Optimal Planning for Photovoltaic System Using a New Heuristic Method

Jeeng Min Ling; Anh Son Khuong

doi:10.4028/www.scientific.net/AMR.512-515.119

Paper Titles

Modeling and Simulation of MPPT for Photovoltaic (PV) Array under Partially Shaded Conditions
p.97

Modeling and Thermal Performance Analysis of Parabolic trough Solar Field with Single-Axis Tracked
p.101

Nickle Oxide Based Bulk Heterojunction Flexible Solar Cells
p.109

Online Electrovalency Formulating and Influence Factors Analysing of Photovoltaic Generation
p.113

Optimal Planning for Photovoltaic System Using a New Heuristic Method
p.119

Performance Analysis of Humidifying Dehumidifying Solar Desalination Unit
p.124

Performance Evaluation of a Solar Water Heating System for Industrial Application
p.130

Performance of the Grid-Connected PV System in LV Microgrid Operation
p.137

Relationship between the Solar Radiation and Surface Temperature in Perlis
p.143

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 512-515Optimal Planning for Photovoltaic System Using a...

Optimal Planning for Photovoltaic System Using a New Heuristic Method

Abstract:

This paper presents an efficient and reliable evolutionary-based approach to solve the Optimal Planning of Photovoltaic (OPPV) system problem by considering the reliability requirement and economical performance. The shuffled frog leaping algorithm (SFLA) is a powerful approach for complex optimization problem, but its performance relies strongly on suitable model parameters. The proposed improved SFLA (ISFLA) shows explicit strategy to select proper values of parameters and improves local exploration to avoid being trapped in local optimal. Simulation results show that the ISFLA performs better compared with conventional SFLA and a simple genetic algorithm (GA).

You might also be interested in these eBooks

Solar Energy: Engineering of Solar Energy Systems

View Preview

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 512-515)

Pages:

119-123

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.512-515.119

Citation:

Cite this paper

Online since:

May 2012

Authors:

Jeeng Min Ling, Anh Son Khuong

Keywords:

Genetic Algorithm (GA), Improved Shuffled Frog Leaping Algorithm, Photovoltaic Generation Planning, Reliability

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] M. M. Eusuff and K.E. Lansey. Optimization of water distribution network design using the shuffled frog leaping algorithm. Journal of Water Resources Planning and Management. Vol. 129, No. 3 (2003), pp.210-225.

DOI: 10.1061/(asce)0733-9496(2003)129:3(210)

Google Scholar

[2] J. Ebrahimi., S.H. Hosseinian, and G, B. Gharehpetian. Unit Commitment problem Solution Using Shuffled frog-leaping algorithm. IEEE Trans. on Power System, Vol. 26, No.2, pp.573-58.

DOI: 10.1109/tpwrs.2010.2052639

Google Scholar

[3] M. M. Eusuff, K. Lansey, and F. Pasha. Shuffled frog-leaping algorithm: a memetic meta-heuristic for discrete optimization. Engineering Optimization. Vol.38 (2006), pp.129-154.

DOI: 10.1080/03052150500384759

Google Scholar

[4] E. Elbeltagi, T. Hegazy and D. Grienson. A modified shuffled frog-leaping optimization algorithm: applications to project management. Structure and Infrastructure. Vol. 3, No. 1 (2007), pp.53-60.

DOI: 10.1080/15732470500254535

Google Scholar

[5] P. Arun, R. Banerjee and S. Bandyopadhyay. Optimal sizing of photovoltaic battery systems incorporating uncertainty through design space approach. Solar Energy. Vol.83, issue 7 (2009), pp.1013-1025.

DOI: 10.1016/j.solener.2009.01.003

Google Scholar

[6] The Central Weather Bureau of Taiwan, http://www.cwb.gov.tw

Google Scholar