Energies 2012, 5(3), 545-560; doi:10.3390/en5030545
Article

Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

1 Research Center for Psychological and Educational Testing, National Taiwan Normal University, HePing East Rd., Section 1, Taipei 106, Taiwan 2 Department of Industrial Engineering Management, National Chiao Tung University, 1001 Ta-Hsuch Rd., Hsunchu 300, Taiwan
* Author to whom correspondence should be addressed.
Received: 24 January 2012; in revised form: 13 February 2012 / Accepted: 20 February 2012 / Published: 27 February 2012
PDF Full-text Download PDF Full-Text [274 KB, uploaded 27 February 2012 14:43 CET]
Abstract: Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV) system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST), data envelopment analysis (DEA), and genetic programming (GP). Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.
Keywords: photovoltaic systems; rough set theory; data envelopment analysis; genetic programming; hybrid model

Article Statistics

Load and display the download statistics.

Citations to this Article

Cite This Article

MDPI and ACS Style

Lee, Y.-S.; Tong, L.-I. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming. Energies 2012, 5, 545-560.

AMA Style

Lee Y-S, Tong L-I. Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming. Energies. 2012; 5(3):545-560.

Chicago/Turabian Style

Lee, Yi-Shian; Tong, Lee-Ing. 2012. "Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming." Energies 5, no. 3: 545-560.

Energies EISSN 1996-1073 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert