基于大数据分析的智能电网降损效果估计模型仿真

摘要

针对智能电网降损效果动态估计结果误差较大的问题.提出基于大数据分析的智能电网降损效果估计模型,其采用Map/Reduce模型处理智能电网中的大数据,依据大数据统计和分析结果,将智能电网划分成不同的子网,采用不同负荷预测模型预测各子网负荷.融合子网的预测结果修正总体智能电网的负荷预测值.将负荷预测值输入智能电网降损概率评估模型,实现单一因素和组合因素约束下的智能电网降损分析,对智能电网降损效果进行动态评估.实验结果表明,所设计模型对智能电网工作日和休息日的负荷预测效果较好.%In view of the large dynamic estimation error of loss-reduction effect of smart grid,a smart grid loss-reduction estimation model is proposed in this paper based on big data analysis,which applies the Map/Reduce model to process the big data of smart grid.According to the statistic and analytical results,the smart grid can be divided into different subnets,and different load forecasting models are applied to predict the loads of subnets.The estimated overall load of smart grid is corrected through fussing the predicted loads of subnets.By inputting the load predictions into the smart grid loss probability evaluation model,the smart grid loss-reduction analysis can be realized under the restriction of both single and combined factors,and a dynamic assessment can be made on the loss-reduction effect of the smart grid.The experimental results show that the proposed model is very effective for estimating the loads of smart grid on both weekdays and playdays.