A Qualitative Study on the United States Internet of Energy: A Step Towards Computational Sustainability

Nazmus Sakib, Eklas Hossain, Sheikh Iqbal Ahamed

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

The burgeoning growth of Big Data not only matures and improves the data management efficiency and useful information extraction techniques, but also motivates the computational science researchers to come up with a new method or solution that can be repurposed for problems across the domain. Computational Sustainability joins this movement for a transferrable computational technique for sustainable development and a better future. Internet-of-energy (IoE) - leveraging IoT to smart grids associated with advanced analytics - is one of the prominent efforts in this regard. This paper presents a qualitative analysis on the elements of the energy and power management ecosystem in the United States. This qualitative study includes the Grid Overview of the United States; Weather and Climate and its impact on the entire energy generation and consumption dynamics; Peak Load Forecasting and its techniques and burgeoning challenges; Variable Renewable Energy, its reliability challenges and how we can take advantage of this variability; Commodity Prices and its criticality; Energy Disaggregation and its impact on consumption-awareness; and Generation Expansion and Decision Analysis. Besides, IoE integration, associated trade-offs, challenges, research opportunities and transferable computational techniques are addressed in this communication. Furthermore, schematics and quantitative analysis are presented in support of this study.

Original languageAmerican English
Article number9058653
Pages (from-to)69003-69037
Number of pages35
JournalIEEE Access
Volume8
DOIs
StatePublished - 7 Apr 2020
Externally publishedYes

Keywords

  • big data
  • Computational sustainability
  • Internet of Energy
  • Internet of Things
  • smart grid
  • transferable computational techniques

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