人工神经网络及其在电力短期负荷预测中的应用研究

Phisical Neural Networks and Applied Research on the Power Short-term Load Forecast

电力系统负荷预测的精度将直接影响电力系统的经济效益和用电的安全和稳定。通过讨论短期负荷预测,来阐述Levenberg-Marquardt算法优于传统BP算法。并分别用BP算法和Levenberg-Marquardt算法对绥龙110kV变电局所属供电网络远动采集来的负荷数据进行预测,来说明Levenberg-Marquardt算法优于传统BP算法。

Power load forecasting system will directly affect the accuracy of the power system and the economic benefits of electricity to the security and stability. By Short-term load forecasting is discussed, to elaborate Leven berg-Marquardt algorithm superior to the traditional BP algorithm. And BP were used algorithms and Levenberg- Marquardt algorithm Sui-long 110 kV power substation owned by the network to remote collection of data to predict the load,to illustrate Levenberg-Marquardt algorithm superior to the traditional BP algorithm.