Exploring Advanced Metering Infrastructure Deployments for Commercial and Industrial Sites

2012 ◽  
Author(s):  
Allison Littman ◽  
Geoff Lyon ◽  
Amip Shah ◽  
John Vogler
Keyword(s):  
Energy Use ◽  
Advanced Metering Infrastructure ◽  
Smart Meters ◽  
Industrial Sites ◽  
Industrial Sectors ◽  
Trade Offs ◽  
Mixed Use ◽  
Building Energy Use ◽  
Advanced Metering ◽  
A Site

Smart meters have become increasingly common as an approach to benchmark and assess building energy use. In this paper, we explore what type of metering infrastructure may be required to derive value from the application of smart meters in the commercial and industrial sectors. As an example, we find that sole reliance upon a site-level smart meter—which has been the focus of most existing deployment models—provides sufficient data to extract summary statistics about how the energy use of a given site may compare to a typical ‘average’ site, but such installations fail to provide adequate detail about where the energy use is occurring or why any discrepancies might be occurring. To resolve these issues, we install a multi-tier advanced metering infrastructure (AMI) at a mixed use (industrial and commercial) campus. We use this AMI deployment to gain insight at different levels of the consumption hierarchy—from sites to buildings, panels, sub-panels, and end loads. The paper concludes by discussing the trade-offs associated with such augmented metering at each level within the hierarchy, with a view towards providing guidelines for AMI deployment at other industrial and commercial campuses.

scholarly journals Communication Performance Assessment for Advanced Metering Infrastructure

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 88 ◽  
Author(s):  
Jen-Hao Teng ◽  
Chia-Wei Chao ◽  
Bin-Han Liu ◽  
Wei-Hao Huang ◽  
Jih-Ching Chiu
Keyword(s):  
Smart Grids ◽  
Small Scale ◽  
Smart Meter ◽  
Advanced Metering Infrastructure ◽  
Smart Meters ◽  
Communication Performance ◽  
Reading Success ◽  
Efficient Communication ◽  
Advanced Metering ◽  
Communication Paths

Advanced Metering Infrastructure (AMI), the foundation of smart grids, can be used to provide numerous intelligent power applications and services based on the data acquired from AMI. Effective and efficient communication performance between widely-spread smart meters and Data Concentrator Units (DCUs) is one of the most important issues for the successful deployment and operation of AMI and needs to be further investigated. This paper proposes an effective Communication Performance Index (CPI) to assess and supervise the communication performance of each smart meter. Some communication quality measurements that can be easily acquired from a smart meter such as reading success rate and response time are used to design the proposed CPI. Fuzzy logic is adopted to combine these measurements to calculate the proposed CPI. The CPIs for communication paths, DCUs and whole AMI can then be derived from meter CPIs. Simulation and experimental results for small-scale AMIs demonstrate the validity of the proposed CPI. Through the calculated CPIs, the communication performance and stability for AMI can be effectively assessed and supervised.

scholarly journals Effect of mobility of smart meters on performance of advanced metering infrastructure

2017 ◽  
Vol 13 (3) ◽  
pp. 1495-1510
Author(s):  
Shunsuke Matsuzawa ◽  
◽  
Satoru Harada ◽  
Kazuya Monden ◽  
Yukihiro Takatani ◽  
...  
Keyword(s):  
Advanced Metering Infrastructure ◽  
Smart Meters ◽  
Advanced Metering

scholarly journals Global scenarios of urban density and its impacts on building energy use through 2050

2017 ◽  
Vol 114 (34) ◽  
pp. 8945-8950 ◽  
Author(s):  
Burak Güneralp ◽  
Yuyu Zhou ◽  
Diana Ürge-Vorsatz ◽  
Mukesh Gupta ◽  
Sha Yu ◽  
...  
Keyword(s):  
Urban Form ◽  
Urban Areas ◽  
Energy Use ◽  
Well Being ◽  
Building Energy ◽  
Sub Saharan Africa ◽  
Urban Density ◽  
Heating And Cooling ◽  
Trade Offs ◽  
Building Energy Use

Although the scale of impending urbanization is well-acknowledged, we have a limited understanding of how urban forms will change and what their impact will be on building energy use. Using both top-down and bottom-up approaches and scenarios, we examine building energy use for heating and cooling. Globally, the energy use for heating and cooling by the middle of the century will be between 45 and 59 exajoules per year (corresponding to an increase of 7–40% since 2010). Most of this variability is due to the uncertainty in future urban densities of rapidly growing cities in Asia and particularly China. Dense urban development leads to less urban energy use overall. Waiting to retrofit the existing built environment until markets are ready in about 5 years to widely deploy the most advanced renovation technologies leads to more savings in building energy use. Potential for savings in energy use is greatest in China when coupled with efficiency gains. Advanced efficiency makes the least difference compared with the business-as-usual scenario in South Asia and Sub-Saharan Africa but significantly contributes to energy savings in North America and Europe. Systemic efforts that focus on both urban form, of which urban density is an indicator, and energy-efficient technologies, but that also account for potential co-benefits and trade-offs with human well-being can contribute to both local and global sustainability. Particularly in growing cities in the developing world, such efforts can improve the well-being of billions of urban residents and contribute to mitigating climate change by reducing energy use in urban areas.

Load Segmentation for Convergence of Distribution Automation and Advanced Metering Infrastructure Systems

2014 ◽  
Vol 15 (6) ◽  
pp. 607-619 ◽  
Author(s):  
Balakrishna Pamulaparthy ◽  
Swarup KS ◽  
Rajagopal Kommu
Keyword(s):  
Low Voltage ◽  
Distribution Automation ◽  
Advanced Metering Infrastructure ◽  
Distribution Grid ◽  
Smart Meters ◽  
Time Intervals ◽  
Power Restoration ◽  
Advanced Metering ◽  
Short Time

Abstract Distribution automation (DA) applications are limited to feeder level today and have zero visibility outside of the substation feeder and reaching down to the low-voltage distribution network level. This has become a major obstacle in realizing many automated functions and enhancing existing DA capabilities. Advanced metering infrastructure (AMI) systems are being widely deployed by utilities across the world creating system-wide communications access to every monitoring and service point, which collects data from smart meters and sensors in short time intervals, in response to utility needs. DA and AMI systems convergence provides unique opportunities and capabilities for distribution grid modernization with the DA system acting as a controller and AMI system acting as feedback to DA system, for which DA applications have to understand and use the AMI data selectively and effectively. In this paper, we propose a load segmentation method that helps the DA system to accurately understand and use the AMI data for various automation applications with a suitable case study on power restoration.

scholarly journals Data falsification attacks in advanced metering infrastructure

2021 ◽  
Vol 10 (1) ◽  
pp. 412-418
Author(s):  
Hasventhran Baskaran ◽  
Abbas M. Al-Ghaili ◽  
Zul- Azri Ibrahim ◽  
Fiza Abdul Rahim ◽  
Saravanan Muthaiyah ◽  
...  
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Smart Grids ◽  
Supply And Demand ◽  
Effective Control ◽  
Smart Meter ◽  
Advanced Metering Infrastructure ◽  
End User ◽  
Smart Meters ◽  
Advanced Metering

Smart grids are the cutting-edge electric power systems that make use of the latest digital communication technologies to supply end-user electricity, but with more effective control and can completely fill end user supply and demand. Advanced Metering Infrastructure (AMI), the backbone of smart grids, can be used to provide a range of power applications and services based on AMI data. The increased deployment of smart meters and AMI have attracted attackers to exploit smart grid vulnerabilities and try to take advantage of the AMI and smart meter’s weakness. One of the possible major attacks in the AMI environment is False Data Injection Attack (FDIA). FDIA will try to manipulate the user’s electric consumption by falsified the data supplied by the smart meter value in a smart grid system using additive and deductive attack methods to cause loss to both customers and utility providers. This paper will explore two possible attacks, the additive and deductive data falsification attack and illustrate the taxonomy of attack behaviors that results in additive and deductive attacks. This paper contributes to real smart meter datasets in order to come up with a financial impact to both energy provider and end-user.

Smart Meters and Advanced Metering Infrastructure

Smart Grids ◽  
2017 ◽  
pp. 445-462
Author(s):  
Aaron F. Snyder ◽  
David Kranzler ◽  
Robby Simpson ◽  
Stuart Borlase ◽  
Mary Carpine-Bell ◽  
...  
Keyword(s):  
Advanced Metering Infrastructure ◽  
Smart Meters ◽  
Advanced Metering
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