CAJ | 학술논문

针对风电功率具有非平稳性和波动集群现象，提出一种基于集合经验模态分解和自回归条件异方差组合模型预测方法。该方法通过EEMD分解法将风电出力分解为一系列平稳的时序分量，再由游程判定法，将时序分量重组为波动分量、短期趋势分量和长期趋势分量，以集中分量特征信息降低预测难度；针对各分量的波动特征，建立相应的ARCH预测模型。算例结果表明，该种组合预测方法简单，具有较高的预测精度，能更好的反应风电功率的波动特性。
침대풍전공솔구유비평은성화파동집군현상，제출일충기우집합경험모태분해화자회귀조건이방차조합모형예측방법。해방법통과EEMD분해법장풍전출력분해위일계렬평은적시서분량，재유유정판정법，장시서분량중조위파동분량、단기추세분량화장기추세분량，이집중분량특정신식강저예측난도；침대각분량적파동특정，건립상응적ARCH예측모형。산례결과표명，해충조합예측방법간단，구유교고적예측정도，능경호적반응풍전공솔적파동특성。
The wind power has the qualifications of random and volatility concentration .This paper presents a com-bined model prediction method based on ensemble empirical mode decomposition ( EEMD) and autoregressive condi-tional heteroscedasticity model ( ARCH) .By means of the EEMD , the wind power sequence is decomposed into a se-ries of stationary components .Then the components are reconstructed into fluctuant components , medium-term trend and long-term trend components for centralizing the characteristic information and reducing the difficulty of predicting . Finally, considering the fluctuation characteristics of different types of components , the different ARCH models are built.Simulation results show that the combined prediction can offer more accurate forecasting results and reflect the fluctuation characteristics of wind power .