Medium and Long Term Power Load Forecasting Based on Stacked-GRU

被引：0

作者：

Yang Z. ^{[1
]}

Cui J. ^{[1
]}

Zhang Q. ^{[2
]}

Yin C. ^{[1
]}

Yang L. ^{[1
]}

Qiu P. ^{[1
]}

Hu K. ^{[3
]}

Yang J. ^{[1
]}

机构：

[1] Electric Power Research Institute of Yunnan Power Grid, Kunming

[2] Key Laboratory in Software Engineering of Yunnan Province, School of Software, Yunnan University, Kunming

[3] Yunnan Power Grid Co., Ltd, Kunming

来源：

Strategic Planning for Energy and the Environment | 2022年 / 41卷 / 04期

关键词：

Medium and long term power load forecasting; stacked gated RNN; time series forecasting;

D O I：

10.13052/spee1048-5236.4141

中图分类号：

学科分类号：

摘要：

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. © 2022 River Publishers.

引用

页码：363 / 378

页数：15

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