Optimal Energy Management and Control of an Industrial Microgrid With Plug-In Electric Vehicles

被引:18
|
作者
Casini, Marco [1 ]
Zanvettor, Giovanni Gino [1 ]
Kovjanic, Milica [1 ]
Vicino, Antonio [1 ]
机构
[1] Univ Siena, Dipartimento Ingn Informaz & Sci Matemat, I-53100 Siena, Italy
关键词
Industrial microgrids; receding horizon control; dynamic optimal power flow; plug-in electric vehicles; chance constraints; OPTIMAL ALLOCATION; CHARGING STATIONS; OPTIMIZATION; STORAGE; OPERATION; MODEL;
D O I
10.1109/ACCESS.2019.2930274
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
An industrial microgrid (IMG) consists in a microgrid involving manufacturer plants that are usually equipped with distributed generation facilities, industrial electric vehicles, energy storage systems, and so on. In this paper, the problem of IMG-efficient operation in the presence of plug-in electric vehicles is addressed. To this purpose, the schedule of the different device operations of IMGs has to be optimally computed, minimizing the operation cost while guaranteeing the electrical network stability and the production constraints. Such a problem is formulated in a receding horizon framework involving dynamic optimal power flow equations. Uncertainty affecting plug-in electric vehicles is handled by means of a chance constraint approach. The obtained nonconvex problem is then approximately solved by exploiting suitable convex relaxation techniques. The numerical simulations have been performed showing computational feasibility and robustness of the proposed approach against increased penetration of the electric vehicles.
引用
收藏
页码:101729 / 101740
页数:12
相关论文
共 50 条
  • [31] Optimal power management of plug-in hybrid electric vehicles with trip modeling
    Gong, Qiuming
    Li, Yaoyu
    Peng, Zhong-Ren
    PROCEEDINGS OF THE ASME INTERNATIONAL MECHANICAL ENGINEERING CONGRESS AND EXPOSITION 2007, VOL 16: TRANSPORTATION SYSTEMS, 2008, : 53 - 62
  • [32] Trip-oriented Energy Management Control Strategy for Plug-in Hybrid Electric Vehicles
    Yu, Hai
    Kuang, Ming
    McGee, Ryan
    2011 50TH IEEE CONFERENCE ON DECISION AND CONTROL AND EUROPEAN CONTROL CONFERENCE (CDC-ECC), 2011, : 5805 - 5812
  • [33] Neural network energy management strategy with optimal input features for plug-in hybrid electric vehicles
    Lu, Ziwang
    Tian, He
    Sun, Yiwen
    Li, Runfeng
    Tian, Guangyu
    ENERGY, 2023, 285
  • [34] Optimal energy management strategy for plug-in hybrid electric vehicles based on a combined clustering analysis
    Zhang, Jianan
    Chu, Liang
    Wang, Xu
    Guo, Chong
    Fu, Zicheng
    Zhao, Di
    APPLIED MATHEMATICAL MODELLING, 2021, 94 : 49 - 67
  • [35] State-of-Health Aware Optimal Control of Plug-in Electric Vehicles
    Wang, Yanzhi
    Yue, Siyu
    Pedram, Massoud
    2014 IEEE PES GENERAL MEETING - CONFERENCE & EXPOSITION, 2014,
  • [36] Continuous-time Optimal Charging Control of Plug-in Electric Vehicles
    Khatami, Roohallah
    Parvania, Masood
    Oikonomou, Konstantinos
    2018 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2018,
  • [37] Optimal Charging Control for Plug-in Electric Vehicles in Smart Microgrids Fueled by Renewable Energy Sources
    Zhu, Li
    Yu, F. Richard
    Ning, Bin
    Tang, Tao
    INTERNATIONAL JOURNAL OF GREEN ENERGY, 2013, 10 (09) : 924 - 943
  • [38] Enhancing microgrid sustainability: Dynamic management of renewable resources and plug-in hybrid electric vehicles
    Zheng, Yangbing
    Xue, Xiao
    Xi, Sun
    Xin, Wang
    JOURNAL OF CLEANER PRODUCTION, 2024, 450
  • [39] Sizing and Siting of Distributed Generators and Energy Storage in a Microgrid Considering Plug-in Electric Vehicles
    Zhang, Mingrui
    Gan, Ming
    Li, Luyao
    ENERGIES, 2019, 12 (12)
  • [40] Hierarchical management for Building Microgrid Considering Virtual Storage System and Plug-in Electric Vehicles
    Jin, Xiaolong
    Mu, Yunfei
    Jia, Hongjie
    Wu, Jianzhong
    Xu, Xiandong
    Yu, Xiaodan
    Qi, Fengyu
    PROCEEDINGS OF RENEWABLE ENERGY INTEGRATION WITH MINI/MICROGRID (REM2016), 2016, 103 : 219 - 224