An adaptive nonlinear predictor with orthogonal escalator structure for short-term load forecasting

Lu Q.-C.; Grady W.M.

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An adaptive nonlinear predictor with orthogonal escalator structure for short-term load forecasting

机译：具有正交自动扶梯结构的自适应非线性预测器，用于短期负荷预测

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An adaptive Hammerstein model with an orthogonal escalator structure as well as a lattice structure for joint process is developed for short-term load forecasting from one hour to several hours in the future. The method uses a Hammerstein nonlinear time-varying functional relationship between load and temperature. Parameters in both linear and nonlinear parts of the predictor are updated systematically using a scalar orthogonalization procedure. Matrix operations are avoided, thereby allowing better model-tracking ability, numerical properties, and performance. Prediction results using actual load-temperature data demonstrate that this algorithm performs better than the commonly used matrix-oriented recursive least-squares algorithm for one-hour-ahead forecasts.

机译：开发了一种自适应Hammerstein模型，该模型具有正交的自动扶梯结构以及用于联合过程的晶格结构，可用于将来从一小时到几小时的短期负荷预测。该方法使用了负载和温度之间的Hammerstein非线性时变函数关系。使用标量正交化程序可以系统地更新预测变量的线性和非线性部分中的参数。避免了矩阵运算，从而实现了更好的模型跟踪能力，数值特性和性能。使用实际负载温度数据的预测结果表明，对于一小时前的预测，该算法的性能优于常用的面向矩阵的递归最小二乘算法。

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《IEEE Transactions on Power Systems》 |1989年第1期|P.158-164|共7页
作者
Lu Q.-C.; Grady W.M.;
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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类理论与分析;电能学;
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An adaptive nonlinear predictor with orthogonal escalator structure for short-term load forecasting

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