Regression analysis to design a solar thermal collector for occasional use

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Abstract

Optimal design of a solar thermal system is necessary to minimize payback time and to diffuse renewable energy use for Domestic Hot Water production in residential areas. More accurate design is crucial in the case of seasonal or occasional use of the system; indeed, the standard criteria generally applied to a design system for continuous use, can lead to considerable over-sizing. To speed up the design phase and to help the planner in the identification of the best solution without any complex evaluation or long computational time, it would be interesting to have available a simpler method than the standard procedures, but one that is reliable and accurate for the evaluation of the best configuration, taking into account occasional use, seasonal and monthly domestic hot water demand, orientation and primary flow rate. To this end, the authors investigated a methodology for the identification of some empirical correlations based on the analysis of data coming from a parametric simulation; in this way the identified correlations can indicate, with high reliability, the optimal design knowing only well-known parameters. In detail, the data output was extracted and processed to evaluate the best design configurations under any operative conditions. Determination of the best configuration identifies the operative parameters that maximize the Solar Fraction of the plant and minimize the auxiliary energy. To highlight the reliability of this methodology, in this work, the authors describe a case study of the Sicilian region proposing a set of simple, reliable correlations that allow the determination of the best tilt angle for monthly or seasonal use. Following the same steps the procedure can be replicate in any context and in any conditions.
Lingua originaleEnglish
Numero di pagine20
RivistaSustainable Energy Technologies and Assessments
Volume37
Stato di pubblicazionePublished - 2020

All Science Journal Classification (ASJC) codes

  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology

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