| 引用本文: | 殷豪,曾云,孟安波,刘哲.基于奇异谱分析的短期电价预测[J].电力系统保护与控制,2019,47(1):115-122.[点击复制] |
| YIN Hao,ZENG Yun,MENG Anbo,LIU Zhe.Short-term electricity price forecasting based on singular spectrum analysis[J].Power System Protection and Control,2019,47(1):115-122[点击复制] |
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| 摘要: |
| 针对电价序列具有非线性和非平稳性的特点，提出了一种基于奇异谱分析(SSA)和改进布谷鸟算法(ICS)优化极限学习机(ELM)的短期电价预测模型。采用奇异谱分析提取电价序列中的趋势成分和振荡成分，进行准周期信号分量重建，并对重建序列进行ELM建模预测。针对ELM预测模型中的参数易陷入局部最优的问题，为了提高预测精度，提出改进布谷鸟算法优化预测模型的参数。最后将所有预测序列进行叠加，得到最终的电价预测值。以澳大利亚某电力市场电价数据为例进行分析，通过与其他几种预测模型相比，表明SSA-ICS-ELM模型能有效提高电价预测的精度和稳定性。 |
| 关键词: 奇异谱分析 改进布谷鸟算法 极限学习机 SSA-ICS-ELM模型 电价预测 |
| DOI：10.7667/PSPC171898 |
| 投稿时间：2017-12-30修订日期：2018-03-01 |
| 基金项目:广东省科技计划项目资助(2016A010104016);广东电网公司科技项目资助(GDKJQQ20152066) |
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| Short-term electricity price forecasting based on singular spectrum analysis |
| YIN Hao,ZENG Yun,MENG Anbo,LIU Zhe |
| (Guangdong University of Technology, Guangzhou 510006, China) |
| Abstract: |
| In view of the nonlinear and non-stationary characteristics of electricity price time series, the novel model for electricity price forecasting in this paper is proposed by the combination of Singular Spectrum Analysis (SSA) and Extreme Learning Machine (ELM) optimized by the Improved Cuckoo Search algorithm (ICS). SSA is used to extract the trend components and oscillation components of the original data and reconstruct all the components, and the ELM model is used to predict the reconstruction sequences. Against the parameters that in the ELM prediction model tend to fall into the local optimum, the ICS algorithm is introduced to optimize the model parameters to further improve the predictive value. Finally, all the predicted sequences are summed up to get the final forecast of electricity price. The empirical results demonstrate that the SSA-ICS-ELM model can improve the prediction accuracy and stability of electricity price forecasting considerably in comparison with other methods by analyzing the price data in Australia electricity market. This work is supported by Science and Technology Project of Guangdong Province (No. 2016A010104016) and Science and Technology Project of Guangdong Power Grid Company (No. GDKJQQ20152066). |
| Key words: SSA ICS algorithm ELM SSA-ICS-ELM model electricity price forecasting |
