; such as, for example, public lighting [65][66][67].…”

Section: Related Workmentioning

confidence: 99%

Vampire: A smart energy meter for synchronous monitoring in a distributed computer system

Díaz,

Prieto,

Escobar

et al. 2024

Journal of Parallel and Distributed Computing

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Section: Related Workmentioning

confidence: 99%

Vampire: A smart energy meter for synchronous monitoring in a distributed computer system

Díaz,

Prieto,

Escobar

et al. 2024

Journal of Parallel and Distributed Computing

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“…To effectively control electricity demand, Avancini et al [12] installed smart meters to provide measurement, communication, control, display, and synchronization functions, and established a smart energy network that can be effectively managed. To effectively reduce energy demand and carbon emissions, Jaiswal and Thakre [13] adopted the control and management of smart meters in the SG based on detailed electricity consumption and price information to plan the energy use. Yang et al [14] established an energy-saving and reliable SG by installing smart meters in the power system, analyzing the actual power consumption data, and introducing probabilistic load forecasting to better control the uncertainty and volatility of future demand.…”

Section: Distribution Side Management Through Sgsmentioning

confidence: 99%

A Survey on Recent Applications of Artificial Intelligence and Optimization for Smart Grids in Smart Manufacturing

Hsu,

Jiang,

Lin

2023

Energies

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To enable highly automated manufacturing and net-zero carbon emissions, manufacturers have invested heavily in smart manufacturing. Sustainable and smart manufacturing involves improving the efficiency and environmental sustainability of various manufacturing operations such as resource allocation, data collecting and monitoring, and process control. Recently, a lot of artificial intelligence and optimization applications based on smart grid systems have improved the energy usage efficiency in various manufacturing operations. Therefore, this survey collects recent works on applications of artificial intelligence and optimization for smart grids in smart manufacturing and analyzes their features, requirements, and challenges. In addition, potential trends and further challenges for the integration of smart grids with renewable energies for smart manufacturing, applications of 5G and B5G (beyond 5G) technologies in the SG system, and next-generation smart manufacturing systems are discussed to provide references for further research.

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“…When the average degradation rate of the product is constant, the performance degradation process can be modeled by Equation (1). However, affected by the environment, the measuring performance degradation of meter presents the characteristics of nonlinearity and randomness, resulting in the degradation rate being not constant.…”

Section: Linearization Of the Nonlinear Modelmentioning

confidence: 99%

“…As the main measuring equipment for electricity trade settlement, the reliability of the meter is very important for maintaining the power grid. In the service process, the meter may fail due to insufficient expectations for its reliability when enterprise designed the meter, resulting in economic losses [1]. Therefore, the accurate and rapid estimation of the reliability life of the meter can provide an important data basis to maintain and replace the meter and prevent major accidents.…”

Section: Introductionmentioning

confidence: 99%

Research on the Life Prediction Method of Meters Based on a Nonlinear Wiener Process

et al. 2022

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Due to the high reliability of present meters, it is difficult to obtain the failure time of meters through accelerated life tests. Based on the failure data of the accelerated life test, this paper studies the mathematical model based on the Wiener process and establishes the degradation model of the instrument by the maximum likelihood to estimate the parameters of the Wiener model. With full consideration of the possible nonlinear effects in modeling, the time scale transformation method is used to study and obtain the reliability life prediction model of smart meters based on nonlinear data. Finally, the reliability life prediction model of meters is verified and evaluated through the example data of the accelerated life test of smart meters. Compared with the conventional method, this method has less error in calculating the reliability, greatly saves test time, and has a higher accuracy than estimating the lifetime model using the Wiener process directly.

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Modeling & designing of smart energy meter for smart grid applications

Cited by 15 publications

References 11 publications

Vampire: A smart energy meter for synchronous monitoring in a distributed computer system

Vampire: A smart energy meter for synchronous monitoring in a distributed computer system

A Survey on Recent Applications of Artificial Intelligence and Optimization for Smart Grids in Smart Manufacturing

Research on the Life Prediction Method of Meters Based on a Nonlinear Wiener Process

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