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.

Highlights

  • The need to reduce greenhouse gas emissions is ever increasing, and several nations have agreed on ambitious targets in the Paris Agreement Treaty [1]

  • The variable prices are determined based on the calculation of distribution locational marginal pricing (DLMP) using distribution network operation and reconfiguration optimization model, which enables achieving prices that are continuously recalculated and adaptable to the ongoing changes in the power network and reflect the situation and needs in each different location of the network

  • Considering a 2500 electric vehicles (EVs) scenario and using the fixed charging price, it is possible to see in Figure 6 the correspondent charging sessions percentages for each user scenario preference

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Summary

Introduction

The need to reduce greenhouse gas emissions is ever increasing, and several nations have agreed on ambitious targets in the Paris Agreement Treaty [1]. Providing incentives to EV users in a way that behavior and charging patterns are changed and adapted to the variation of electricity prices is essential to ensure the EV’s flexibility balances the variation of renewable energy sources. It is in this scope that this paper brings its main contributions, by presenting a study on the impact of electricity prices variation on EV users’.

Electric Mobility
Charging Behaviour
Distribution Locational Marginal Pricing
Simulation Tools
Proposed Simulation Tool
Parameters
Simulator Algorithm
Data Generation
Trip Simulation
Charging Stations
Charging Decisions
Energy Prices
DLMP Optimisation Model Description
Case Studies
Population Scenario with 2500 EVs
Population Scenario with 5000 EVs
Conclusions
Full Text
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