河海大学学报（自然科学版）
河海大學學報（自然科學版）
하해대학학보（자연과학판）
JOURNAL OF HOHAI UNIVERSITY (NATURAL SCIENCES)
2015年
3期
271-277
,共7页
短期电力负荷%负荷预测%时间序列%RBF-ARX模型%循环预测%结构化非线性参数优化法
短期電力負荷%負荷預測%時間序列%RBF-ARX模型%循環預測%結構化非線性參數優化法
단기전력부하%부하예측%시간서렬%RBF-ARX모형%순배예측%결구화비선성삼수우화법
short-term electric load forecasting%load forecasting%time series%RBF-ARX model%cycle forecasting%structured nonlinear parameter optimization method
为了提高短期电力负荷预测的精度，提出基于RBF-ARX模型的短期电力负荷循环预测法：将短期电力负荷预测看作非线性时间序列预测问题，并根据历史负荷数据建立电力负荷自回归预测模型( ARX模型)，用 RBF 神经网络逼近 ARX 模型的参数，并用结构化非线性参数优化法( SNPOM)离线估计模型参数。用该方法对湖南某市电力负荷进行预测，将预测结果与实际负荷值进行比较，结果表明：基于RBF-ARX模型的短期电力负荷循环预测法精度高，可靠性强，具有很好的实用性。
為瞭提高短期電力負荷預測的精度，提齣基于RBF-ARX模型的短期電力負荷循環預測法：將短期電力負荷預測看作非線性時間序列預測問題，併根據歷史負荷數據建立電力負荷自迴歸預測模型( ARX模型)，用 RBF 神經網絡逼近 ARX 模型的參數，併用結構化非線性參數優化法( SNPOM)離線估計模型參數。用該方法對湖南某市電力負荷進行預測，將預測結果與實際負荷值進行比較，結果錶明：基于RBF-ARX模型的短期電力負荷循環預測法精度高，可靠性彊，具有很好的實用性。
위료제고단기전력부하예측적정도，제출기우RBF-ARX모형적단기전력부하순배예측법：장단기전력부하예측간작비선성시간서렬예측문제，병근거역사부하수거건립전력부하자회귀예측모형( ARX모형)，용 RBF 신경망락핍근 ARX 모형적삼수，병용결구화비선성삼수우화법( SNPOM)리선고계모형삼수。용해방법대호남모시전력부하진행예측，장예측결과여실제부하치진행비교，결과표명：기우RBF-ARX모형적단기전력부하순배예측법정도고，가고성강，구유흔호적실용성。
In order to improve the accuracy of short-term electric load forecasting, a cycle forecasting method for short-term electric load forecasting is proposed based on a radial basis function network-style coefficients autoregressive model with an exogenous variable ( RBF-ARX) model. First, the short-term electric load forecasting was regarded as a nonlinear time series prediction problem, and an autoregressive model ( ARX model) of electric load forecasting was established based on historical load data. Then, the ARX model parameters were approximated with the RBF neural network and were estimated with an off-line structured nonlinear parameter optimization method ( SNPOM) . Finally, based on this, a cycle forecasting method for short-term electric load forecasting was established. The proposed method was used to predict the short-time electric load in a certain city of Hunan Province. The predicted results were compared with the actual load values. The results show that the proposed method has high accuracy, reliability, and practicability.
