Ready To Roll: Southeastern Pennsylvania's Regional Electric Vehicle Action Plan

On-road internal combustion engine (ICE) vehicles are responsible for nearly one-third of energy use and one-quarter of greenhouse gas (GHG) emissions in southeastern Pennsylvania.1 Electric vehicles (EVs), including plug-in hybrid electric vehicles (PHEVs) and all-electric vehicles (AEVs), present an opportunity to serve a significant portion of the region's mobility needs while simultaneously reducing energy use, petroleum dependence, fueling costs, and GHG emissions. As a national leader in EV readiness, the region can serve as an example for other efforts around the country."Ready to Roll! Southeastern Pennsylvania's Regional EV Action Plan (Ready to Roll!)" is a comprehensive, regionally coordinated approach to introducing EVs and electric vehicle supply equipment (EVSE) into the five counties of southeastern Pennsylvania (Bucks, Chester, Delaware, Montgomery, and Philadelphia). This plan is the product of a partnership between the Delaware Valley Regional Planning Commission (DVRPC), the City of Philadelphia, PECO Energy Company (PECO; the region's electricity provider), and Greater Philadelphia Clean Cities (GPCC). Additionally, ICF International provided assistance to DVRPC with the preparation of this plan. The plan incorporates feedback from key regional stakeholders, national best practices, and research to assess the southeastern Pennsylvania EV market, identify current market barriers, and develop strategies to facilitate vehicle and infrastructure deployment

Integracija električnih vozila u energetske i transportne sustave

There is a strong tendency of development and application of different types of electric vehicles (EV). This can clearly be beneficial for transport systems in terms of making it more efficient, cleaner, and quieter, as well as for energy systems due to the grid load leveling and renewable energy sources exploitation opportunities. The latter can be achieved only through application of smart EV charging technologies that strongly rely on application of optimization methods. For the development of both EV architectures and controls and charging optimization methods, it is important to gain the knowledge about driving cycle features of a particular EV fleet. To this end, the paper presents an overview of (i) electric vehicle architectures, modeling, and control system optimization and design; (ii) experimental characterization of vehicle fleet behaviors and synthesis of representative driving cycles; and (iii) aggregate-level modeling and charging optimization for EV fleets, with emphasis on freight transport.U novije vrijeme postoji izražena težnja za razvojem i korištenjem različitih tipova električnih vozila. Ovo može biti korisno sa stanovišta transportnih sustava u smislu omogućavanja efikasnijeg, čišćeg, i tišeg transporta, kao i iz perspektive energetskih sustava zbog dodatnih potencijala za poravnanje opterećenja mreže i iskorištenje obnovljivih izvora energije. Potonje može biti ostvareno samo kroz korištenje tehnologija naprednog punjenja električnih vozila, koje se često temelje na primjeni optimizacijskih postupaka. Za razvoj prikladnih konfiguracija, upravljačkih sustava te metoda pametnog punjenja električnih vozila, potrebno je steći uvid u značajke voznih ciklusa razmatrane flote električnih vozila. Imajući u vidu navedeno, članak predstavlja pregled (i) konfiguracija i modeliranja električnih vozila, te optimiranja i sinteze njihova upravljačkog sustava; (ii) eksperimentalne karakterizacije ponašanja flote vozila i sinteze reprezentativnih voznih ciklusa; te (iii) modeliranja i optimiranja punjenja flote električnih vozila na agregatnom nivou, s naglaskom na teretni transport

Distributed Control of Charging for Electric Vehicle Fleets Under Dynamic Transformer Ratings

Due to their large power draws and increasing adoption rates, electric vehicles (EVs) will become a significant challenge for electric distribution grids. However, with proper charging control strategies, the challenge can be mitigated without the need for expensive grid reinforcements. This article presents and analyzes new distributed charging control methods to coordinate EV charging under nonlinear transformer temperature ratings. Specifically, we assess the tradeoffs between required data communications, computational efficiency, and optimality guarantees for different control strategies based on a convex relaxation of the underlying nonlinear transformer temperature dynamics. Classical distributed control methods, such as those based on dual decomposition and alternating direction method of multipliers (ADMM), are compared against the new augmented Lagrangian-based alternating direction inexact Newton (ALADIN) method and a novel low-information, look-ahead version of packetized energy management (PEM). These algorithms are implemented and analyzed for two case studies on residential and commercial EV fleets with fixed and variable populations. The latter motivates a novel EV hub charging model that captures arrivals and departures. Simulation results validate the new methods and provide insights into key tradeoffs

The Innovation Interface: Business model innovation for electric vehicle futures

There is huge potential to link electric vehicles, local energy systems, and personal mobility in the city. By doing so we can improve air quality, tackle climate change, and grow new business models. Business model innovation is needed because new technologies and engineering innovations are currently far ahead of the energy system’s ability to accommodate them. This report explores new business models that can work across the auto industry, transport infrastructure and energy systems

A Household-Oriented Approach to The Benefits of Vehicle-To-Grid-Capable Electric Vehicles

In this paper we introduce a novel approach to exploring the benefits associated with Vehicle-to-Grid technology on an individual household level. We design an artifact that enables the implementation of different management strategies to utilize synergies between residential photovoltaic electricity generation and the energy storage provided by electric vehicles. The main advantage of this approach is that it does not rely on strong assumptions regarding the market penetration or social acceptance of electric vehicles. In a proof-of-concept case study we show that even a very simple management strategy derived from a household utility function provides additional revenues to the household, while simultaneously decreasing (peak) load on the distribution grid

Triggering the development of electric mobility: a review of public policies

libre accès au texte intégral : http://www.springerlink.com/content/ghq570268853q546/fulltext.pdfInternational audienceContext The fundamental challenge of a massive deployment of electric mobility is the reduction of transportation's impact on climate. Hereby derived challenges specifically concern: (a) the organization of mobility together with the uptake of recharge infrastructure, (b) the interaction of the electric mobility system with the electricity net, hereby considering the energy storage function of batteries, (c) the technological progress and the industrial production of vehicles and various components. Overall, these stakes involve the community more than the individual vehicle user. Objective This paper analyses public policies and projects in favour of electric mobility based on private or shared vehicle usage. An international review of national policies and regional projects is given. The conditions for availability and attractiveness of an electric mobility system to potential users are discussed, notably so with respect to the deployment of the recharging infrastructure and its adequacy to existing land-use patterns. Conclusion Current policy approaches supporting the uptake of electric mobility are promising. For the time being, however, the complexity of the electromobility system impedes a valid conclusion on the effectiveness of measures put in place. Besides public policy intervention mainly also economic, technical and industrial factors will define the success of e-mobility. Upcoming years will allow first ex-post policy analyses