Two-layer optimization approach for Electric Vehicle Charging Station with dynamic reconfiguration of charging points

被引:0
作者
Ramaschi, Riccardo [1 ]
Polimeni, Simone [2 ]
Cabrera-Tobar, Ana [1 ]
Leva, Sonia [1 ]
机构
[1] Politecn Milan, DOE, Via La Masa 34, I-20156 Milan, Italy
[2] Free2move eSolut SpA, Piazzale Lodi 3, I-20137 Milan, Italy
关键词
Electric vehicle charging station; Energy scheduling; Electric vehicle allocation; Model predictive control; Two layer optimization; Dynamic switching; Parking lot; Demand response; Renewable energy; ENERGY MANAGEMENT; PARKING LOTS; ALLOCATION; SYSTEM; MODEL; OPERATION;
D O I
10.1016/j.segan.2024.101531
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
This paper presents a two-layer optimization of a fast Electric Vehicle (EV) Charging Station powered by the grid, a Photovoltaic (PV) system, and a Battery Energy Storage System (BESS). The paper aims to increase profits by providing an energy schedule of the BESS and the grid, but also dynamically adjusting the power output of every Charging Point (CP). The first layer of optimization gives the daily energy scheduling in thirty minute intervals considering forecast values of PV production, EV cumulative demand, and electrical price. Meanwhile, the second layer, based on Model Predictive Control, adapts in real time the energy scheduling from the first layer taking into account the actual EV power demand, and the PV power production. Additionally, it dynamically allocates power to each CP depending on the EVs remaining charging time which is estimated using the corresponding EV power curve. The power rate of each CP varies by mechanically changing the internal connection of the Charging Column (CC). We evaluate the proposed methodology by introducing forecast errors regarding the cumulative EV demand and PV power production on sunny and cloudy days. Additionally, we assess the real-time operation with diverse EV arrival times, EV power demand and random EV types. Our findings demonstrate that the optimal dynamic reconfiguration of the CC effectively enables adherence to the daily energy schedule, ensuring increased profit, and EV's satisfaction without affecting the charging time.
引用
收藏
页数:21
相关论文
共 66 条
  • [61] Robust optimization for energy transactions in multi-microgrids under uncertainty
    Zhang, Bingying
    Li, Qiqiang
    Wang, Luhao
    Feng, Wei
    [J]. APPLIED ENERGY, 2018, 217 : 346 - 360
  • [62] Dynamic Charging Scheduling for EV Parking Lots With Photovoltaic Power System
    Zhang, Yongmin
    Cai, Lin
    [J]. IEEE ACCESS, 2018, 6 : 56995 - 57005
  • [63] Pricing for private charging pile sharing considering EV consumers based on non-cooperative game model
    Zhao, Zhenli
    Zhang, Lihui
    Yang, Meng
    Chai, Jianxue
    Li, Songrui
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 254
  • [64] A Novel Two-Stage, Dual-Layer Distributed Optimization Operational Approach for Microgrids with Electric Vehicles
    Zhou, Bowen
    Zhang, Zhibo
    Xi, Chao
    Liu, Boyu
    [J]. MATHEMATICS, 2023, 11 (21)
  • [65] Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm
    Zhou, Guangyou
    Zhu, Zhiwei
    Luo, Sumei
    [J]. ENERGY, 2022, 247
  • [66] Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices
    Zhou, Kaile
    Cheng, Lexin
    Lu, Xinhui
    Wen, Lulu
    [J]. APPLIED ENERGY, 2020, 276