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Optimization model for home energy management system of rural dwellings

Author

Listed:
  • Huang, Zhijia
  • Wang, Fang
  • Lu, Yuehong
  • Chen, Xiaofeng
  • Wu, Qiqi

Abstract

In the context of the increasing popularity of distributed energy, this paper proposes a home energy management system method considering the working state of flexible load to deal with the problem of mismatch between home energy supply and demand. Specifically, in this paper, the flexible load in the system is studied, and the model of flexible load and its working state are established. On this basis, combined with the real-time electricity price of the grid, the model of home energy management system is constructed to minimize the electricity purchase cost and improve the utilization rate of renewable energy, the genetic algorithm is used to solve it, and the influence of time step, flexible load ratio and whether to use energy storage equipment on the optimization degree of the model are analyzed. The research results show that, while meeting the requirements of human comfort and electricity demand, the daily electricity purchase cost of the system with flexible load scheduling is 22.5% lower than that of the system without flexible load scheduling, and the utilization rate of renewable energy is increased by 16.5%. In terms of model optimization, shortening the prediction time step, increasing the proportion of flexible load and using energy storage equipment can further reduce the electricity purchase cost. The case study confirms the effectiveness of the proposed home energy management system model, which can provide an efficient optimal scheduling scheme for household energy saving.

Suggested Citation

  • Huang, Zhijia & Wang, Fang & Lu, Yuehong & Chen, Xiaofeng & Wu, Qiqi, 2023. "Optimization model for home energy management system of rural dwellings," Energy, Elsevier, vol. 283(C).
    • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024337
    DOI: 10.1016/j.energy.2023.129039
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    Cited by:

    1. Hussain, Sadam & Azim, M. Imran & Lai, Chunyan & Eicker, Ursula, 2023. "New coordination framework for smart home peer-to-peer trading to reduce impact on distribution transformer," Energy, Elsevier, vol. 284(C).

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