智能配电网超短期负荷状态估计模型的改进

摘要

传统的电网负荷状态估计方法存在超短期周期下实时量测在线准确率低的问题,提出一种改进的智能配电网的超短期负荷状态估计模型,其将采集到的数据反馈到数据采集服务器中.采用配电网并行分层估计方法,解决超短期实时预测节点负荷的小周期问题.融合各层的超短期负荷预测结果,得到总体配电网超短期负荷预测值.将电网负荷预测值反馈给上位机,提高状态估计的效率.实验结果说明,所设计模型对超短期负荷预测具有较高的精度和效率.%Due to the low accuracy of online real-time measurement of traditional load state estimation method for power grid in super short term cycle,an improved ultra short-term load state estimation model of intelligent power distribution network was proposed,which fed back the collected data to the data acquisition server.The parallel hierarchical estimation method was adopted in the distribution network to solve the small period problem of ultra short-term real-time forecasting node.The ultra short-term load forecasting results of each layer were integrated and the estimated value of the overall distribution network short-term load was obtained.The estimated value was fed back to the upper monitor to improve the efficiency of state estimation.The experiment result shows that the designed ultra short-term load forecasting model has higher precision and efficiency.