Effect of different load profiles on the loss-of-load probability of stand-alone photovoltaic systems

As well as the technical design criteria, the performance of a stand-alone photovoltaic (PV) system depends on other variables, such as the solar radiation distribution and load profile. Different load profiles are encountered in stand-alone PV applications. Load profiles may vary from 24-h constant to only nighttime or oppositely only daytime load profiles. This article presents results of system performance simulations for analysing the effect of different load profiles on the system performance. The load demand used in this article is appropriate for an average residential application with an average 9.4kWh of daily energy demand. The loss-of-load probability (LLP) of the PV system is simulated for five different weekly load profiles and the results are examined based on techno-economic parameters, including the total system cost or alternatively the cost of electricity per kWh for a 20-year system lifetime. The results are drawn based on 1-year long hourly time-series solar radiation and ambient temperature data.

[1]  Sanford Klein,et al.  Loss-of-load probabilities for stand-alone photovoltaic systems , 1987 .

[2]  Richard N. Chapman.  Development of sizing nomograms for stand-alone photovoltaic/storage systems☆ , 1987 .

[3]  Kame Khouzam,et al.  The load matching approach to sizing photovoltaic systems with short-term energy storage , 1994 .

[4]  Louis L. Bucciarelli,et al.  Estimating loss-of-power probabilities of stand-alone photovoltaic solar energy systems , 1984 .

[5]  J. M. Gordon,et al.  Optimal sizing of stand-alone photovoltaic solar power systems , 1987 .

[6]  A. Hunter Fanney,et al.  BUILDING INTEGRATED PHOTOVOLTAIC TEST FACILITY , 2000 .

[7]  A. Hadj Arab,et al.  Photovoltaic systems sizing for Algeria , 1995 .

[8]  B. J. Brinkworth,et al.  Battery state of voltage modelling and an algorithm describing dynamic conditions for long-term storage simulation in a renewable system , 1994 .

[9]  G. C. Bakos,et al.  Techno-economic assessment of a stand-alone PV/hybrid installation for low-cost electrification of a tourist resort in Greece , 2002 .

[10]  Bin Ai,et al.  Computer-aided design of PV/wind hybrid system , 2003 .

[11]  Lin Lu,et al.  Weather data and probability analysis of hybrid photovoltaic–wind power generation systems in Hong Kong , 2003 .

[12]  H.M.S. Hussein,et al.  Theoretical analysis and experimental verification of PV modules , 2003 .

[13]  W. Beckman,et al.  A method for estimating the long-term performance of direct-coupled PV pumping systems , 1998 .

[14]  Richard D. Duke,et al.  Accelerating residential PV expansion: supply analysis for competitive electricity markets , 2001 .

[15]  A. Louche,et al.  IMPROVED PROCEDURE FOR STAND-ALONE PHOTOVOLTAIC SYSTEMS SIZING USING METEOSAT SATELLITE IMAGES , 1998 .

[16]  S. Catalanotti,et al.  An analytical method to determine the optimal size of a photovoltaic plant , 1984 .

[17]  Sanford Klein,et al.  A method for estimating the performance of photovoltaic systems , 1982 .

[18]  Martin A. Green,et al.  SHORT COMMUNICATION: Price/efficiency correlations for 2004 photovoltaic modules , 2005 .

[19]  Tomas Markvart,et al.  Modelling battery charge regulation for a stand-alone photovoltaic system , 2000 .

[20]  Tawanda Hove,et al.  A method for predicting long-term average performance of photovoltaic systems , 2000 .

[21]  W. Beckman,et al.  A simplified method for estimating the monthly-average performance of photovoltaic systems , 1981 .

[22]  Hansjörg Gabler.  Autonomous power supply with photovoltaics : Photovoltaics for rural electrification : Reality and vision , 1998 .

[23]  Ali Naci Celik,et al.  A simplified model based on clearness index for estimating yearly performance of hybrid PV energy systems , 2002 .

[24]  Eduardo Lorenzo,et al.  On the usefulness of stand‐alone PV sizing methods , 2000 .