Power Forecasting of Combined Heating and Cooling Systems Based on Chaotic Time Series
Joint Authors
Source
Journal of Control Science and Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-05-12
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Electronic engineering
Information Technology and Computer Science
Abstract EN
Theoretic analysis shows that the output power of the distributed generation system is nonlinear and chaotic.
And it is coupled with the microenvironment meteorological data.
Chaos is an inherent property of nonlinear dynamic system.
A predicator of the output power of the distributed generation system is to establish a nonlinear model of the dynamic system based on real time series in the reconstructed phase space.
Firstly, chaos should be detected and quantified for the intensive studies of nonlinear systems.
If the largest Lyapunov exponent is positive, the dynamical system must be chaotic.
Then, the embedding dimension and the delay time are chosen based on the improved C-C method.
The attractor of chaotic power time series can be reconstructed based on the embedding dimension and delay time in the phase space.
By now, the neural network can be trained based on the training samples, which are observed from the distributed generation system.
The neural network model will approximate the curve of output power adequately.
Experimental results show that the maximum power point of the distributed generation system will be predicted based on the meteorological data.
The system can be controlled effectively based on the prediction.
American Psychological Association (APA)
Hai, Liu& Song, Yong& Qingfu, Du. 2015. Power Forecasting of Combined Heating and Cooling Systems Based on Chaotic Time Series. Journal of Control Science and Engineering،Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1067753
Modern Language Association (MLA)
Hai, Liu…[et al.]. Power Forecasting of Combined Heating and Cooling Systems Based on Chaotic Time Series. Journal of Control Science and Engineering No. 2015 (2015), pp.1-7.
https://search.emarefa.net/detail/BIM-1067753
American Medical Association (AMA)
Hai, Liu& Song, Yong& Qingfu, Du. Power Forecasting of Combined Heating and Cooling Systems Based on Chaotic Time Series. Journal of Control Science and Engineering. 2015. Vol. 2015, no. 2015, pp.1-7.
https://search.emarefa.net/detail/BIM-1067753
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1067753