Electric Vehicles’ User Charging Behaviour Simulator for a Smart City

Bruno Canizes, João Soares, Angelo Costa, Tiago Pinto, Fernando Lezama, Paulo Novais and Zita Vale
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Bruno Canizes: GECAD—Knowledge Engineering and Decision Support Research Center—Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal
João Soares: GECAD—Knowledge Engineering and Decision Support Research Center—Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Angelo Costa: ALGORITMI Centre, University of Minho, 4710-057 Braga, Portugal
Tiago Pinto: GECAD—Knowledge Engineering and Decision Support Research Center—Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Fernando Lezama: GECAD—Knowledge Engineering and Decision Support Research Center—Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal
Paulo Novais: ALGORITMI Centre, University of Minho, 4710-057 Braga, Portugal
Zita Vale: Polytechnic of Porto (IPP), R. Dr. António Bernardino de Almeida, 431, 4200-072 Porto, Portugal

Energies, 2019, vol. 12, issue 8, 1-20

Abstract: The increase of variable renewable energy generation has brought several new challenges to power and energy systems. Solutions based on storage systems and consumption flexibility are being proposed to balance the variability from generation sources that depend directly on environmental conditions. The widespread use of electric vehicles is seen as a resource that includes both distributed storage capabilities and the potential for consumption (charging) flexibility. However, to take advantage of the full potential of electric vehicles’ flexibility, it is essential that proper incentives are provided and that the management is performed with the variation of generation. This paper presents a research study on the impact of the variation of the electricity prices on the behavior of electric vehicle’s users. This study compared the benefits when using the variable and fixed charging prices. The variable prices are determined based on the calculation of distribution locational marginal pricing, which are recalculated and adapted continuously accordingly to the users’ trips and behavior. A travel simulation tool was developed for simulating real environments taking into account the behavior of real users. Results show that variable-rate of electricity prices demonstrate to be more advantageous to the users, enabling them to reduce charging costs while contributing to the required flexibility for the system.

Keywords: electric charging behaviour; electric mobility; energy prices; EVs; travel simulator (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (20)

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