Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation

This thesis is a study of the geometric design of solar concentrating collectors. In this work, a numerical optimization methodology was developed and applied to various problems in linear solar concentrator design, in order to examine overall optimization success as well as the effect of various s...

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Main Author: Marston, Andrew James
Language:en
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10012/5589
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spelling ndltd-LACETR-oai-collectionscanada.gc.ca-OWTU.10012-55892013-10-04T04:10:13ZMarston, Andrew James2010-10-01T20:39:11Z2010-10-01T20:39:11Z2010-10-01T20:39:11Z2010http://hdl.handle.net/10012/5589This thesis is a study of the geometric design of solar concentrating collectors. In this work, a numerical optimization methodology was developed and applied to various problems in linear solar concentrator design, in order to examine overall optimization success as well as the effect of various strategies for improving computational efficiency. Optimization is performed with the goal of identifying the concentrator geometry that results in the greatest fraction of incoming solar radiation absorbed at the receiver surface, for a given collector configuration. Surfaces are parametrically represented in two-dimensions, and objective function evaluations are performed using various Monte Carlo ray-tracing techniques. Design optimization is performed using a gradient-based search scheme, with the gradient approximated through finite-difference estimation and updates based on the direction of steepest-descent. The developed geometric optimization methodology was found to perform with mixed success for the given test problems. In general, in every case a significant improvement in performance was achieved over that of the initial design guess, however, in certain cases, the quality of the identified optimal geometry depended on the quality of the initial guess. It was found that, through the use of randomized quasi-Monte Carlo, instead of traditional Monte Carlo, overall computational time to converge is reduced significantly, with times typically reduced by a factor of four to six for problems assuming perfect optics, and by a factor of about 2.5 for problems assuming realistic optical properties. It was concluded that the application of numerical optimization to the design of solar concentrating collectors merits additional research, especially given the improvements possible through quasi-Monte Carlo techniques.enNumerical OptimizationMonte Carlo methodsSolar EnergySolar Concentrationstochastic programmingGeometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo SimulationThesis or DissertationMechanical and Mechatronics EngineeringMaster of Applied ScienceMechanical Engineering
collection NDLTD
language en
sources NDLTD
topic Numerical Optimization
Monte Carlo methods
Solar Energy
Solar Concentration
stochastic programming
Mechanical Engineering
spellingShingle Numerical Optimization
Monte Carlo methods
Solar Energy
Solar Concentration
stochastic programming
Mechanical Engineering
Marston, Andrew James
Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation
description This thesis is a study of the geometric design of solar concentrating collectors. In this work, a numerical optimization methodology was developed and applied to various problems in linear solar concentrator design, in order to examine overall optimization success as well as the effect of various strategies for improving computational efficiency. Optimization is performed with the goal of identifying the concentrator geometry that results in the greatest fraction of incoming solar radiation absorbed at the receiver surface, for a given collector configuration. Surfaces are parametrically represented in two-dimensions, and objective function evaluations are performed using various Monte Carlo ray-tracing techniques. Design optimization is performed using a gradient-based search scheme, with the gradient approximated through finite-difference estimation and updates based on the direction of steepest-descent. The developed geometric optimization methodology was found to perform with mixed success for the given test problems. In general, in every case a significant improvement in performance was achieved over that of the initial design guess, however, in certain cases, the quality of the identified optimal geometry depended on the quality of the initial guess. It was found that, through the use of randomized quasi-Monte Carlo, instead of traditional Monte Carlo, overall computational time to converge is reduced significantly, with times typically reduced by a factor of four to six for problems assuming perfect optics, and by a factor of about 2.5 for problems assuming realistic optical properties. It was concluded that the application of numerical optimization to the design of solar concentrating collectors merits additional research, especially given the improvements possible through quasi-Monte Carlo techniques.
author Marston, Andrew James
author_facet Marston, Andrew James
author_sort Marston, Andrew James
title Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation
title_short Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation
title_full Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation
title_fullStr Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation
title_full_unstemmed Geometric Optimization of Solar Concentrating Collectors using Quasi-Monte Carlo Simulation
title_sort geometric optimization of solar concentrating collectors using quasi-monte carlo simulation
publishDate 2010
url http://hdl.handle.net/10012/5589
work_keys_str_mv AT marstonandrewjames geometricoptimizationofsolarconcentratingcollectorsusingquasimontecarlosimulation
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