电子测试
電子測試
전자측시
ELECTRONIC TEST
2015年
4期
49-51
,共3页
ARMA模型%Kalman滤波%SVM模型%电力负荷预测
ARMA模型%Kalman濾波%SVM模型%電力負荷預測
ARMA모형%Kalman려파%SVM모형%전력부하예측
ARMA model%Kalman filter%SVM model%Power load forecasting
为提高电力负荷预测模型的预测精度本文将基本ARMA模型与Kalman滤波结合建立ARMA-Kalman滤波模型,将ARMA模型与SVM模型以及SVM的优化方法结合,建立ARMA-SVM模型,以试图提高模型的预测精度。同时将前两个模型以及基本ARMA模型应用于澳大利亚昆士兰州短期电力负荷预测中。实例研究表明,ARMA-Kalman模型未能如期较大提高对澳大利亚昆士兰州的电力负荷预测精度,ARMA-SVM模型在一定程度上提高了预测精度。
為提高電力負荷預測模型的預測精度本文將基本ARMA模型與Kalman濾波結閤建立ARMA-Kalman濾波模型,將ARMA模型與SVM模型以及SVM的優化方法結閤,建立ARMA-SVM模型,以試圖提高模型的預測精度。同時將前兩箇模型以及基本ARMA模型應用于澳大利亞昆士蘭州短期電力負荷預測中。實例研究錶明,ARMA-Kalman模型未能如期較大提高對澳大利亞昆士蘭州的電力負荷預測精度,ARMA-SVM模型在一定程度上提高瞭預測精度。
위제고전력부하예측모형적예측정도본문장기본ARMA모형여Kalman려파결합건립ARMA-Kalman려파모형,장ARMA모형여SVM모형이급SVM적우화방법결합,건립ARMA-SVM모형,이시도제고모형적예측정도。동시장전량개모형이급기본ARMA모형응용우오대리아곤사란주단기전력부하예측중。실례연구표명,ARMA-Kalman모형미능여기교대제고대오대리아곤사란주적전력부하예측정도,ARMA-SVM모형재일정정도상제고료예측정도。
To improve the forecasting accuracy of electricity load, the basic ARMA model and Kalman filter are combined into ARMA-Kalman filter model,ARMA model and SVM model along with its optimization methods are associated into ARMA-SVM model in this paper.The two models as well as basic ARMA model are employed in the forecasting of short-term electricity load in Queensland,Australia.The case study shows that ARMA-Kalman model can’t improve the forecasting accuracy as expected,while ARMA-SVM model improve the forecasting accuracy to some extent.