Towards statistical modeling and machine learning based energy usage forecasting in smart grid

2015 ◽  
Vol 15 (1) ◽  
pp. 6-16 ◽  
Author(s):  
Wei Yu ◽  
Dou An ◽  
David Griffith ◽  
Qingyu Yang ◽  
Guobin Xu
Keyword(s):  
Machine Learning ◽  
Smart Grid ◽  
Statistical Modeling ◽  
Energy Usage

Machine learning versus statistical modeling

2014 ◽  
Vol 56 (4) ◽  
pp. 588-593 ◽  
Author(s):  
Anne-Laure Boulesteix ◽  
Matthias Schmid
Keyword(s):  
Machine Learning ◽  
Statistical Modeling

Smart Metering for Applications

2014 ◽  
Vol 960-961 ◽  
pp. 823-827
Author(s):  
Ying Pan ◽  
Bo Jiang
Keyword(s):  
Smart Grid ◽  
Electrical Energy ◽  
Smart Meter ◽  
Smart Metering ◽  
Power Network ◽  
Energy Usage ◽  
Smart Meters ◽  
Additional Information ◽  
Energy Efficiency Improvement ◽  
Energy Meter

As an important part of Smart Grid, smart metering attracts more and more attention all over the world. It is the way for energy consumer to sense the benefit of smart grid directly. Smart meter is an advanced energy meter that measures consumption of electrical energy providing additional information compared to a conventional energy meter. This paper discusses various applications and technologies that can be integrated with a smart meter. Smart meters can be used not only from the supply side monitoring but also for the demand side management as well. It plays an important role to monitor the performance and the energy usage of the grid loadings and power quality. In addition, This paper gives a comprehensive view on the benefit of smart metering in power network such as energy efficiency improvement.

An Autonomous Residential Smart Distribution Board: A Panacea for Demand Side Energy Management for Non-Smart Grid Networks

2018 ◽  
Vol 19 (3) ◽  
Author(s):  
Oladayo O. Olakanmi ◽  
Oluyemi Adetoyi ◽  
Oluwafemi Fajemisin
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Demand Response ◽  
Dynamic Pricing ◽  
Performance Comparison ◽  
Usage Pattern ◽  
Energy Usage ◽  
Grid Networks ◽  
A Priority ◽  
Priority Model

Abstract Despite the benefits of demand response in energy management, the non-existence of its key concepts; dynamic pricing and smart grid, in some countries makes its impracticable in these countries, therefore making energy management unattainable for their consumers. This paper proposed a Smart Distribution Board (SDB) using a priority model for energy management in non-smart grid network. An historical consumption signatures of user’s loads were used to develop a priority model for load units of the SDB. Performance comparison was carried out between the SDB and a conventional Distribution Board which has no level of intelligence. Results obtained indicated that the SDB correctly emulated the energy usage pattern of users, thereby ensuring load preference is maximally satisfied autonomously within a limited budgeted energy and period.

Towards Graph Machine Learning for Smart Grid Knowledge Graphs in Industrial Scenarios

2021 ◽  
Author(s):  
Guido Walter Di Donato ◽  
Andrea Damiani ◽  
Alberto Parravicini ◽  
Enea Bionda ◽  
Francesca Soldan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Smart Grid ◽  
Knowledge Graphs
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