Dynamic load management and optimum sizing of stand-alone hybrid PV/Wind system.

Simulation algorithms for the sizing of stand-alone hybrid PV/Wind systems are a powerful tool in evaluating the optimum configuration that would cover the energy demand with a predefined reliability level at the lowest cost. Several parameters such as the interval of the simulation (day, day-night, hourly) and the consumption profile may significantly affect the optimum configuration. This paper examines the effect of these parameters within an optimum sizing simulation algorithm developed. The effect of these parameters was particularly evident at low battery capacities, which involve optimum configurations resulting in minimum cost. Furthermore, shift-able loads in the hourly-based weekly profile assumed in this study were identified, and a dynamic load management functionality was developed. In this approach, loads that could be shifted through time were dynamically allocated during periods of excess energy production by the hybrid PV/Wind system. The results showed an increase in system reliability from 95% to 97% when load shifting was introduced. Finally, sizing the system for only the static (non-shift-able loads) proved to withstand the addition of the extra shift-able loads while retaining the 95% reliability level when the load management functionality was introduced. Thus, a smaller installation with lower cost is achieved.

[1]  C. Justus,et al.  Height variation of wind speed and wind distributions statistics , 1976 .

[2]  Fatih Onur Hocaoglu,et al.  A novel hybrid (wind-photovoltaic) system sizing procedure , 2009 .

[3]  A. Louche,et al.  Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions , 2008 .

[4]  Eleni Kaplani,et al.  A stochastic simulation model for reliable PV system sizing providing for solar radiation fluctuations , 2012 .

[5]  Wei Zhou,et al.  A novel optimization sizing model for hybrid solar-wind power generation system , 2007 .

[6]  A J Anderson,et al.  Photovoltaic translation equations: A new approach. Final subcontract report , 1996 .

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

[8]  Ιωάννης Καλδέλλης,et al.  Minimum cost solution of wind–photovoltaic based stand-alone power systems for remote consumers , 2015 .

[9]  Wei Zhou,et al.  Current status of research on optimum sizing of stand-alone hybrid solar–wind power generation systems , 2010 .

[10]  Eleni Kaplani,et al.  Thermal modelling and experimental assessment of the dependence of PV module temperature on wind velocity and direction, module orientation and inclination , 2014 .

[11]  A. Balouktsis,et al.  Sizing stand-alone photovoltaic systems , 2006 .

[12]  Soteris A. Kalogirou,et al.  Artificial intelligence techniques for photovoltaic applications: A review , 2008 .

[13]  Tom Markvart,et al.  PV system sizing using observed time series of solar radiation , 2006 .

[14]  A. Rajendra Prasad,et al.  Optimization of integrated photovoltaic–wind power generation systems with battery storage , 2006 .

[15]  Djamila Diaf,et al.  A methodology for optimal sizing of autonomous hybrid PV/wind system , 2007 .