A language and a pattern system for temporal property specification: advanced metering infrastructure case study

2020 ◽  
Vol 19 (6) ◽  
pp. 695-710
Author(s):  
Tina Tavizi ◽  
Mehdi Shajari
Author(s):  
Hyeong Jin Choi ◽  
Sisam Park ◽  
Wonsuk Ko ◽  
Essam A. Al Ammar

2014 ◽  
Vol 15 (6) ◽  
pp. 607-619 ◽  
Author(s):  
Balakrishna Pamulaparthy ◽  
Swarup KS ◽  
Rajagopal Kommu

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.


Author(s):  
Wonsuk Ko ◽  
Hyeong Jin Choi ◽  
Sisam Park ◽  
Essam A. Al Ammar

2020 ◽  
Vol 12 (20) ◽  
pp. 8704
Author(s):  
Do-Hyeon Ryu ◽  
Ryu-Hee Kim ◽  
Seung-Hyun Choi ◽  
Kwang-Jae Kim ◽  
Young Myoung Ko ◽  
...  

Real-time collection of household electricity consumption data has been facilitated by an advanced metering infrastructure. In recent studies, collected data have been processed to provide information on household appliance usage. The noise caused by electrical appliances from neighboring households constitutes a major issue, which is related to discomfort and even mental diseases. The assessment of noise discomfort using electricity consumption data has not been dealt with in the literature up to this day. In this study, a method that utilizes electricity consumption data for the assessment of noise discomfort levels caused by electrical appliances between neighboring households is proposed. This method is based on the differences in the usage time of electrical appliances in a collective residential building. The proposed method includes the following four steps: data collection and preprocessing, residential units clustering, noise discomfort modeling, and evaluation of noise discomfort. This method is demonstrated through a case study of a campus apartment building. Variations in the noise discomfort assessment model and measures for alleviating noise discomfort are also discussed. The proposed method can guide the application of electricity consumption data to the assessment and alleviation of noise discomfort from home appliances at an apartment building.


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