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Internet of Things and Information Processing in Smart Energy Applications

Feature Topic


There are four major challenges for the current electricity grid — increasing electricity demand, ageing grid infrastructure, ever-increasing penetration of renewables, and significant uptake of electric vehicles and energy storage with behind-the-meter applications for residential and commercial buildings. To address these challenges, there must be strong and low-cost communications infrastructures that can support rapid and secure information exchange as well as consistent and efficient design of communication protocols and architectures to enable automation and effective use of smart energy resources. Internet of Things (IoT) could accelerate establishment of such infrastructures. With IoT technologies, a lot more devices could be controlled and managed through the Internet, and data pertaining to the grid, commercial buildings, and residential premises can be readily collected and utilized. To derive valuable information from the data, further information and data processing becomes essential. There are, however, a number of challenges to be addressed.

This Feature Topic (FT) aims to disseminate general ideas extracted from cutting-edge research results spanning multiple disciplines. Potential authors will be able to share various viewpoints and the latest findings from research and ongoing projects relevant to smart energy applications from the perspectives of IoT and advanced information processing and communications technologies. Topics of interest include, but are not limited to:

  • Machine-to-Machine (M2M) or Vehicle-to-Grid (V2G)/home communications in smart grid
  • Smart metering including Behind-The-Meter (BTM) applications and autonomous demand response
  • Advanced Metering Infrastructure (AMI) and information processing in smart grid
  • Intelligent Energy Management System (EMS) for utility grid and commercial/residential buildings
  • IoT-enabled smart energy applications, security mechanisms, and architectures
  • Big data analysis and mining for IoT-based smart grid, city, and home


Wei-Yu Chiu
Yuan Ze University, Taiwan

Hongjian Sun
Durham University, UK

Shunqing Zhang
Intel Corporation, China

John Thompson
Edinburgh University, UK

Kiyoshi Nakayama
NEC Laboratories America, USA