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Smart Charging Strategies for Electric Bus Fleets with Aggregator Support: A Robust Bi-level Optimisation Approach

Name: Smart Charging Strategies for Electric Bus Fleets with Aggregator Support: A Robust Bi-level Optimisation Approach
Creator: Manzolli, Jônatas
Keywords: Electric Vehicle Aggregator, Constrained Optimization, Energy Engineering, Electric Vehicles

Research datakeyboard_double_arrow_right Dataset 01 Jan 2024Embargo end date: 05 Aug 2024Publisher:Mendeley Data

Authors: Manzolli, Jônatas;

doi: 10.17632/6smy53nwbx.1

Smart Charging Strategies for Electric Bus Fleets with Aggregator Support: A Robust Bi-level Optimisation Approach

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Abstract

This dataset is part of the thesis "Smart Charging Strategies for Electric Bus Fleets with Aggregator Support: A Robust Bi-level Optimisation Approach", submitted in accordance with the requirements for the degree of Doctor of Philosophy in Sustainable Energy Systems, supervised by Professor Carlos Henggeler Antunes and Professor João Pedro Fernandes Trovão, and presented to the Department of Electrical and Computer Engineering of the Faculty of Sciences and Technology of the University of Coimbra.

Keywords

Electric Vehicle Aggregator, Constrained Optimization, Energy Engineering, Electric Vehicles

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	0
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Average
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Average
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Average

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