Reprint

Smart Energy and Intelligent Transportation Systems

Edited by
August 2022
110 pages
  • ISBN978-3-0365-4453-3 (Hardback)
  • ISBN978-3-0365-4454-0 (PDF)

This book is a reprint of the Special Issue Smart Energy and Intelligent Transportation Systems that was published in

Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Physical Sciences
Summary

With the Internet of Things and various information and communication technologies, a city can manage its assets in a smarter way, constituting the urban development vision of a smart city. This facilitates a more efficient use of physical infrastructure and encourages citizen participation. Smart energy and smart mobility are among the key aspects of the smart city, in which the electric vehicle (EV) is believed to take a key role. EVs are powered by various energy sources or the electricity grid. With proper scheduling, a large fleet of EVs can be charged from charging stations and parking infrastructures. Although the battery capacity of a single EV is small, an aggregation of EVs can perform as a significant power source or load, constituting a vehicle-to-grid (V2G) system. Besides acquiring energy from the grid, in V2G, EVs can also support the grid by providing various demand response and auxiliary services. Thanks to this, we can reduce our reliance on fossil fuels and utilize the renewable energy more effectively. This Special Issue “Smart Energy and Intelligent Transportation Systems” addresses existing knowledge gaps and advances smart energy and mobility. It consists of five peer-reviewed papers that cover a range of subjects and applications related to smart energy and transportation.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
electric vehicles; PROSA; PROMETHEE for Sustainability Assessment; MCDA; Multi-Criteria Decision Analysis; stochastic analysis; Monte Carlo; uncertainty; cargo bicycles; loading hub; facility location problem; computer simulations; Python programing; electric vehicle charging; vehicle-to-grid; genetic algorithms; particle swarm optimization; demand-side management; discrete choice theory; revenue management; road–railway accidents; classification trees; road safety; transport means; accidents victims; condition monitoring; vibroacoustic diagnostics; gearbox; power transmission systems; neural networks; deep learning; n/a