基于粒子滤波器的大容量冲击负荷短期预测方法

HUANG Renke; LUO Chenchi; ZHANG Ming

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基于粒子滤波器的大容量冲击负荷短期预测方法

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- 基于粒子滤波器的大容量冲击负荷短期预测方法
- Automation of Electric Power Systems Vol. 33, Issue 3, Pages: 40-45(2009)
- 作者机构：
  
  上海交通大学电子信息与电气工程学院,上海市,200030
- 作者简介：
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- Published：2009
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HUANG Renke, LUO Chenchi, ZHANG Ming. [J]. Automation of electric power systems, 2009, 33(3): 40-45.
DOI：

HUANG Renke, LUO Chenchi, ZHANG Ming. [J]. Automation of electric power systems, 2009, 33(3): 40-45. DOI：

摘要

应用基于α稳定分布的概率模型建立了新的电力系统短期负荷时变模型，充分利用了α稳定分布对大容量冲击性负荷良好的模拟特性。应用粒子滤波器对所建立的短期负荷模型的时变参数进行估计，然后利用估计所得的最新参数预测短期负荷。粒子滤波器突破了以往研究的各种滤波器必须建立在负荷模型是高斯分布的线性模型以及模型的参数必须是定常数的局限，可以研究非高斯非线性的时变系数系统模型。结合实际电网负荷数据的实验验证了所提出的方法对大容量冲击性负荷预测的有效性。

Abstract

This paper presents a new time-varying power system short-term load model based on the α stable distribution that can satisfactorily simulate the features of the high capacity impact load. The particle filter is applied to estimate the time-varying parameters of the short-term load model， with the latest parameters obtained by estimation used for load forecasting. The particle filter has overcome the drawbacks of the conventional filters which can only work for the constant linear Gaussian system while incapable of working on the non-linear， non-Gaussian and time-varying system. The relative error analysis of the short-term load forecasting results on an actual power network validates the effectiveness of the proposed method.

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