基于隐马尔可夫模型的日内风电功率预测误差区间滚动估计

ZHOU Wei

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基于隐马尔可夫模型的日内风电功率预测误差区间滚动估计

更新时间：2025-08-13

- 基于隐马尔可夫模型的日内风电功率预测误差区间滚动估计
- Automation of Electric Power Systems Vol. 42, Issue 21, Pages: 90-95(2018)
- 作者机构：
  
  大连理工大学电气工程学院,辽宁省,大连市,116024
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2018
- 稿件说明：
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ZHOU Wei. [J]. Automation of electric power systems, 2018, 42(21): 90-95.
DOI：

ZHOU Wei. [J]. Automation of electric power systems, 2018, 42(21): 90-95. DOI：

摘要

风电的波动性和不确定性给大规模风电并网带来了挑战，估计风电场上报风电的预测功率误差范围，能够为含风电电力系统的运行调度提供重要信息。因此，提出基于隐马尔可夫模型的日内风电功率预测误差区间滚动估计方法。通过建立隐马尔可夫模型实现一定置信水平下对风电功率误差波动区间的快速估计，并利用局部加权回归散点平滑法对误差区间进行处理。以实际数据为例分析，结果表明所提方法能够给出风电功率预测误差的波动范围，为电力系统的调度与控制、备用容量的配置、风险评估等方面提供更全面的信息。

Abstract

The randomness and fluctuation of wind power bring challenges to the integration of wind power to the power grid. The error range estimation of predicted power for wind farms can provide important information for the operation and the scheduling of power system with wind power. So

an interval rolling estimation method for daily wind power forecast errors is proposed

which is based on hidden Markov model. The hidden Markov model can be built to achieve fast estimation of wind power error fluctuation range under the certain confidence level

and the local weighted regression smoothing method is used to deal with the error interval. Based on the actual data

the simulation results show that this method can give the fluctuation range of the wind power prediction error and provide more comprehensive information for the power system scheduling and control

the allocation of backup capacity

the risk assessment and so on.

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