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A novel stochastic energy analysis of a solar air heater: case study in solar radiation uncertainty

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Abstract

There is a growing recognition of the fact that solar energy utilization plans cannot be carried out without explicitly accounting for the uncertainty presented in the received solar irradiation. This may be expressed as an uncertainty quantification problem. A novel stochastic energy analysis is introduced to study the transient heat transfer problem of a typical flat plate solar air heater, based on the polynomial chaos expansion approach. The constructed model was equipped with the numerical finite difference method and the Galerkin projection scheme in the random space. The numerical model was verified against the available exact analytical solutions. The results of polynomial chaos method was compared to corresponding basic Monte Carlo sampling results. Finally, a case study with realistic solar irradiance data of Urmia, a cold climate city in Iran, was conducted for a typical solar air heater. Afterward, the outlet temperature of the air heater was tracked in a probabilistic framework, to find the reliable hours for extracting solar energy stably during a typical summery day. These hours were found between 11 am to 5 pm.The proposed approach could be highly worthwhile in the designing and contriving control plans taking into consideration the non-negligible uncertainty of solar radiation.

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Abbreviations

\({{\varvec{x}}}\) :

Distance from collector inlet (m)

\(\Delta {{\varvec{x}}}\) :

mesh length in numerical solution (m)

\({{\varvec{L}}}\) :

Length of collector (m)

\({{\varvec{X}}}\) :

Dimensionless distance from collector’s inlet \(\left( X=\frac{x}{L}\right) \)

\({{\varvec{W}}}\) :

Width of collector (m)

\({{\varvec{t}}}\) :

time started from sunrise (h)

\(\Delta {{\varvec{t}}}\) :

Time step in numerical solution (h)

\( \bar{t} \) :

\( \bar{t} = \left\{ {\begin{array}{*{20}l} {0,} &{} {\quad t \le t_{{ss}} } \\ {t - t_{{ss}} ,} &{} {\quad t > t_{{ss}} } \\ \end{array} } \right. \)

\({{\varvec{I}}}\) :

Solar irradiance (W/m2)

\({{\varvec{I}}}_{max}\) :

Maximum solar irradiance during a day (W/m\(^2\))

\(\mathbb {E}\) :

First statistical moment (mean)

\(\mathbb {VAR}\) :

Second central statistical moment (variance)

\({{\varvec{N}}}( {-\infty ,+\infty } )\) :

Normal distribution

\({{\varvec{z}}}\) :

Independent variable defined in Eq. 4

\({{\varvec{y}}}\) :

Independent variable defined in Eq. 4

\({\varvec{\mu }}\) :

Summation numerator in Eq. 4

\({{\varvec{r}}}\) :

Summation numerator in Eq. 4

\({\varvec{\delta }} \) :

Kronecker delta

\({{\varvec{n}}}\) :

Order of \(R_{\left( t \right) } \) polynomial representation

\({\varvec{\theta }} \) :

weighting coefficient of Crank–Nicholson backward difference scheme in Eq. 6

\({{\varvec{j}}}\) :

Time mesh superscript in numerical solution

\({{\varvec{i}}}\) :

Space mesh subscript in numerical solution

\({{\varvec{n}}}_{{\varvec{{i}}}} \) :

Number of space mesh in numerical solution

\({{\varvec{n}}}_{{\varvec{{j}}}} \) :

Number of timesteps in numerical solution

\({\upxi }\) :

Random outcome with normal distribution which can take values between \(-\infty \) and \(+\infty \).

\({{\varvec{R}}}\) :

Solar irradiance intensity ratio (dimensionless)

\({{\varvec{R}}}_{{\varvec{{( t )}}}} \) :

Solar irradiance intensity ratio as a function of time \(R_{\left( t \right) } =\left\{ {\begin{array}{*{20}l} {\sum \nolimits _{{k = 0}}^{n} {a_{k} } t^{k} ,} &{} {\quad 0 \le t \le t_{{ss}} } \\ {0,} &{} {\quad t > t_{{ss}} } \\ \end{array} } \right. \)

\(\mathbf{R}_{( \mathbf{t};{\upxi } )} \) :

Uncertain solar irradiance Intensity Ratio

\({\varvec{\tau }}\) :

Temperature (C)

\({{\varvec{T}}}\) :

Dimensionless temperature

\({{\varvec{U}}}\) :

the overall collector heat loss coefficient (W/m2C)

\({{\varvec{c}}}_{{\varvec{p}}} \) :

Absorbing plate specific heat (J/kgC)

\({{\varvec{c}}}_{{\varvec{f}}} \) :

fluid (blowing air) specific heat (J/kgC)

\(\dot{{\varvec{m}}}\) :

Air mass flow rate (kg/s)

\({{\varvec{m}}}_{{\varvec{p}}} \) :

mass of plate per unit length (kg/m)

\({{\varvec{N}}}_{{\varvec{C}}} \) :

Convection number

\({{\varvec{N}}}_{{\varvec{L}}} \) :

Heat loss number

\({\varvec{\gamma }}\) :

\(\gamma =UW/m_p c_p \)

\({{\varvec{I}}}_0 \) :

First order Bessel function

\({{\varvec{w}}}_{( {\varvec{\xi }} )} \) :

weighting function of normal distribution \(w_{\left( \xi \right) } =\frac{1}{\sqrt{2\pi }}e^{-\frac{\xi ^{2}}{2}}\)

\({{\varvec{H}}}_{( {\varvec{\xi }} )}^{\varvec{\kappa }} \) :

Hermite polynomials of \(\kappa \)-th order (Table 2)

\({\varvec{\iota }} \) :

Order of Hermite polynomials

\({\varvec{\kappa }} \) :

Order of Hermite polynomials

\({{\varvec{P}}}\) :

Parameter defined in Eq. 13

\({\varvec{\epsilon }}\) :

Number of random dimensions (defined in Eq. 13)

\({{\varvec{d}}}\) :

The highest degree of polynomial (defined in Eq. 13)

\( \hat{{\varvec{T}}}_{{\varvec{f}}}^{*} \) :

Dimensionless outlet temperature at noon

\({{\varvec{T}}}_{{\varvec{f}}}^*\) :

Dimensionless outlet temperature

\(\mathbf{p}\) :

Absorbing plate

\(\mathbf{f}\) :

Agent fluid (blowing air)

\(\mathbf{am}\) :

Ambient

ss :

Sunset

\({{\varvec{x}}}\) :

Along collector length

FPSAH:

Flat plate solar air heaters

PCE:

Polynomial chaos method

MCS:

Monte Carlo method

PDF:

Probability density functions

SII:

Solar irradiance intensity

FD:

Finite difference

CTC:

Collector time constant

PDE:

Partial differential equation

References

  1. Myers, D.R.: Solar radiation modeling and measurements for renewable energy applications: data and model quality. Energy. 30, 1517–1531 (2005)

    Article  Google Scholar 

  2. Marcel, S., Thomas, H., Ewan, D., Michel, A., Mireille, L., Lucien, W.: Uncertainties in solar electricity yield prediction from fluctuation of solar radiation. In: Proc. 22nd Eur. Photovolt. Sol. Energy Conf. 2007, 1985–1990 (2007)

  3. Saxena, A., El-sebaii, A.A.: A thermodynamic review of solar air heaters. Renew. Sustain. Energy Rev. 43, 863–890 (2015)

    Article  Google Scholar 

  4. Tyagi, V.V., Panwar, N.L., Rahim, N.A., Kothari, R.: Review on solar air heating system with and without thermal energy storage system. Renew. Sustain. Energy Rev. 16, 2289–2303 (2012)

    Article  Google Scholar 

  5. Tagliafico, L.A., Scarpa, F., De Rosa, M.: Dynamic thermal models and CFD analysis for flat-plate thermal solar collectors—a review. Renew. Sustain. Energy Rev. 30, 526–537 (2014)

    Article  Google Scholar 

  6. Chandra, R., Sodha, M.S.: Testing procedures for solar air heaters: a review. Energy Convers. Manag. 32, 11–33 (1991)

    Article  Google Scholar 

  7. Ekechukwu, O., Norton, B.: Review of solar energy drying systems II: an overview of solar drying technology. Energy Convers. Manag. 40, 615–655 (1999)

    Article  Google Scholar 

  8. Ekechukwu, O.V., Norton, B.: Review of solar energy drying systems III: low temperature air-heating solar collectors for crop drying applications. Energy Convers. Manag. 40, 657–667 (1999)

    Article  Google Scholar 

  9. Tchinda, R.: A review of the mathematical models for predicting solar air heaters systems. Renew. Sustain. Energy Rev. 13, 1734–1759 (2009)

    Article  Google Scholar 

  10. Deng, J., Xu, Y., Yang, X.: A dynamic thermal performance model for fl at-plate solar collectors based on the thermal inertia correction of the steady-state test method. Renew. Energy76, 679–686 (2015)

  11. El-Refaie, M.F., Hashish, M.A.: Temperature distributions in the flat-plate collector under actual unsteady insolation. Appl. Math. Model. 4, 181–186 (1980)

    Article  Google Scholar 

  12. Grine, A., Radjouh, A., Harmand, S.: Analytical modelling using Green’s functions of heat transfer in a flat solar air collector. Sol. Energy. 105, 760–769 (2014)

    Article  Google Scholar 

  13. Ammari, H.D.: A mathematical model of thermal performance of a solar air heater with slats. Renew. Energy 28, 1597–1615 (2003)

    Article  Google Scholar 

  14. Hernández, A.L., Quiñonez, J.E.: Analytical models of thermal performance of solar air heaters of double-parallel flow and double-pass counter flow. Renew. Energy 55, 380–391 (2013)

    Article  Google Scholar 

  15. Ong, K.S.: Thermal performance of solar air heaters: mathematical model and solution procedure. Sol. Energy 55, 93–109 (1995)

    Article  Google Scholar 

  16. Forson, F.K., Nazha, M.A.A., Rajakaruna, H.: Experimental and simulation studies on a single pass, double duct solar air-heater. Energy Convers. Manage. 44, 1209–1227 (2003)

  17. Baritto, M., Bracamonte, J.: A dimensionless model for the outlet temperature of a nonisothermal flat plate solar collector for air heating. Sol. Energy. 86, 647–653 (2012)

    Article  Google Scholar 

  18. Ghanem, R.G., Spanos, P.D.: Stochastic Finite Elements: A Spectral Approach. Springer, New York (1991)

    Book  MATH  Google Scholar 

  19. Xiu, D., Karniadakis, G.E.: The Wiener–Askey polynomial chaos for stochastic differential equations. SIAM J. Sci. Comput. 24, 619–644 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  20. Sandu, A., Sandu, C., Ahmadian, M.: Modeling multibody systems with uncertainties. Part I: Theoretical and computational aspects. Multibody Syst. Dyn. 15, 369–391 (2006)

    Article  MATH  Google Scholar 

  21. Sandu, A., Sandu, C., Ahmadian, M.: Modeling multibody dynamic systems with uncertainties. Part II: Numerical applications two degree of freedom vehicle suspension model. Multibody Syst. Dyn. 15, 241–262 (2006)

    Article  MATH  Google Scholar 

  22. Xiu, D., Em Karniadakis, G.: Modeling uncertainty in steady state diffusion problems via generalized polynomial chaos. Comput. Methods Appl. Mech. Eng. 191, 4927–4948 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  23. Xiu, D., Karniadakis, G.E.: A new stochastic approach to transient heat conduction modeling with uncertainty. Int. J. Heat Mass Transf. 46, 4681–4693 (2003)

    Article  MATH  Google Scholar 

  24. Constantine, P.G., Doostan, A., Iaccarino, G.: A hybrid collocation / Galerkin scheme for convective heat transfer problems with stochastic boundary conditions. Int. J. Numer. Meth. Engng. 80, 868–880 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  25. Abedi, S., Riahy, G.H., Hosseinian, S.H., Farhadkhani, M.: Improved stochastic modeling: an essential tool for power system scheduling in the presence of uncertain renewables. In: Arman, H., Yuksel, I. (eds.) New Developments in Renewable Energy (2013). https://doi.org/10.5772/52161

  26. Colle, S., Abreu, S.L.D.E., Ruther, R.: Uncertainty in economical analysis of solar water heating and photovoltaic systems. Fuel Energy Abstr. 43, 124 (2002)

    Google Scholar 

  27. LeVeque, R.: Finite difference methods for ordinary and partial differential equations: steady-state and time-dependent problems. Society for Industrial and Applied Mathematics (2007). https://doi.org/10.1137/1.9780898717839

  28. Chantrasmi, T., Iaccarino, G.: Computing shock interactions under uncertainty. AIAA Pap. 2009–2284, 1–14 (2009)

  29. Loève, M.: Probability Theory I. Springer, New York (1977)

    MATH  Google Scholar 

  30. Sandu, C., Sandu, A., Li, L.: Stochastic modeling of terrain profiles and soil parameters. SAE Technical Paper 2005-01-3559, (2005). https://doi.org/10.4271/2005-01-3559

  31. Fishman, G.: Coordinate selection rules for Gibbs sampling. Ann. Appl. Probab. 6, 444–465 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  32. Duffie, J., Beckman, W.: Solar Engineering of Thermal Processes. Wiley, New York (2013)

  33. SOLARGIS: GHI Solar Map2017Solargis. http://solargis.com/products/maps-and-gis-data/free/download/iran. Accessed March 1 2017

  34. Spark Weather.: Weather in Urmia, Iran. https://weatherspark.com. Accessed 1 March 2017

  35. Iran Meteorological Organization (IRIMO). http://www.irimo.ir. Accessed 1 June 2016

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Sarnavi, H.J., Nikbakht, A.M., Hasanpour, A. et al. A novel stochastic energy analysis of a solar air heater: case study in solar radiation uncertainty. Energy Syst 10, 141–161 (2019). https://doi.org/10.1007/s12667-017-0263-7

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  • DOI: https://doi.org/10.1007/s12667-017-0263-7

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