Short-term electricity load forecasting method based on multilayered self-normalizing GRU network

机译：基于多层自归一化GRU网络的短期电力负荷预测方法

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A multilayered self-normalizing gated recurrent units (MS-GRU) model is proposed for short-term electricity load forecasting. This model introduces scaled exponential linear units (SELU) activation function to squash the hidden states to calculate the output of the model. Meanwhile, the squashed states also contribute to the calculation of update gate, reset gate and candidate state of GRU. Therefore, exploding and vanishing gradient problem can be overcome in a stacked GRU neural network using this self-normalizing method. Fuzzy cluster-means (FCM) algorithm is used for the selection of similar days of electricity loads. Experiments illustrates that the MS-GRU model can give a more accurate forecast to the short-term electricity load compared with other RNN models.

机译：针对短期电力负荷预测，提出了一种多层自归一化门控递归单元模型。该模型引入了缩放指数线性单位（SELU）激活函数，以压缩隐藏状态以计算模型的输出。同时，压缩状态也有助于计算GRU的更新门，复位门和候选状态。因此，使用此自规范化方法可以解决堆叠GRU神经网络中爆炸和消失梯度的问题。模糊聚类均值（FCM）算法用于选择相似的用电天数。实验表明，与其他RNN模型相比，MS-GRU模型可以对短期电力负荷做出更准确的预测。

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来源
《IEEE Conference on Energy Internet and Energy System Integration》|2017年|1-5|共5页
会议地点 Beijing(CN)
作者
Lu Kuan; Zhao Yan; Wang Xin; Cheng Yan; Pang Xiangkun; Sun Wenxue; Jiang Zhe; Zhang Yong; Xu Nan; Zhao Xin;
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State Grid Shandong Electric Power Research Institute Jinan China;

State Grid Shandong Electric Power Research Institu;

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1. A Short-Term Load Forecasting Method Based on GRU-CNN Hybrid Neural Network Model [J] . Lizhen Wu, Chun Kong, Xiaohong Hao, Mathematical Problems in Engineering: Theory, Methods and Applications . 2020,第1期

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2. Short-term forecasting of natural gas prices by using a novel hybrid method based on a combination of the CEEMDAN-SE-and the PSO-ALS-optimized GRU network [J] . Wang Jun, Cao Junxing, Yuan Shan, Energy . 2021,第Octa15期

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3. Short-term electricity price and load forecasting in isolated power grids based on composite neural network and gravitational search optimization algorithm [J] . Heydari Azim, Nezhad Meysam Majidi, Pirshayan Elmira, Applied Energy . 2020,第Nova1期

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4. Short-term Electricity Load Forecasting Method Based on Multilayered Self-normalizing GRU Network [C] . Lu Kuan, Zhao Yan, Wang Xin, IEEE Conference on Energy Internet and Energy System Integration . 2017

机译：基于多层自归三化GRU网络的短期电力负荷预测方法
5. Neural network-based short-term load forecasting for unit commitment scheduling. [D] . Methaprayoon, Kittipong. 2003

机译：基于神经网络的短期负荷预测，用于机组承诺计划。
6. An Attention-Based Multilayer GRU Model for Multistep-Ahead Short-Term Load Forecasting [O] . Seungmin Jung, Jihoon Moon, Sungwoo Park, 2021

机译：用于多层短期负荷预测的基于关注的多层GRU模型
7. Short-Term Electricity Load Forecasting Model Based on EMD-GRU with Feature Selection [O] . Xin Gao, Xiaobing Li, Bing Zhao, 2019

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8. Neutral network based technique for short-term forecasting of anomalous load periods [R] . Sforna, M. , Lamedica, R. , Prudenzi, A. , 1995

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Short-term electricity load forecasting method based on multilayered self-normalizing GRU network

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