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A novel Traversal-and-Pruning algorithm for household load scheduling

Author

Listed:
  • Wang, Chengshan
  • Zhou, Yue
  • Wang, Jidong
  • Peng, Peiyuan

Abstract

With the various detail pricing schemes designed by utilities and the development of the smart grid technologies, consumers are motivated and enabled to schedule their home appliances to save energy, reduce cost and help grid operation. This paper presents a novel Traversal-and-Pruning (TP) algorithm which schedules thermostatically controlled household loads to meet an optimization objective considering both payment and comfort settings. The novel TP algorithm is robust and a flexible method is developed to balance the optimality and speed of the algorithm. Simulation results show that an improved load schedule is obtained by the novel TP algorithm compared to an existing algorithm.

Suggested Citation

  • Wang, Chengshan & Zhou, Yue & Wang, Jidong & Peng, Peiyuan, 2013. "A novel Traversal-and-Pruning algorithm for household load scheduling," Applied Energy, Elsevier, vol. 102(C), pages 1430-1438.
    • Handle: RePEc:eee:appene:v:102:y:2013:i:c:p:1430-1438
    DOI: 10.1016/j.apenergy.2012.09.010
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    Citations

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    Cited by:

    1. Mitra, Krishnendranath & Dutta, Goutam, 2016. "Electricity Consumption Scheduling with Energy Storage, Home-based Renewable Energy Production and A Customized Dynamic Pricing Scheme," IIMA Working Papers WP2016-11-01, Indian Institute of Management Ahmedabad, Research and Publication Department.
    2. Zeng, Yuan & Zhang, Ruiwen & Wang, Dong & Mu, Yunfei & Jia, Hongjie, 2019. "A regional power grid operation and planning method considering renewable energy generation and load control," Applied Energy, Elsevier, vol. 237(C), pages 304-313.
    3. Jaclason M. Veras & Igor Rafael S. Silva & Plácido R. Pinheiro & Ricardo A. L. Rabêlo, 2018. "Towards the Handling Demand Response Optimization Model for Home Appliances," Sustainability, MDPI, vol. 10(3), pages 1-18, February.
    4. Wang, Xiaoxue & Wang, Chengshan & Xu, Tao & Guo, Lingxu & Li, Peng & Yu, Li & Meng, He, 2018. "Optimal voltage regulation for distribution networks with multi-microgrids," Applied Energy, Elsevier, vol. 210(C), pages 1027-1036.
    5. Kazemi, Mehdi & Siano, Pierluigi & Sarno, Debora & Goudarzi, Arman, 2016. "Evaluating the impact of sub-hourly unit commitment method on spinning reserve in presence of intermittent generators," Energy, Elsevier, vol. 113(C), pages 338-354.
    6. Xiangyu Kong & Siqiong Zhang & Bowei Sun & Qun Yang & Shupeng Li & Shijian Zhu, 2020. "Research on Home Energy Management Method for Demand Response Based on Chance-Constrained Programming," Energies, MDPI, vol. 13(11), pages 1-27, June.
    7. Goutam Dutta & Krishnendranath Mitra, 2017. "A literature review on dynamic pricing of electricity," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1131-1145, October.
    8. Qiao, Guofu & Sun, Guodong & Li, Hui & Ou, Jinping, 2014. "Heterogeneous tiny energy: An appealing opportunity to power wireless sensor motes in a corrosive environment," Applied Energy, Elsevier, vol. 131(C), pages 87-96.

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