Cost-optimal Fleet Management Strategies for Solar-electric Autonomous Mobility-on-Demand Systems

This paper studies mobility systems that incorporate a substantial solar energy component, generated not only on the ground, but also through solar roofs installed on vehicles, directly covering a portion of their energy consumption. In particular, we focus on Solar-electric Autonomous Mobility-on-Demand systems, whereby solar-electric autonomous vehicles provide on-demand mobility, and optimize their operation in terms of serving passenger requests, charging and vehicle-to-grid (V2G) operations. We model this fleet management problem via directed acyclic graphs and parse it as a mixed-integer linear program that can be solved using off-the-shelf solvers. We showcase our framework in a case study of Gold Coast, Australia, analyzing the fleet's optimal operation while accounting for electricity price fluctuations resulting from a significant integration of solar power in the total energy mix. We demonstrate that using a solar-electric fleet can reduce the total cost of operation of the fleet by 10-15% compared to an electric-only counterpart. Finally, we show that for V2G operations using vehicles with a larger battery size can significantly lower the operational costs of the fleet, overcompensating its higher energy consumption by trading larger volumes of energy and even accruing profits

Bi-directional coordination of plug-in electric vehicles with economic model predictive control

© 2017 by the authors. Licensee MDPI, Basel, Switzerland. The emergence of plug-in electric vehicles (PEVs) is unveiling new opportunities to de-carbonise the vehicle parcs and promote sustainability in different parts of the globe. As battery technologies and PEV efficiency continue to improve, the use of electric cars as distributed energy resources is fast becoming a reality. While the distribution network operators (DNOs) strive to ensure grid balancing and reliability, the PEV owners primarily aim at maximising their economic benefits. However, given that the PEV batteries have limited capacities and the distribution network is constrained, smart techniques are required to coordinate the charging/discharging of the PEVs. Using the economic model predictive control (EMPC) technique, this paper proposes a decentralised optimisation algorithm for PEVs during the grid-To-vehicle (G2V) and vehicle-To-grid (V2G) operations. To capture the operational dynamics of the batteries, it considers the state-of-charge (SoC) at a given time as a discrete state space and investigates PEVs performance in V2G and G2V operations. In particular, this study exploits the variability in the energy tariff across different periods of the day to schedule V2G/G2V cycles using real data from the university's PEV infrastructure. The results show that by charging/discharging the vehicles during optimal time partitions, prosumers can take advantage of the price elasticity of supply to achieve net savings of about 63%

Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives

The goal of the study presented in this article is to provide a general overview of the various aspects related to electric vehicles (EVs), along with all associated emerging challenges and perspectives. In this context, the basic types of EVs and the corresponding charging technologies are analyzed. Since EVs are expected to be a key component of future smart electrical grids (SEG), connection to the grid issues, along with advanced charging techniques (i.e., wireless power transfer), are analyzed as well. To this end, the main features, the requirements of vehicle to grid (V2G) communications, as well as future developments and scenarios of electrification, are also presented and analyzed. Moreover, integration issues with currently deployed fifth generation (5G) mobile wireless networks are also outlined, in order to ensure optimum transmission and reception quality in V2G communications and improved user experience. This integration is also expanded in autonomous vehicles (AVs) technology (self-driving objects), since optimized information processing from various diverse sources is required in order to ensure advanced traffic management aspects. Document type: Articl

Impact of electric vehicles on power quality in a smart grid context

The large dependency of the imported fossil fuels and the soaring oil prices, makes essential the look for alternatives to the traditional people transportation system. The natural bet is the electric mobility, namely Electric Vehicles (EV), and Plug-in Hybrid Electric Vehicles (PHEV). This way, in this paper is analyzed the potential impacts of the battery charging systems on the grid power quality, in a Smart Grid context. It is considered the current consumed, according to a typical electric consumption profile, and the voltage degradation for a large number of houses. Two different types of EV batteries chargers were considered: a traditional charger; and a smart charger with sinusoidal current consumption and unitary power factor. It presents simulation results of the integration of EVs and PHEVs in terms of power quality, and experimental results of a smart charger which was specially developed for EV charging and that allows mitigation of the power quality degradation.Fundação para a Ciência e a Tecnologia (FCT

A bidirectional power charging control strategy for Plug-in Hybrid Electric Vehicles

© 2019 by the authors. Plug-in Hybrid Electric Vehicles (PHEVs) have the potential of providing frequency regulation due to the adjustment of power charging. Based on the stochastic nature of the daily mileage and the arrival and departure time of Electric Vehicles (EVs), a precise bidirectional charging control strategy of plug-in hybrid electric vehicles by considering the State of Charge (SoC) of the batteries and simultaneous voltage and frequency regulation is presented in this paper. The proposed strategy can control the batteries charge which are connected to the grid, and simultaneously regulate the voltage and frequency of the power grid during the charging time based on the available power when different events occur over a 24-h period. The simulation results prove the validity of the proposed control strategy in coordinating plug-in hybrid electric vehicles aggregations and its significant contribution to the peak reduction, as well as power quality improvement. The case study in this paper consists of detailed models of Distributed Energy Resources (DERs), diesel generator and wind farm, a generic aggregation of EVs with various charging profiles, and different loads. The test system is simulated and analyzed in MATLAB/SIMULINK software

Batteries charging systems for electric and plug-in hybrid electric vehicles

Many countries have a large dependence on imported fossil fuels whose prices increase almost every day. Knowing that much of this consumption is for transportation systems, it becomes essential to seek for alternatives. The natural bet is the electric mobility, namely through Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs). However, the wide spread utilization of these vehicles has consequences on the electrical power grid, mainly in terms of load management and electric power quality, which are associated to the batteries charging systems. In this scenario, this chapter assesses the electric mobility integration in Smart Grid context, focusing different approaches to the operation of EVs and PHEVs charging processes and the specifications of the chargers, as well as different topologies of charging systems and their features, modes of operation, typical waveforms, and impact in the electrical power grid in terms of power quality. It is also presented a laboratory prototype of a bidirectional EV charger and shown some experimental results. This prototype was developed to charge the batteries aiming to preserve their lifespan, and to contribute to mitigate the degradation of the power quality. The experimental results show the operation of this prototype during the batteries charging process (G2V – Grid-to-Vehicle operation), and during the delivering of stored energy back to the electrical power grid (V2G – Vehicle-to-Grid operation).FEDER Funds - Operational Program for Competitiveness Factors – COMPETEFundação para a Ciência e a Tecnologia (FCT) - FCOMP-01-0124-FEDER-022674, MITPT/ EDAM-SMS/0030/200