Short-term load forecasting model for metro power supply system based on echo state neural network

Yu Litao, Han Aoyang, Wang Li, Jia Xu, Zhang Zhisheng
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引用次数: 5

Abstract

The paper presents a short-term load forecasting model for metro power supply system based on echo state neural network. Echo state neural network composed of input layer, reserve pool, the output layer. Reserve pool as a dynamic network is connected by a large number of random sparse of neurons. Reserve pool is used to overcome the slow convergence speed and avoid neural network into the local minimum. Using the actual historical data of the metro power supply system to simulate, the simulation results show that the short-term load forecasting model for metro power supply system based on echo state neural network has good prediction accuracy.
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基于回波状态神经网络的地铁供电系统短期负荷预测模型
提出了一种基于回波状态神经网络的地铁供电系统短期负荷预测模型。回声状态神经网络由输入层、储备池、输出层组成。储备池作为一个动态网络,由大量随机稀疏的神经元连接而成。利用储备池克服了收敛速度慢的问题,避免了神经网络陷入局部极小值。利用地铁供电系统的实际历史数据进行仿真,仿真结果表明,基于回波状态神经网络的地铁供电系统短期负荷预测模型具有较好的预测精度。
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