| 基于粒子滤波算法的电力系统短期负荷预测研究 |
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| 引用本文： | 李凯,刘金海,陆岩.基于粒子滤波算法的电力系统短期负荷预测研究[J].电力学报,2011,26(6):466-469,475. |
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| 作者姓名： | 李凯 刘金海 陆岩 |
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| 作者单位： | 1. 辽宁省电力公司沈阳供电公司,沈阳,110003
2. 东北大学信息科学与工程学院,沈阳,110003 |
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| 摘 要： | 针对电力系统短期负荷随机性和偶然性较大,使得传统的卡尔曼滤波或者扩展卡尔曼算法不能发挥最优的滤波效果的问题,建立了基于粒子滤波算法的负荷预测模型,并讨论了参数选择对预测结果的影响,给出了优化的状态参数选择区间.通过对仿真验证了本文方法的有效性,最后将本文的方法与卡尔曼滤波算法进行了对比仿真,仿真结果证明本文提出的方法具...
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| 关 键 词： | 电力系统 短期负荷预测 粒子滤波 卡尔曼滤波 |
Electric Power System Short-term Load Forecasting Based on Particle Filter Algorithm |
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| LI Kai
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LIU Jin-hai
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LU Yan.Electric Power System Short-term Load Forecasting Based on Particle Filter Algorithm[J].Journal of Electric Power,2011,26(6):466-469,475. |
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| Authors: | LI Kai LIU Jin-hai LU Yan |
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| Affiliation: | 1.Shenyang power supply company,Liaoning Electric Power Corp.,Shenyang 110003,China; 2.School of Information Science and Engineering,Northeastern University,Shenyang 110004,China) |
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| Abstract: | The Kalman filter or extended Kalman filter could not perform well in dynamic systems that are typically nonlinear and non-Gaussian,especially in the load forecasting problem which is of strong randomness.This paper derived and constructed the load forecasting model based on particle filter,which was testified to be an effective method by plenty of simulations.The proper range of state vector was proposed either by a method of traversal algorithm.Finally,this method showed a better performance compared with Kalman filter. |
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| Keywords: | power system short-term load forecasting particle filter kalman filter |
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