Modeling of Mobility On-Demand Fleet Operations Based on Dynamic Electricity Pricing

被引:2
|
作者
Fehn, Fabian [1 ]
Noack, Florian [1 ]
Busch, Fritz [1 ]
机构
[1] Tech Univ Munich, Chair Traff Engn & Control, Munich, Germany
关键词
electric mobility; vehicle-to-grid; dynamic vehicle fleet simulation; dynamic electricity pricing; charging optimization; VEHICLES;
D O I
10.1109/mtits.2019.8883370
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The 21st century is characterized not only by a growing need for mobility, but above all by an increasing variety of mobility forms. Individualization, connectivity, urbanization and post-fossil drive technologies will determine the mobility of tomorrow. Technical innovations and changing human needs are becoming the driving force behind novel forms of mobility and innovative business models. However, not only the mobility world is changing rapidly. Particularly renewable energy sources, like sun and wind are directly connected to planning uncertainty due to their dependence on weather. This leads to frequency fluctuations in the power grid. These fluctuations in turn are the reason for dynamic electricity prices to which especially large consumers can adapt in order to save money. This paper investigates to what extent an operating electric mobility on-demand fleet can adjust to changing electricity prices and whether this adaptation affects the service performance of the overall system. For this purpose, a model is built up, which considers traffic influences in the form of dynamic travel times as well as the passenger and battery management of the vehicles. The model suggests that a vehicle fleet with an adapted charging strategy to dynamic electricity prices can save money at all investigated fleet sizes. First results indicate that the service performance of the mobility on-demand fleet is not substantially affected. In addition, considerable cost savings can be realized by applying the dynamic charging strategy. The analysis of idle times of the vehicle fleet revealed further potential for optimization, which could potentially be used for the provision of ancillary services.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] Dynamic Pricing Mechanism Design for Electric Mobility-on-Demand Systems
    Ni, Liang
    Sun, Bo
    Wang, Su
    Tsang, Danny H. K.
    IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (08) : 11361 - 11375
  • [32] A dynamic simulation approach in modeling on-demand irrigation water consumption
    Lin, Mei-Chun (madgebse@gmail.com), 1600, Taiwan Agricultural Engineers Society (60):
  • [33] On-demand ride-hailing platforms under green mobility: Pricing strategies and government regulation
    Xu, Yu
    Ling, Liuyi
    Wu, Jie
    Xu, Shengshuo
    TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2024, 189
  • [34] THE IMPACT OF CONSUMER PREFERENCE DISTRIBUTIONS ON DYNAMIC ELECTRICITY PRICING FOR RESIDENTIAL DEMAND RESPONSE
    Dunbar, Samuel
    Ferguson, Scott
    PROCEEDINGS OF THE ASME INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, 2019, VOL 2A, 2020,
  • [35] Simulation-based design and analysis of on-demand mobility services
    Markov, Iliya
    Guglielmetti, Rafael
    Laumanns, Marco
    Fernandez-Antolin, Anna
    de Souza, Ravin
    TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE, 2021, 149 : 170 - 205
  • [36] Time-based Electricity Pricing for Demand Response Implementation in Monopolized Electricity Market
    Nazar, N. S. M.
    Abdullah, M. P.
    Hassan, M. Y.
    Hussin, F.
    2012 IEEE STUDENT CONFERENCE ON RESEARCH AND DEVELOPMENT (SCORED), 2012,
  • [37] Agent-based simulation testbed for on-demand mobility services
    Certicky, Michal
    Jakob, Michal
    Pibil, Radek
    Moler, Zbynek
    5TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT-2014), THE 4TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2014), 2014, 32 : 808 - 815
  • [38] Behavior-Based Pricing in On-Demand Service Platforms With Network Effects
    Chen, Mingyang
    Gong, Yeming
    IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2023, 71 : 4160 - 4174
  • [39] Modeling of dynamic pricing by market demand in multiple QoS networks
    Kim, SK
    Choi, MK
    OPERATIONS AND MANAGEMENT IN IP-BASED NETWORKS, PROCEEDINGS, 2005, 3751 : 49 - 57
  • [40] Modeling and prioritizing dynamic demand response programs in the electricity markets
    Yu, Dongmin
    Xu, Xinyi
    Dong, Mingyu
    Nojavan, Sayyad
    Jermsittiparsert, Kittisak
    Abdollahi, Amir
    Aalami, Habib Allah
    Pashaei-Didani, Hamed
    SUSTAINABLE CITIES AND SOCIETY, 2020, 53