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Residential demand response behavior analysis based on Monte Carlo simulation: The case of Yinchuan in China

机译:基于蒙特卡洛模拟的居民需求响应行为分析:以中国银川为例

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摘要

Demand response to time-varying pricing of electricity is critical to a smart grid's efficient management of electrical resources. This paper presents a new approach to quantify residential demand responsiveness to (time-of-use) TOU rates, which does not entail an econometric estimation of TOU demand equations. Based on one of the four smart grid pilots in China, our approach uses the survey data collected in 2011 from 236 residents in Yinchuan to implement a Monte Carlo simulation to obtain the minimum, expected and maximum demand responsiveness to four TOU rate designs. We find that residents do not respond to TOU pricing when the TOU rate design only causes a 10% increase in their existing electricity bills under non-TOU rates. However, their estimated peak demand responsiveness is 8.41% (21.26%) when the peak-time price increases by 20% (40%). Based on these findings, we conclude that suitably designed TOU rates are useful to the efficient operation of a smart grid.
机译:对时变电价的需求响应对于智能电网的电力资源有效管理至关重要。本文提出了一种量化住宅需求对(使用时间)TOU费率的响应性的新方法,该方法不需要对TOU需求方程进行计量经济学估算。基于中国四个智能电网试点之一,我们的方法使用了2011年从银川市236名居民那里收集的调查数据,进行了蒙特卡洛模拟,从而获得了对四种TOU费率设计的最小,预期和最大需求响应。我们发现,当使用分时电价设计时,在不使用分时电价的情况下,现有电费只会增加10%,居民不会对分时电价做出回应。但是,当高峰时间价格上涨20%(40%)时,他们估计的高峰需求响应能力为8.41%(21.26%)。基于这些发现,我们得出结论,适当设计的TOU费率对于智能电网的有效运行非常有用。

著录项

  • 来源
    《Energy》 |2012年第1期|230-236|共7页
  • 作者单位

    School of Economics and Management, North China Electric Power University, Zhu Xin Zhuang, Bei Nong Road No. 2, Changping District, Beijing 102206, China;

    School of Economics and Management, North China Electric Power University, Zhu Xin Zhuang, Bei Nong Road No. 2, Changping District, Beijing 102206, China;

    Decision and Information Sciences Division, Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL, USA,School of Economics and Management, Shanghai University of Electric Power, Ping Yang Road No. 2103, Yangpu District, Shanghai, China;

    School of Economics and Management, North China Electric Power University, Zhu Xin Zhuang, Bei Nong Road No. 2, Changping District, Beijing 102206, China;

    School of Economics and Management, North China Electric Power University, Zhu Xin Zhuang, Bei Nong Road No. 2, Changping District, Beijing 102206, China,Cansu Electric Power Corporation, Xi fin East Road No. 628, Lanzhou, Cansu Province, China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    smart grid; monte carlo simulation; residential demand response; TOU rates;

    机译:智能电网;蒙特卡洛模拟住宅需求响应;TOU费率;

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