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

Yi-Shian Lee¹ 

[1] Research Center for Psychological and Educational Testing, National Taiwan Normal University, HePing East Rd., Section 1, Taipei 106, Taiwan

关键词: photovoltaic systems;    rough set theory;    data envelopment analysis;    genetic programming;    hybrid model;   

DOI  :  10.3390/en5030545

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2012 by the authors; licensee MDPI, Basel, Switzerland.