基于堆积GRU的中长期电力负荷预测

Q3 Environmental Science
Zheng Yang, Jing Cui, Qiangjian Zhang, Chunli Yin, Li Yang, Pengfeng Qiu, Kai Hu, Junwen Yang
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引用次数: 0

摘要

电力负荷预测在电力系统的能源经济发展和配电中起着至关重要的作用。预测中长期电力负荷促进了电网的发展。本文应用堆叠门控递归单元(stacked GRU),通过综合经济因素,建立了电力负荷预测模型。同时,根据云南省2009-2010年的电力负荷数据,进行了中长期电力负荷预测。通过比较不同的优化器,发现Adam优化器在Stacked GRU架构上工作得最好。在云南省中长期电力负荷预测实验中,该模型的MAPE、RMSE和MAE值分别为9.76%、1.412和1.14,均优于其他深度学习比较算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medium and Long Term Power Load Forecasting Based on Stacked-GRU
Power load forecasting plays a critical role in energy economy development and distribution of power systems. Predicting medium and long term power loads have facilitated the development of power grids. In this paper, a stacked-gated recurrent unit (Stacked-GRU) is applied to establish a power load forecasting model by integrating economic factors. Meanwhile, it also conducts medium and long term power load (MLTPL) forecasting based on the power load data of Yunnan Province from 2009 to 2020. By comparing different optimizers, it is found that the Adam optimizer works the best on the Stacked-GRU architecture. In the experiment of medium and long term power load forecasting for Yunnan Province, the values of MAPE, RMSE, and MAE of the model are 9.76%, 1.412, and 1.14, respectively, all of which outperform other deep learning comparison algorithms.
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来源期刊
Strategic Planning for Energy and the Environment
Strategic Planning for Energy and the Environment Environmental Science-Environmental Science (all)
CiteScore
1.50
自引率
0.00%
发文量
25
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