Residential power scheduling for demand response in smart grid

被引:200
|
作者
Ma, Kai [1 ]
Yao, Ting [1 ]
Yang, Jie [1 ,2 ]
Guan, Xinping [2 ]
机构
[1] Yanshan Univ, Sch Elect Engn, Qinhuangdao 066004, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Automat, Minist Educ, Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Smart grid; Demand response; Day-ahead price; Power scheduling; Optimization; SIDE MANAGEMENT; LOAD CONTROL; OPTIMIZATION; BUILDINGS;
D O I
10.1016/j.ijepes.2015.11.099
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
This paper studies the power scheduling problem for residential consumers in smart grid. In general, the consumers have two types of electric appliances. The first type of appliances have flexible starting time and work continuously with a fixed power. The second type of appliances work with a flexible power in a predefined working time. The consumers can adjust the starting time of the first type of appliances or reduce the power consumption of the second type of appliances to reduce the payments. However, this will also incur discomfort to the consumers. Assuming the electricity price is announced by the service provider ahead of time, we propose a power scheduling strategy for the residential consumers to achieve a desired trade-off between the payments and the discomfort. The power scheduling is formulated as an optimization problem including integer and continuous variables. An optimal scheduling strategy is obtained by solving the optimization problem. Simulation results demonstrate that the scheduling strategy can achieve a desired tradeoff between the payments and the discomfort. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:320 / 325
页数:6
相关论文
共 50 条
  • [21] A Review on Residential Area Demand Response Analysis in Smart Grid Era
    Paul, Subho
    Choudhary, Sachin
    Prasad, Narayana
    2018 IEEE 8TH POWER INDIA INTERNATIONAL CONFERENCE (PIICON), 2018,
  • [22] Peak Demand Scheduling in the Smart Grid
    Yaw, Sean
    Mumey, Brendan
    McDonald, Erin
    Lemke, Jennifer
    2014 IEEE INTERNATIONAL CONFERENCE ON SMART GRID COMMUNICATIONS (SMARTGRIDCOMM), 2014, : 770 - 775
  • [23] Performance evaluation of power demand scheduling scenarios in a smart grid environment
    Vardakas, John S.
    Zorba, Nizar
    Verikoukis, Christos V.
    APPLIED ENERGY, 2015, 142 : 164 - 178
  • [24] A demand response modeling for residential consumers in smart grid environment using game theory based energy scheduling algorithm
    Reka, S. Sofana
    Ramesh, V.
    AIN SHAMS ENGINEERING JOURNAL, 2016, 7 (02) : 835 - 845
  • [25] Smart residential electricity distribution system (SREDS) for demand response under smart grid environment
    Selvan Manickavasagam Parvathy
    CSI Transactions on ICT, 2020, 8 (2) : 231 - 234
  • [26] Building power demand response methods toward smart grid
    Wang, Shengwei
    Xue, Xue
    Yan, Chengchu
    HVAC&R RESEARCH, 2014, 20 (06): : 665 - 687
  • [27] Cyber and Physical Integration Analysis for Automated Residential Demand Response in Smart Grid
    Jia, Kunqi
    He, Guangyu
    Fan, Shuai
    Lin, Guoying
    Lu, Shixiang
    Pan, Feng
    2017 IEEE PES ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2017,
  • [28] A Smart Demand Response Management Scheme for Direct Load Control in Residential Grid
    Dash, Shitikantha
    Sodhi, Ranjana
    Sodhi, Balwinder
    2018 20TH NATIONAL POWER SYSTEMS CONFERENCE (NPSC), 2018,
  • [29] Design of Intelligent Power Meter for Demand Response of Smart Grid
    Chen, Chao-Shun
    Ku, Te-Tien
    Lin, Chia-Hung
    ELECTRICAL POWER & ENERGY SYSTEMS, PTS 1 AND 2, 2012, 516-517 : 1692 - +
  • [30] A new flexible and resilient model for a smart grid considering joint power and reserve scheduling, vehicle-to-grid and demand response
    Alirezazadeh, Atefeh
    Rashidinejad, Masoud
    Afzali, Peyman
    Bakhshai, Alireza
    Sustainable Energy Technologies and Assessments, 2021, 43