A common approach to intelligent energy and mobility services in a smart city environment

Abstract

Due to the fact that electric vehicles have not broadly entered the vehicle market there are many attempts to convince producers to integrate technologies that utilise embedded batteries for purposes different from driving. The vehicle-to-grid technology, for instance, literally turns electric vehicles into a mobile battery, enabling new areas of applications (e.g., to provide regulatory energy, to do grid-load balancing, or to buffer surpluses of energy) and business perspectives. Utilising a vehicle's battery, however is not without a price-in this case: the driver's mobility. Given this dependency, it is interesting that most available works consider the application of electric vehicles for energy and grid-related problems in isolation, that is, detached from mobility-related issues. The distributed artificial intelligence laboratory, or DAI-Lab, is a thirdparty funded research lab at Technische Universität Berlin and integrates the chair for agent technologies in business applications and telecommunication. The DAI-Lab has engaged in a large number of both, past and upcoming projects concerned with two aspects of managing electric vehicles, namely: energy and mobility. This article aims to summarise experiences that were collected during the last years and to present developed solutions which consider energy and mobility-related problems jointly.

Last-mile travel and bicycle sharing system in small/medium sized cities: user’s preferences investigation using hybrid choice model

“…A variety of mobility-related solutions is proposed to make cities smart, sustainable, congestion free and environment friendly. For example; electric mobility (Lützenberger et al 2015), Carpooling (Knapen et al 2014), efficient public transport scheduling (Avila-Torres et al 2017), vehicle routing solutions (Wang et al 2018), bicycling and bike sharing programs (Tang et al 2011). The benefits of cycling at both individual and societal level are significant and well known.…”

Data-driven charging strategies for grid-beneficial, customer-oriented and battery-preserving electric mobility

“…This mechanism also enables communication into the vehicle. Currently ten EVs provide 370 signals of interest, which we record with a 10-Hz sampling rate 4 .…”

“…In the following, we briefly present the single perspectives and respective interactions. To satisfy their individual needs, vehicle users expect their EVs to be just as reliable and convenient to use, as known from combustion engine cars [3,4]. However, limited range and longer charging times of EVs complicate individual mobility, manifesting e.g.…”

Viability of electric vehicles in combined day and night delivery: a total cost of ownership example in Germany

“…They conclude that the benefits of EVs -such as reduced noise and dependency on imported energy, as well as economic development opportunities -are significant and outweigh the effort of overcoming the barriers to installing green loading zones. Lu ¨tzenberger et al (2014) andLu ¨ tzenberger et al (2015) derive a combined model of intelligent energy and mobility services, by aggregating results of smart grid and electric mobility projects.…”

“…The objection of neighbours to potentially higher noise emissions at night is problematic (Balm et al, 2014;Cavar et al, 2011;Russo and Comi, 2010;Suksri et al, 2012). Noise might be reduced by implementing a certified silent delivery chain (Dizian, 2012) which includes more silent EVs (Lu ¨tzenberger et al, 2015;Wang et al, 2013). Neighbours and customers benefit from enhanced road safety; since traffic of heavy delivery vehicles and secondrow parking is reduced, passengers can cross the streets more safely (Cavar et al, 2011;Silas et al, 2012).…”