Special Issue "Advancements in Renewable Energy Systems with AI, Big Data, BlockChain, IoT, and Machine Learning Applications"

Submission Deadline: 31 December 2020 (closed)
Guest Editors
Dr. M. Premkumar, GMR Institute of Technology, Rajam, Andhra Pradesh, India
Dr. S. Umashankar, Prince Sulton University, Saudi Arabia
Dr. T. Sudhakar Babu, Universiti Tenaga Nasional (UNITEN), Malaysia

Summary

The exponential growth of industrialization and economic development increases the demand to energy. The problems such as threat to human health and the environment, shortage of the fossil fuels, variable price, and emissions, which cause climate change and global warming, and this situation is the main driving force behind the use of renewable energy sources (RESs). In fact, RESs can be defined as clean sources of energy that minimizes environmental impacts, produces minimum or zero secondary wastes, and is sustainable based on the energetic, economic, and social needs. RESs include, among others, wind, hydropower, solar, geothermal, marine energies, and biomass. RES is in a constant state of innovation in 2019, with new advances in technology announced constantly. In the past year alone, there have been milestones in conversion efficiency, energy storage, Nano grid/Microgrid/Smart grid, Artificial Intelligence (AI), Energy Block-chain, IoT etc. The renewable energy research initiative targets to leverage Research and Engineering capabilities to facilitate and enable the achievement of Sustainable Development Goal. A series of new developments in RES technology also promise to contribute to the industry’s success. The primary objective of this special session is to encourage translational research utilizing available lab-scale know-hows to consolidate research outcomes to advance current technologies in the related field to deliver potential solutions to solar sector industrial and societal applications. From this special session, the most important developments and advances in RES were identified.


Keywords
Renewable energy systems; AI; ML; IoT; BigData; Power; Energy

Published Papers