With the progress of science and technology,big data technology is used more and more in power load forecasting.In order to improve the performance of the power load forecasting system based on big data technology,the research first designed an op-eration and maintenance management and control system based on big data technology,then combined K-means clustering with long and short term memory network to design a load forecasting model,and finally applied the operation and maintenance management and control system and power load forecasting module to the distribution network platform.The results show that the coefficient of determi-nation of the load forecasting model is increased by 0.051,0.089 and 0.128 compared with other models respectively,and the fitting degree and accuracy are higher.In practical application,the average difference between the predicted value and the real value of the load forecasting model is 1.0％,and the accuracy is high.The above conclusions prove that the design model has good performance and can provide scientific basis for the planning and scheduling of electric power system.
关键词
大数据技术/负荷预测/K均值/长短期记忆网络
Key words
big data technology/load forecasting/K mean/long short-term memory network
维普
万方数据