Aggregate Peak EV Charging Demand: The Influence of Segmented Network Tariffs

被引:0
|
作者
Panda, Nanda Kishor [1 ]
Li, Na [1 ]
Tindemans, Simon H. [1 ]
机构
[1] Delft Univ Technol, Dept Elect Sustainable Energy, Delft, Netherlands
来源
2024 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO, ITEC 2024 | 2024年
关键词
Aggregate; Distribution system; Electric vehicle; Flexibility; Segmented tariff;
D O I
10.1109/ITEC60657.2024.10599041
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Aggregate peak Electric Vehicle (EV) charging demand is a matter of growing concern for network operators as it severely limits the network's capacity, preventing its reliable operation. Various tariff schemes have been proposed to limit peak demand by incentivizing flexible asset users to shift their demand from peak periods. However, fewer studies quantify the effect of these tariff schemes on the aggregate level. In this paper, we compare the effect of a multi-level segmented network tariff with and without dynamic energy prices for individual EV users on the aggregate peak demand. Results based on real charging transactions from over 1200 public charging points in the Netherlands show that the segmented network tariff with flat energy prices results in more diverse load profiles with increasing aggregation, as compared to cost-optimized dispatch based on only dynamic day-ahead energy prices. When paired with dynamic energy prices, the segmented tariff still outperforms only dynamic energy price-based tariffs in reducing peaks. Results show that a balance between power thresholds and price per threshold is crucial in designing a suitable tariff, taking into account the needs of the power network. We also provide valuable insights to network operators by calculating the diversity factor for various peak demands per charging point.
引用
收藏
页数:6
相关论文
共 50 条
  • [1] Impact of Dynamic Tariffs for Smart EV Charging on LV Distribution Network Operation
    Verbist, Fiore
    Panda, Nanda Kishor
    Vergara, Pedro P.
    Palensky, Peter
    2023 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, PESGM, 2023,
  • [2] Rural EV charging: The effects of charging behaviour and electricity tariffs
    McKinney, Thomas R.
    Ballantyne, Erica E. F.
    Stone, David A.
    ENERGY REPORTS, 2023, 9 : 2321 - 2334
  • [3] Impact of EV Charging Strategies on Peak Demand Reduction and Load Factor Improvement
    Dogan, Ahmet
    Kuzlu, Murat
    Pipattanasomporn, Manisa
    Rahman, Saifur
    Yalcinoz, Tankut
    2015 9TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO), 2015, : 374 - 378
  • [4] Optimized Scheduling of EV Charging in Solar Parking Lots for Local Peak Reduction under EV Demand Uncertainty
    Ghotge, Rishabh
    Snow, Yitzhak
    Farahani, Samira
    Lukszo, Zofia
    van Wijk, Ad
    ENERGIES, 2020, 13 (05)
  • [5] Peak-Minimizing Online EV Charging
    Zhao, Shizhen
    Lin, Xiaojun
    Chen, Minghua
    2013 51ST ANNUAL ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING (ALLERTON), 2013, : 46 - 53
  • [6] Efficient Determination of Distribution Tariffs for the Prevention of Congestion from EV Charging
    O'Connell, Niamh
    Wu, Qiuwei
    Ostergaard, Jacob
    2012 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING, 2012,
  • [7] Impact of Higher Power of EV Quick Chargers on Peak Load and Analysis of Smoothing Effect of Charging Demand
    Takagi M.
    Ikeya T.
    IEEJ Transactions on Power and Energy, 2024, 144 (02) : 182 - 191
  • [8] Pricing EV charging service with demand charge
    Lee, Zachary J.
    Pang, John Z. F.
    Low, Steven H.
    ELECTRIC POWER SYSTEMS RESEARCH, 2020, 189
  • [9] Managing Peak Water Demand Behavior through Dynamic Tariffs
    Onuki, Yutaro
    Otaki, Yurina
    JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT, 2025, 151 (02)
  • [10] Cascading failures in EV charging network
    Ma, Sining
    Li, Jie
    FRONTIERS IN PHYSICS, 2022, 10