基于改进鸡群算法的非侵入式家电负荷分解
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(1.上海电力学院电气工程学院,上海 200090;2.上海和联通讯工程有限公司,上海 201108)

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许仪勋(1969-),男,博士,硕士生导师,研究方向为电能质量及智能用电;E-mail:xu_yixun@sina.com
李 旺(1989-),男,硕士研究生,研究方向为智能用电;E-mail:914384645@qq.com
李东东(1976-),男,博士,教授,硕士生导师,主要从事风力发电与电力系统稳定控制、智能用电等方面的研究工作。

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上海绿色能源并网工程技术研究中心(13DZ225 1900)


Disaggregation for non-invasive domestic appliances based on the improved chicken swarm optimization algorithm
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(1. School of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China;
;2. Shanghai Helian Communication Engineering Co., Ltd., Shanghai 201108, China)

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    摘要:

    基于家电负荷在稳态工作时电流具有线性叠加的特点,提出一种基于家电负荷稳态基波电流和谐波电流为负荷特征量的非侵入式家电负荷分解算法。通过将一家电负荷的任一工作状态用0和1来表示,即只有关和开这两种状态,则家电负荷分解问题可转化为求解优化组合问题,然后运用改进鸡群算法来识别各个家电的工作状态。最后通过实例验证了该算法具有较高的负荷识别准确率和广泛的适用性,有利于非侵入式家电负荷分解技术的推广与应用。

    Abstract:

    Considering that the current of domestic appliances in steady work condition has the characteristics of linear superposition, the disaggregation algorithm for non-invasive domestic appliance loads is proposed. And this new algorithm features in taking the fundamental current and harmonic current of the steady domestic appliance loads as load characteristics. By marking any work condition of the domestic appliance load with “0” and “1”, which means only two states are available, close and open, the issue of domestic appliance loads aggregation can be turned into optimization and the work condition of each domestic appliance load will be identified via the improved chicken swarm optimization algorithm. Case study verifies this algorithm is of higher load accuracy and broader availability conductive to the popularization and application for the non-invasive domestic appliance loads identification technology.

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许仪勋,李 旺,李东东,等.基于改进鸡群算法的非侵入式家电负荷分解[J].电力系统保护与控制,2016,44(13):27-32.[XU Yixun, LI Wang, LI Dongdong, et al. Disaggregation for non-invasive domestic appliances based on the improved chicken swarm optimization algorithm[J]. Power System Protection and Control,2016,V44(13):27-32]

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  • 收稿日期:2015-08-05
  • 最后修改日期:2016-03-03
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  • 在线发布日期: 2016-07-03
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