Improving Electric Vehicle Charging Coordination Through Area Pricing

Flath, Christoph M.; Ilg, Jens P.; Gottwalt, Sebastian; Schmeck, Hartmut; Weinhardt, Christof

doi:10.2139/ssrn.2197327

Cited by 11 publications

(8 citation statements)

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“…This analysis also suggests that research on EVs in the smart grid context is yet in the early stage. Although many theoretical concepts and ideas have been proposed (e.g., dynamic pricing [38,39] and vehicle-to-grid [6,40]), both EVs and smart grid are yet in the early stage of introduction and lessons have to be learned to better understand how EVs can realize the full smart grid potential. Energy resource management-related research has increased steadily along with the research in DR topics since its importance to the new paradigm of power systems (see Section 3.2).…”

Section: Complexitymentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

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Section: Complexitymentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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“…Hence, they are a prime candidate for exploring the effects of load flexibility (Blumsack and Fernandez 2012). Following previous research (e.g., Sioshansi 2012;Flath et al 2014), we model an EV fleet by combining empirical driving profiles and appropriate EV technical specifications with an individual charging decision model. To this end, we extracted 900 profiles from the German Mobility Panel.…”

Section: Flexible Loadmentioning

confidence: 99%

Price-based load coordination revisited: augmenting open-loop coordination approaches

Flath

Gottwalt

2016

Bus Res

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The activation of flexible loads through demand side management offers opportunities for more efficient power systems operations. Price-based incentive are a straight-forward form for decentral coordination of these flexible loads. However, their applicability has recently been seen more pessimistic as they may induce new load peaks due to herding effects. We revisit these results by characterizing desynchronized posted pricing approaches. Illustrating highly flexible load by means of electric vehicle charging, we show that these desynchronized rate can mitigate the occurrence of extreme load spikes, improve the utilization of renewable generation and in summary create significant system cost savings. Our results show that simple open-loop pricing can almost match the efficiency of closed-loop adaptive pricing in settings with limited system flexibility. We find that the more renewable generation and flexible load are present in the system, the better more complex pricing schemes fare compared to simple ones. This insight may guide regulators and utilities in establishing more effective pricing schemes in retail electricity markets.

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“…Using centralized charging management keeps the edge devices (EV side) simple, and favors more sophisticated centralized optimizations from the GA side based on the aggregated global information. Last but not least, the price [18]- [21] differences between CSs concerning business model, and battery exchange service [22] concerning a super fast service provision could be easily integrated into our proposed CS-selection decision making.…”

Section: Introductionmentioning

confidence: 99%

An EV Charging Management System Concerning Drivers’ Trip Duration and Mobility Uncertainty

Cao

Wang

Kaiwartya

et al. 2018

IEEE Trans. Syst. Man Cybern, Syst.

142

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Abstract-With continually increased attention on Electric Vehicles (EVs) due to environment impact, public Charging Stations (CSs) for EVs will become common. However, due to the limited electricity of battery, EV drivers may experience discomfort for long charging waiting time during their journeys. This often happens when a large number of (on-the-move) EVs are planning to charge at the same CS, but it has been heavily overloaded. With this concern, in an EV charging management system, we focus on CS-selection decision making and propose a scheme to manage EVs' charging plans, to minimize drivers' trip duration through intermediate charging at CSs. The proposed scheme jointly considers EVs' anticipated charging reservations (including arrival time, expected charging time) and parking duration at CSs. Furthermore, by tackling mobility uncertainty that EVs may not reach their planned CSs on time (due to traffic jams on the road), a periodical reservation updating mechanism is designed to adjust their charging plans. Results under the Helsinki city scenario with realistic EV and CS characteristics show the advantage of our proposal, in terms of minimized drivers' trip duration, as well as charging performance at the EV and CS sides.

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Improving Electric Vehicle Charging Coordination Through Area Pricing

Cited by 11 publications

References 0 publications

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Price-based load coordination revisited: augmenting open-loop coordination approaches

An EV Charging Management System Concerning Drivers’ Trip Duration and Mobility Uncertainty

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