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Time Distribution Simulation of Household Power Load Based on Travel Chains and Monte Carlo–A Study of Beijing in Summer

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  • Jinpeng Liu

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

  • Hao Yang

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

  • Delin Wei

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

  • Xiaohua Song

    (School of Economics and Management, North China Electric Power University, Beijing 102206, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Beijing 102206, China)

Abstract

In recent years, China’s residential electricity consumption has continued to grow at high speed, and its contribution to the growth of the total electricity consumption has become more prominent. The peak-to-valley gap is also gradually increasing, which reduces the efficiency of electricity—an increasingly important terminal energy form. The resident travel chain is a major influencing factor of residents’ electricity consumption, and it is of great significance to dig deeper into the mechanism of its influence on residents’ electricity consumption behavior. In this paper, the time distribution model of household power load in summer in Beijing is constructed by comprehensively considering the difference of travel chain, electricity consumption behavior, and load level. The Monte Carlo simulation method is introduced for the simulation of the model. According to the results, both household type and temperature have a significant impact on the peak load, while the difference in the choice of mode of transportations does not. It is also found that the household appliance with the most potential for regulation is the air conditioning, followed by the water heater, which where regulation and optimization should be mainly carried out.

Suggested Citation

  • Jinpeng Liu & Hao Yang & Delin Wei & Xiaohua Song, 2021. "Time Distribution Simulation of Household Power Load Based on Travel Chains and Monte Carlo–A Study of Beijing in Summer," Sustainability, MDPI, vol. 13(12), pages 1-19, June.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:12:p:6651-:d:572819
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    References listed on IDEAS

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