Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction
Joint Authors
Jin, Shiqiang
Qin, Shanshan
Jiang, Haiyan
Wang, Jianzhou
Source
Mathematical Problems in Engineering
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-09-30
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Abstract EN
Swarm intelligence (SI) is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities.
In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS) as well as the singular spectrum analysis (SSA), time series, and machine learning methods are proposed to conduct short-term power load prediction.
The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon.
The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA) and support vector regression (SVR) in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance.
Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.
American Psychological Association (APA)
Wang, Jianzhou& Jin, Shiqiang& Qin, Shanshan& Jiang, Haiyan. 2014. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction. Mathematical Problems in Engineering،Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1046401
Modern Language Association (MLA)
Wang, Jianzhou…[et al.]. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction. Mathematical Problems in Engineering No. 2014 (2014), pp.1-17.
https://search.emarefa.net/detail/BIM-1046401
American Medical Association (AMA)
Wang, Jianzhou& Jin, Shiqiang& Qin, Shanshan& Jiang, Haiyan. Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction. Mathematical Problems in Engineering. 2014. Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1046401
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1046401