Leveraging the flexibility of electric vehicle parking lots in distribution networks with high renewable penetration

被引:7
|
作者
Karimi-Arpanahi, Sahand [1 ]
Jooshaki, Mohammad [2 ]
Pourmousavi, S. Ali [1 ]
Lehtonen, Matti [3 ]
机构
[1] Univ Adelaide, Sch Elect & Elect Engn, Adelaide, SA 5005, Australia
[2] Circular Econ Solut Unit, Geologian Tutkimuskeskus GTK, FI-02151 Espoo, Finland
[3] Aalto Univ, Dept Elect Engn & Automation, FI-02150 Espoo, Finland
关键词
Bi-level programming; Distribution network operation; Electric vehicle parking lot; High renewable energy; Power system flexibility; MODEL;
D O I
10.1016/j.ijepes.2022.108366
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
The ongoing rapid increase in the integration of variable and uncertain renewable energy sources calls for enhancing the ways of providing flexibility to power grids. To this end, we propose an optimal approach for utilizing electric vehicle parking lots to provide flexibility at the distribution level. Accordingly, we present a day-ahead scheduling model for distribution system operators, where they can offer discounts on the network tariff to electric vehicle parking lot operators. This way, they will be encouraged to exploit the potential flexibility of electric vehicle batteries to assist in alleviating the steep ramps of system net-load. To determine the optimal discounts, the distribution system operator minimizes the network operating costs considering the network operational constraints, while the electric vehicle parking lot operators try to maximize their profits. Due to the contradictory objectives and decision hierarchy, the problem is an instance of Stackelberg games and can be formulated as a bi-level program, which is linearized and converted to a single-level mixed-integer linear program using strong-duality theorem and Karush-Kuhn-Tucker conditions. To validate the proposed model, comprehensive simulation studies are performed on a test distribution network. The simulation results show that implementing the model can reduce the peak-off-peak difference and peak-to-average ratio of the network net-load by up to 15% and 24%, respectively.
引用
收藏
页数:12
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