Hierarchical Distributed Energy Management Framework for Multiple Greenhouses Considering Demand Response

被引:7
|
作者
Rezaei, Ehsan [1 ]
Dagdougui, Hanane [1 ]
Ojand, Kianoosh [1 ]
机构
[1] Dept Math & Ind Engn, Polytech Montreal, Montreal, PQ H3T1J4, Canada
关键词
Distributed control; demand response; network of greenhouses; load shifting; load shaving; PREDICTIVE CONTROL; WATER;
D O I
10.1109/TSTE.2022.3215686
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Greenhouses are a key component of modernised agriculture, aiming for producing high-quality crops and plants. Furthermore, a network of greenhouses has enormous potential as part of demand response programs. Saving energy during off-peak time, reducing power consumption and delaying the start time of subsystems during on-peak time are some strategies that can be used to limit power exchanged with the main grid. In this work, a hierarchical distributed alternating direction method of multipliers-based model predictive control framework is proposed that has two main objectives: 1) providing appropriate conditions for greenhouses' crops and plants to grow, and 2) limiting the total power exchanged with the main grid. At each time step in the framework, an aggregator coordinates the greenhouses to reach a consensus and limit the total electric power exchanged while managing shared resources, e.g., reservoir water. The proposed framework's performance is investigated through a case study.
引用
收藏
页码:453 / 464
页数:12
相关论文
共 50 条
  • [41] Energy management in a demand response framework for efficient voltage control and distribution automation
    Davarzani, Sima
    Pisica, Ioana
    Taylor, Gareth A.
    2015 50TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2015,
  • [42] Smart energy management model for households considering incentive-based demand response
    Li, Zhihao
    Wang, Xiangjin
    Lin, Da
    Zheng, Ruonan
    Han, Bei
    Li, Guojie
    2021 POWER SYSTEM AND GREEN ENERGY CONFERENCE (PSGEC), 2021, : 327 - 332
  • [43] Building Energy Management Based on Demand Response Strategy Considering Dynamic Thermal Characteristic
    Yang, Fan
    Guo, Qinglai
    Pan, Zhaoguang
    Sun, Hongbin
    2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 2017,
  • [44] An effective quantum artificial rabbits optimizer for energy management in microgrid considering demand response
    Nehmedo Alamir
    Salah Kamel
    Mohamed H. Hassan
    Sobhy M. Abdelkader
    Soft Computing, 2023, 27 : 15741 - 15768
  • [45] Optimal scheduling of household appliances for smart home energy management considering demand response
    Lu, Xinhui
    Zhou, Kaile
    Chan, Felix T. S.
    Yang, Shanlin
    NATURAL HAZARDS, 2017, 88 (03) : 1639 - 1653
  • [46] Two-stage stochastic framework for energy hubs planning considering demand response programs
    Mansouri, Seyed Amir
    Ahmarinejad, Amir
    Javadi, Mohammad Sadegh
    Catalao, Joao P. S.
    ENERGY, 2020, 206
  • [47] An improved weighted mean of vectors algorithm for microgrid energy management considering demand response
    Alamir, Nehmedo
    Kamel, Salah
    Hassan, Mohamed H.
    Abdelkader, Sobhy M.
    NEURAL COMPUTING & APPLICATIONS, 2023, 35 (28) : 20749 - 20770
  • [48] Optimal scheduling of household appliances for smart home energy management considering demand response
    Xinhui Lu
    Kaile Zhou
    Felix T. S. Chan
    Shanlin Yang
    Natural Hazards, 2017, 88 : 1639 - 1653
  • [49] Home Energy Management Optimizing Models for Residential Demand Response Considering Compound DES
    Liu, Yanhua
    Wu, Kaiyue
    Zhao, Dongmei
    2014 INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2014,
  • [50] Smart distribution system management considering electrical and thermal demand response of energy hubs
    Davatgaran, Vahid
    Saniei, Mohsen
    Mortazavi, Seyed Saeidollah
    ENERGY, 2019, 169 : 38 - 49