Smart meters for power grid: Challenges, issues, advantages and status

Depuru, Soma Shekara Sreenadh Reddy; Wang, Lingfeng; Devabhaktuni, Vijay

doi:10.1016/j.rser.2011.02.039

Cited by 495 publications

(255 citation statements)

References 8 publications

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“…Apart from the energy efficiency, probably the terms most often used are Smart Metering (SM) and Smart Grid (SG) as synonyms for the solution of (all) problems of (mainly electrical) energy industry [1], [2].…”

Section: Metering Status Quomentioning

confidence: 99%

From Smart Metering to Smart Grid

Kukuca

Chrapčiak

2016

Measurement Science Review

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The paper deals with evaluation of measurements in electrical distribution systems aimed at better use of data provided by Smart Metering systems. The influence of individual components of apparent power on the power loss is calculated and results of measurements under real conditions are presented. The significance of difference between the traditional and the complex evaluation of the electricity consumption efficiency by means of different definitions of the power factor is illustrated.

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Section: Metering Status Quomentioning

confidence: 99%

From Smart Metering to Smart Grid

Kukuca

Chrapčiak

2016

Measurement Science Review

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“…Possible additional services for the customers include a comparison of energy tariffs and recommendation of the most suitable ones, remote control of household appliances for increased consumer convenience, prediction of the future energy consumption and the associated costs as well as the detection of inefficient devices to improve household energy efficiency [25,26]. Besides, the consumption data can be used to demonstrate the effects of a modified user behaviour and analyse the resulting opportunities for the customer.…”

Section: Customer Servicesmentioning

confidence: 99%

“…These systems are suitable for distributed generation concepts and offer customers an option of increasing energy efficiency while simultaneously reducing costs. Companies with access to residential energy consumption data could promote and offer custom-tailored home generation and storage solutions [26,30].…”

Section: Promotion Of Alternative Energy Sourcesmentioning

confidence: 99%

Application-oriented modelling of domestic energy demand

Gruber

Jahromizadeh

Prodanović

et al. 2014

International Journal of Electrical Power & Energy Systems

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link AbstractDetailed residential energy consumption data can be used to offer advanced services and provide new business opportunities to all participants in the energy supply chain, including utilities, distributors and customers. The increasing interest in the residential consumption data is behind the roll-out of smart meters in large areas and led to intensified research efforts in new data acquisition technologies for the energy sector. This paper introduces a novel model for generation of residential energy consumption profiles based on the energy demand contribution of each household appliance and calculated by using a probabilistic approach. The model takes into consideration a wide range of household appliances and its modular structure provides a high degree of flexibility. Residential consumption data generated by the proposed model are suitable for development of new services and applications such as residential real-time pricing schemes or tools for energy demand prediction. To demonstrate the main features of the model, an individual household consumption was created and the effects of a possible change in the user behaviour and the appliance configuration presented. In order to show the flexibility offered in creation of the aggregated demand, the detailed simulation results of an energy demand management algorithm applied to an aggregated user group are used.

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“…Several project-proposals for AMI have been made using different communication technologies [3] [4] [5]. However, there is a lack of network requirements estimation in order to get an overview of what to expect from a network planned to be deployed for AMI.…”

Section: Contributionmentioning

confidence: 99%

Bandwidth analysis of smart meter network infrastructure

Balachandran

Olsen

Pedersen

2014

16th International Conference on Advanced Communication Technology

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Abstract-Advanced Metering Infrastructure (AMI) is a network infrastructure in Smart Grid, which links electricity customers to utility company. Compared to a network where different amount of data is send, AMI network sends small amount of data at different time intervals. This network enables smart services by making it possible for the utility company to get an overview of their customers power consumption and also control devices in their costumers household e.g. heat pumps. The problem investigated in this paper is what bandwidth requirements can be expected when implementing such network to utilize smart meters and which existing broadband network technologies can facilitate this smart meter service. Initially, scenarios for smart meter infrastructure are identified. The paper defines abstraction models which cover the AMI scenarios. A general overview of the bandwidth requirements are analysed. For this analysis assumptions and limitations are defined. The results show the bandwidth provided by GPRS technology is sufficient. However, from a delay point of view, GPRS has its limits, therefore, xDSL or 3G can be used for faster transfer but will rarely utilize the available bandwidth from these technologies. The aggregator which is responsible to collect all the data from the different smart meters can become a bottleneck as the aggregated amount of data is high, thus the bandwidth for the data concentrator has to be high. These results are interesting to look at, as they show there are different bandwidth requirements from a smart meter and aggregator point of view and that, the aggregator is a vital element in the network and it has to be studied further.

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Smart meters for power grid: Challenges, issues, advantages and status

Cited by 495 publications

References 8 publications

From Smart Metering to Smart Grid

From Smart Metering to Smart Grid

Application-oriented modelling of domestic energy demand

Bandwidth analysis of smart meter network infrastructure

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