摘要
智能电网用户端环境下的用电模式有其自身的特点。结合该特点对成熟的神经元网络负荷预测方法进行改进,着重优化预测的输入部分,形成一套适合智能电网用户端环境下短期负荷预测方法。算例结果表明,该方案有助于预测准确率的提高。
The smart grid energy consumption patterns in the user side have its own characteristics.The artificial neural network（ANN）,which is a mature method in short-term load forecast（SLF）,was used in the user side environment of smart grid.Its input mode was changed according to the characteristics of the user side power consumption.The experimental results verify that the method can help to improve the forecasting accuracy.
出处
《低压电器》
2012年第17期8-12,共5页
Low Voltage Apparatus
基金
上海市科学技术委员会资助(10dz1202900)
关键词
智能电网用户端
短期负荷预测
神经元网络
模型参数修正
smart grid user side
short-term load forecast
artificial neural network
correction of model parameters
