基于PQ耦合潮流模型的电力负荷滚动预测方法

Rolling load forecasting method based on pq coupled power flow model

传统的电力负荷滚动预测方法在处理原始数据时,误差大,模型参数为一定值,难以与实际情况相符,得到的预测值与实际值相差较大。为了解决上述问题,基于PQ耦合潮流模型研究了一种新的电力负荷滚动预测方法,通过电力监测系统得到的一系列原始数据,对得到的原始数据集合采用加权的滑动平均指数法进行处理,引入自适应性滚动模型计算自适应性平滑指数。在PQ耦合潮流模型中建立具有自适应性的滚动优化参数,根据特定的目标函数对各模型所得预测值进行优化,最终得到更加准确的预测值。通过对比实验进行验证,结果表明,基于PQ耦合潮流模型研究的电力负荷滚动预测方法具有很强的原始数据处理能力,处理过程中模型参数不断改变,得到的结果与实际值相符度高。当PQ耦合节点个数为100个时,电力负荷预测值准确度高达99.4%。

The traditional rolling load forecasting method has a large error in processing the original data,and the model parameters are a certain value,which is difficult to conform to the actual situation,so the predicted value is quite different from the actual value.In order to solve the above problems,a new rolling load forecasting method based on PQ coupled power flow model is studied.A series of original data obtained from power monitoring system are processed by weighted sliding average index method,and adaptive rolling model is introduced to calculate adaptive smoothing.Index.In the PQ coupled power flow model,adaptive rolling optimization parameters are established,and the predicted values of each model are optimized according to the specific objective function.Finally,more accurate predicted values are obtained.The results of comparative experiments show that the rolling load forecasting method based on PQ coupled power flow model has strong original data processing ability,and the parameters of the model change constantly during the process of processing,and the results are in good agreement with the actual values.When the number of PQ coupling nodes is 100,the accuracy of the power load prediction is as high as 99.4%.