Distributed Machine Learning on Smart-Gateway Network toward Real-Time Smart-Grid Energy Management with Behavior Cognition

2018 ◽  
Vol 23 (5) ◽  
pp. 1-26 ◽  
Author(s):  
Hantao Huang ◽  
Hang Xu ◽  
Yuehua Cai ◽  
Rai Suleman Khalid ◽  
Hao Yu
Keyword(s):  
Machine Learning ◽  
Smart Grid ◽  
Real Time ◽  
Energy Management ◽  
Smart Gateway ◽  
Distributed Machine Learning

scholarly journals Machine Learning Based Energy Management Model for Smart Grid and Renewable Energy Districts

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 185059-185078
Author(s):  
Waqar Ahmed ◽  
Hammad Ansari ◽  
Bilal Khan ◽  
Zahid Ullah ◽  
Sahibzada Muhammad Ali ◽  
...  
Keyword(s):  
Machine Learning ◽  
Renewable Energy ◽  
Smart Grid ◽  
Energy Management ◽  
Management Model

Robust Real-Time Distributed Optimal Control Based Energy Management in a Smart Grid

2017 ◽  
Vol 8 (4) ◽  
pp. 1568-1579 ◽  
Author(s):  
Yinliang Xu ◽  
Zaiyue Yang ◽  
Wei Gu ◽  
Ming Li ◽  
Zicong Deng
Keyword(s):  
Optimal Control ◽  
Smart Grid ◽  
Real Time ◽  
Energy Management ◽  
Distributed Optimal Control

scholarly journals Intelligent Energy Management of Electrical Power Systems

2020 ◽  
Vol 10 (8) ◽  
pp. 2951 ◽  
Author(s):  
Manuela Sechilariu
Keyword(s):  
Smart Grid ◽  
Power Systems ◽  
Real Time ◽  
Energy Management ◽  
Distribution System ◽  
Power Flow ◽  
Low Voltage ◽  
Electrical Power ◽  
Building Blocks ◽  
Energy System

Smart grid implementation is facilitated by multi-source energy systems development, i.e., microgrids, which are considered the key smart grid building blocks. Whether they are alternative current (AC) or direct current (DC), high voltage or low voltage, high power or small power, integrated into the distribution system or the transmission network, multi-source systems always require an intelligent energy management that is integrated into the power system. A comprehensive intelligent energy system aims at providing overall energy efficiency with regard to the following: increased power generation flexibility, increased renewable generation systems, improved energy consumption, reduced CO2 emission, improved stability, and minimized energy cost. This Special Issue presents recent key theoretical and practical developments that concern the models, technologies, and flexible solutions to facilitate the following optimal energy and power flow strategies: the techno-economic model for optimal sources dispatching (mono and multi-objective energy optimization), real-time optimal scheduling, and real time optimization with model predictive control.

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