Geometric Optimization of Concentrating Solar Collectors using Monte Carlo Simulation
- 19 August 2010
- journal article
- Published by ASME International in Journal of Solar Energy Engineering
- Vol. 132 (4), 041002
- https://doi.org/10.1115/1.4001674
Abstract
This paper presents an optimization algorithm for designing linear concentrating solar collectors using stochastic programming. A Monte Carlo technique is used to quantify the performance of the collector design in terms of an objective function, which is then minimized using a modified Kiefer–Wolfowitz algorithm that uses sample size and step size controls. This process is more efficient than traditional “trial-and-error” methods and can be applied more generally than techniques based on geometric optics. The method is validated through application to the design of three different configurations of linear concentrating collector.Keywords
This publication has 10 references indexed in Scilit:
- Evaluation of CPC-collector designs for stand-alone, roof- or wall installationSolar Energy, 2005
- Geometric Optimization of Radiant Enclosures Containing Specular SurfacesJournal of Heat Transfer, 2003
- An Algorithm for Gradient-Free Simulation Optimization using Sampling ControlInternational Journal of Modelling and Simulation, 2003
- Optimized reflectors for non-tracking solar collectors with tubular absorbersSolar Energy, 2000
- Radiative heat transfer with quasi-monte carlo methodsTransport Theory and Statistical Physics, 1994
- Edge-ray method for analysis of radiation transfer among specular reflectorsApplied Optics, 1994
- Non-Imaging Optics Design Using Genetic AlgorithmsJournal of the Illuminating Engineering Society, 1994
- On sampling controlled stochastic approximationIEEE Transactions on Automatic Control, 1991
- Stochastic Estimation of the Maximum of a Regression FunctionThe Annals of Mathematical Statistics, 1952
- A Stochastic Approximation MethodThe Annals of Mathematical Statistics, 1951