Cheng, S.;
(2009)
Curved photovoltaic surface optimization for BIPV: an
evolutionary approach based on solar radiation simulation.
Masters thesis , UCL (University College London).
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Abstract
The paper attempts to address the problem of the optimization of curved photovoltaic surfaces that may become the alternatives of the traditional flat PV surfaces in BIPV. The proposed method combines three parts: an evolutionary algorithm (Genetic Algorithm) for optimization, an adaptive simulation tool based on Hay’s anisotropic radiation model, and a comparison module for analysis. The cladding problem of curved PV modules is geometrically solved that may serve as the starting point for practical links with architectural and PV engineering considerations. A systematical approach is established for the comparisons between the curved and flat surfaces according to various surface angle-settings (tilt angle and azimuth angle) and solar condition setups (latitude and radiation mode), involving specific 3D and 2D radiation plots and related data recording system. Through a series of experiments, the paper presents the characteristics of curved surfaces in terms of the solar energy gain, such as the stabilization characteristic and the mean total annual solar radiation, etc. The capacities of the algorithm are confirmed and several findings are discussed and concluded so as to be used as references for BIPV projects and other practical photovoltaic appliances.
Type: | Thesis (Masters) |
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Title: | Curved photovoltaic surface optimization for BIPV: an evolutionary approach based on solar radiation simulation |
Open access status: | An open access version is available from UCL Discovery |
Language: | English |
Additional information: | Approved for UCL Eprints by Mr A. Turner, The Bartlett School of Graduate Studies |
Keywords: | Curved photovoltaic surface, BIPV, Genetic Algorithm, Hay’s anisotropic radiation model, cladding, tilt angle, azimuth angle, latitude, radiation mode, 3D and 2D radiation plots |
UCL classification: | |
URI: | https://discovery.ucl.ac.uk/id/eprint/18982 |
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