A Novel Combined Model for Short-Term Electric Load Forecasting Based on Whale Optimization Algorithm

Zhihao Shang; Zhaoshuang He; Yanru Song; Yi Yang; Lian Li; Yanhua Chen

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A Novel Combined Model for Short-Term Electric Load Forecasting Based on Whale Optimization Algorithm

机译：基于鲸鲸优化算法的短期电负载预测组合模型

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摘要

Stable electric load forecasting plays a significant role in power system operation and grid management. Improving the accuracy of electric load forecasting is not only a hot topic for energy managers and researchers of the power system, but also a fair challenging and difficult task due to its complex nonlinearity characteristics. This paper proposes a new combination model, which uses the least squares support vector machine, extreme learning machine, and generalized regression neural network to predict the electric load in New South Wales, Australia. In addition, the model employs a heuristic algorithm-whale optimization algorithm to optimize the weight coefficient. To verify the usability and generalization ability of the model, this paper also applies the proposed combined model to electricity price forecasting and compares it with the benchmark method. The experimental results demonstrate that the combined model not only can get accurate results for short-term electric load forecasting, but also achieves fine accuracy for the same period of electricity price forecasting.

机译：稳定的电负载预测在电力系统运行和电网管理中起着重要作用。提高电负荷预测的准确性不仅是能源经理和电力系统研究人员的热门话题，而且由于其复杂的非线性特征，也是一个公平的具挑战性和艰巨的任务。本文提出了一种新的组合模型，它使用最小二乘支持向量机，极端学习机和广义回归神经网络来预测澳大利亚新南威尔士州的电负荷。此外，该模型采用启发式算法鲸鲸优化算法来优化权重系数。为了验证模型的可用性和泛化能力，本文还将所提出的组合模型应用于电价预测，并将其与基准方法进行比较。实验结果表明，联合模型不仅可以获得短期电负荷预测的准确结果，而且还可以实现相同的电价预测时期的精确度。

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来源
《Neural processing letters》 |2020年第2期|1207-1232|共26页
作者
Zhihao Shang; Zhaoshuang He; Yanru Song; Yi Yang; Lian Li; Yanhua Chen;
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作者单位

School of Information Engineering Zhengzhou University Zhengzhou 450000 People's Republic of China;

School of Information Science and Engineering Lanzhou University Lanzhou 730000 People's Republic of China;

School of Information Science and Engineering Lanzhou University Lanzhou 730000 People's Republic of China;

School of Information Science and Engineering Lanzhou University Lanzhou 730000 People's Republic of China;

School of Information Science and Engineering Lanzhou University Lanzhou 730000 People's Republic of China;

School of Information Engineering Zhengzhou University Zhengzhou 450000 People's Republic of China;

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正文语种 eng
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Short-term electric load forecasting; Electricity price forecasting; LSSVM; ELM; GRNN; WOA;

机译：短期电负荷预测;电价预测;LSSVM;榆树;grnn;WOA.;

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1. A novel combined model based on hybrid optimization algorithm for electrical load forecasting [J] . Wang Rui, Wang Jiyang, Xu Yunzhen Applied Soft Computing . 2019,第期

机译：一种基于混合优化算法的电负荷预测的新型组合模型
2. A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with Bayesian optimization algorithm [J] . He Feifei, Zhou Jianzhong, Feng Zhong-kai, Applied Energy . 2019,第MARa1期

机译：贝叶斯优化算法基于变分模式分解和考虑相关因素的长短期记忆网络的混合短期负荷预测模型
3. Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model [J] . H.M. Al-Hamadi, S.A. Soliman Electric power systems research . 2004,第1期

机译：基于移动窗天气和负荷模型的基于卡尔曼滤波算法的短期电力负荷预测
4. A Combined Model Based on Neural Networks, LSSVM and Weight Coefficients Optimization for Short-Term Electric Load Forecasting [C] . Caihong Li, Zhaoshuang He, Yachen Wang Web-age information management . 2016

机译：基于神经网络，LSSVM和权重优化的组合模型用于短期电力负荷预测
5. Short-term electric load forecasting using neural network with fuzzy set based classification. [D] . Bumroonggit, Gumpanart. 1995

机译：使用基于模糊集的神经网络对电力负荷进行短期预测。
6. Forecasting Short-Term Traffic Flow by Fuzzy Wavelet Neural Network with Parameters Optimized by Biogeography-Based Optimization Algorithm [O] . Jeng-Fung Chen, Shih-Kuei Lo, Quang Hung Do 2018

机译：基于生物地理优化算法的模糊小波神经网络预测短期交通流量
7. The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection [O] . Jin-peng Liu, Chang-ling Li 2017

机译：基于抹香鲸算法和DWT-IR小波最小二乘支持向量机的特征选择短期电力负荷预测

A Novel Combined Model for Short-Term Electric Load Forecasting Based on Whale Optimization Algorithm

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