04967nam a22006735i 4500 978-3-031-61917-5 DE-He213 20251030113121.0 cr nn 008mamaa 241002s2024 sz | s |||| 0|eng d 9783031619175 978-3-031-61917-5 10.1007/978-3-031-61917-5 doi TL1-4050 TR bicssc TRA000000 bisacsh TR thema Ferro, Giulio. author. (orcid)0000-0002-0641-6846 https://orcid.org/0000-0002-0641-6846 aut http://id.loc.gov/vocabulary/relators/aut 85442 Optimization of Electric-Vehicle Charging [electronic resource] : Scheduling and Planning Problems / by Giulio Ferro, Riccardo Minciardi, Luca Parodi, Michela Robba. 1st ed. 2024. Cham : Springer International Publishing : Imprint: Springer, 2024. XVII, 178 p. 81 illus., 74 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Advances in Industrial Control, 2193-1577 1. Introduction -- 2. Modelling, Simulation, and Optimization for the Optimal Planning and Management of Electric Vehicles: State of the Art and Challenges -- 3. Optimal Charging in Smart Grids: Discrete Time Optimization Model for Aperiodic Scheduling -- 4. Optimal Charging in Smart Grids: A Discrete Event Approach for Scheduling in Single Socket Charging Stations -- 5. Optimal Charging in Smart Grids: A Discrete Event Approach for Scheduling in Multi Socket Charging Stations -- 6. Optimal Charging in Smart Grids: A Discrete Event Approach for Periodic Scheduling -- 7. Planning for Electric Vehicles: Deterministic and Stochastic User Equilibrium Approaches for Joint Traffic Assignment and Energy Demand Assignment -- 8. Planning for Electric Vehicles: A User Equilibrium Approaches for Joint Traffic Assignment, Energy Demand Assignment and Sizing of Charging Stations -- 9. Planning for Electric Vehicles: Optimal Placement of Charging Stations in an Electrical Distribution Grid -- 10. Conclusions. This book provides models and methods for the optimal management of electrical vehicles through an interdisciplinary approach that brings together knowledge from the sectors of transportation, manufacturing and smart grids. Optimization of Electric-Vehicle Charging explores several optimization models for the scheduling of electric vehicles in a smart grid. Both discrete-time and discrete-event approaches are considered to minimize tardiness, charging and production costs, on the basis of information like release time, due date, deadline, energy request, and availability of energy generated from renewable sources. Transportation demand is assessed, as well as user-equilibrium-based approaches, for the location of charging stations and for the assignment of users to multiple charging stations. Employing illustrations, tables and examples to elucidate the ideas presented, this book will be of value to researchers and practitioners in the fields of electrical engineering and transportation, as well as to graduate and PhD students. Vehicles. 66337 Electric power distribution. 66068 Control engineering. Mathematical optimization. 65522 Operations research. 57943 Management science. 57941 Transportation engineering. 65686 Traffic engineering. 65687 Vehicle Engineering. 66340 Energy Grids and Networks. 66069 Control and Systems Theory. 65868 Discrete Optimization. 73079 Operations Research, Management Science. 65527 Transportation Technology and Traffic Engineering. 65691 Minciardi, Riccardo. author. aut http://id.loc.gov/vocabulary/relators/aut 85443 Parodi, Luca. author. (orcid)0000-0002-9288-0273 https://orcid.org/0000-0002-9288-0273 aut http://id.loc.gov/vocabulary/relators/aut 85444 Robba, Michela. author. (orcid)0000-0002-0032-9493 https://orcid.org/0000-0002-0032-9493 aut http://id.loc.gov/vocabulary/relators/aut 85445 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031619168 Printed edition: 9783031619182 Printed edition: 9783031619199 Advances in Industrial Control, 2193-1577 14359 https://doi.org/10.1007/978-3-031-61917-5 ZDB-2-ENG ZDB-2-SXE 63922 63922