基于配电网全域大数据的负荷智能预测模型

Intelligent Load Forecasting Model Based on Global Big Data of Distribution Network

为了精准预测配电网负荷,为电力系统调度运行提供科学依据,设计基于配电网全域大数据的负荷智能预测模型,分析影响配电网负荷因素,依据分析结果采集历史配电网全域数据集,对数据集实施预处理,建立训练样本集,长短期记忆神经网络根据训练集建立配电网负荷智能预测模型,最后结果表明,该模型的配电网负荷预测结果与历史实际负荷几乎吻合,预测性能稳定,预测结果精准可靠,可有效保障电力系统的精准调度运行。

In order to accurately predict the load of distribution network and provide scientific basis for power system dispatching operation,an intelligent load forecasting model based on global big data of distribution network is designed to analyze the factors affecting the load of distribution network,collect the global data set of historical distribution network according to the analysis results,preprocess the data set and establish a training sample set,The long-term and short-term memory neural network establishes the distribution network load intelligent prediction model according to the training set.The final results show that the distribution network load prediction results of the model are almost consistent with the historical actual load,the prediction performance is stable,the prediction results are accurate and reliable,and can effectively ensure the accurate dispatching operation of the power system.