A fast building demand response method based on supply-demand coordination for urgent responses to smart grids

被引:8
|
作者
Jin, Chen [1 ]
Yan, Chengchu [1 ]
Tang, Rui [2 ]
Cai, Hao [1 ]
Zeng, Ruixuan [1 ]
机构
[1] Nanjing Tech Univ, Coll Urban Construct, Nanjing 210009, Jiangsu, Peoples R China
[2] Hong Kong Polytech Univ, Dept Bldg Serv Engn, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
THERMAL COMFORT EVALUATION; AIR-CONDITIONING SYSTEMS; CHILLED-WATER-SYSTEMS; DIRECT LOAD CONTROL; CONTROL STRATEGY; LIMITING CONTROL; MODEL; REQUESTS; MASS;
D O I
10.1080/23744731.2019.1653626
中图分类号
O414.1 [热力学];
学科分类号
摘要
Many demand response (DR) measures are available for building air-conditioning systems, which can be categorized as demand-side-based controls and supply-side-based controls. However, due to the limitations of response speed and/or thermal comfort control, existing methods cannot economically and effectively meet the urgent DR requests from grids in emergency situations. This paper proposes a fast building demand response method based on supply-demand-side coordination for urgent responses to smart grids. It combines both the demand-side-based and supply-side-based control measures simultaneously. On the supply side, direct load control actions are employed to provide immediate power reductions. On the demand side, indoor air temperature set-points are adjusted stepwise according to an "incremental schedule" to achieve a uniform indoor temperature rise in different zones. In addition, two performance indexes are newly proposed to evaluate the sacrifice degree of thermal comfort. Measures for avoiding power rebound in post-DR periods are also considered. The proposed DR method is tested as a case study in a virtual building. The results show that through the coordinated control of the supply and demand side, a fast and effective DR (e.g., 18.3% of power reduction) is achieved with a uniform sacrifice of thermal comfort.
引用
收藏
页码:1494 / 1504
页数:11
相关论文
共 50 条
  • [31] Analysis of Water Supply-Demand Based on Socioeconomic Efficiency
    Ren, Wenying
    Bai, Xue
    Wang, Yuetian
    Liang, Chaoming
    Huang, Siyan
    Wang, Zhiying
    Yang, Liu
    JOURNAL OF SENSORS, 2022, 2022
  • [32] Fast Transactive Control for Frequency Regulation in Smart Grids with Demand Response and Energy Storage
    Ly, Andrew
    Bashash, Saeid
    ENERGIES, 2020, 13 (18)
  • [33] PRAHA - Price based demand Response framework for smArt Homes: Application to smart grids
    Chreim, Bashar
    Esseghir, Moez
    Merghem-Boulahia, Leila
    2023 INTERNATIONAL WIRELESS COMMUNICATIONS AND MOBILE COMPUTING, IWCMC, 2023, : 1585 - 1590
  • [34] An Optimal Demand Response Pricing Model for Smart Grids
    Qin, Yining
    Min, Liang
    Yao, Yiming
    2015 SEVENTH ANNUAL IEEE GREEN TECHNOLOGIES CONFERENCE (GREENTECH), 2015, : 44 - 49
  • [35] Demand Response in Smart Grids: Participants, Challenges, and a Taxonomy
    Hansen, Jacob
    Knudsen, Jesper
    Annaswamy, Anuradha M.
    2014 IEEE 53RD ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2014, : 4045 - 4052
  • [36] Demand Response in Smart Grids: Research Opportunities for the IS Discipline
    Strueker, Jens
    van Dinther, Clemens
    AMCIS 2012 PROCEEDINGS, 2012,
  • [37] Demand Response Analysis and Its Application to Smart Grids: A Evolutionary Game Method
    Zhou, Mengyu
    Liu, Xingwen
    Shao, Yingying
    INTELLIGENT NETWORKED THINGS, CINT 2024, PT I, 2024, 2138 : 152 - 160
  • [38] Taxi allocation model based on supply-demand analysis
    Wang, Na
    Li, Guo
    Qi, Xinshe
    Huang, Ruiping
    Li, Meng
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2019, 125 : 35 - 35
  • [39] Demand Response Management for Smart Grids With Wind Power
    Cicek, Nihan
    Delic, Hakan
    IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2015, 6 (02) : 625 - 634
  • [40] Evaluation of Voluntary Residential Demand Response in Smart Grids
    Barijough, Sanam Mirzazad
    Chen, Wei-Peng
    2014 INTERNATIONAL CONFERENCE ON INTELLIGENT GREEN BUILDING AND SMART GRID (IGBSG), 2014,