Sizing optimization of a stand-alone street lighting system powered by a hybrid system using fuel cell, PV and battery

Currently commercialised stand-alone street lighting systems based on the classical configuration coupling photovoltaic cells (PV) and battery cannot work all the year round in regions that are far from the equator. To improve the classical system, a hybrid system coupling a PV, a battery and a fuel cell is proposed. However, the sizing method of hybrid systems is a key issue in obtaining the cheapest system. To optimise the system, an original time-saving method is applied. Two optimization methods are used: first the genetic algorithms, then the simplex algorithms. A simulation model is used to evaluate the validity of the different hybrid configurations. After presenting the problem of stand-alone street lighting, the optimization methodology and the simulation model are detailed. Finally, an optimal configuration is obtained and shows that a 60W street light would cost 7150€ with a lifetime of 25 years. The optimised parameters are also given and analysed.

[1]  M. Y. Hussaini,et al.  Placement of wind turbines using genetic algorithms , 2005 .

[2]  S. M. Shaahid,et al.  Economic analysis of hybrid photovoltaic–diesel–battery power systems for residential loads in hot regions—A step to clean future , 2008 .

[3]  K. Agbossou,et al.  Renewable energy systems based on hydrogen for remote applications , 2001 .

[4]  James Larminie,et al.  Fuel Cell Systems Explained , 2000 .

[5]  Ingrid Schjølberg,et al.  Security and tolerable risk for hydrogen service stations , 2008 .

[6]  T. Funabashi,et al.  Optimum configuration for renewable generating systems in residence using genetic algorithm , 2006, IEEE Transactions on Energy Conversion.

[7]  Caisheng Wang,et al.  Unit sizing and cost analysis of stand-alone hybrid wind/PV/fuel cell power generation systems , 2006 .

[8]  D. Nichols,et al.  An optimal design of a grid connected hybrid wind/photovoltaic/fuel cell system for distributed energy production , 2005, 31st Annual Conference of IEEE Industrial Electronics Society, 2005. IECON 2005..

[9]  Kostas Kalaitzakis,et al.  Methodology for optimal sizing of stand-alone photovoltaic/wind-generator systems using genetic algorithms , 2006 .

[10]  S. Wakao,et al.  Reduction of Fuel Consumption in PV / Diesel Hybrid Power Generation System by Dynamic Programming Combined With Genetic Algorithm , 2006, 2006 IEEE 4th World Conference on Photovoltaic Energy Conference.

[11]  Alain Ricaud Modules photovoltaïques - Aspects technico-économiques , 2015, Conversion de l'énergie électrique.

[12]  Alireza Maheri,et al.  Application of combined analytical/FEA coupled aero-structure simulation in design of wind turbine adaptive blades , 2007 .

[13]  Giri Venkataramanan,et al.  Generation unit sizing and cost analysis for stand-alone wind, photovoltaic, and hybrid wind/PV systems , 1998 .

[14]  Saifur Rahman,et al.  A decision support technique for the design of hybrid solar-wind power systems , 1998 .

[15]  Lothar M. Schmitt,et al.  Theory of genetic algorithms , 2001, Theor. Comput. Sci..

[16]  J. Matics,et al.  Intelligent Design of PV based Home Supply using a Versatile Simulation Tool , 2005, Proceedings of the 13th International Conference on, Intelligent Systems Application to Power Systems.

[17]  Javier Contreras,et al.  Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage , 2007 .

[18]  Massimo Santarelli,et al.  Mathematical optimization of a RES-H2 plant using a black box algorithm , 2005 .

[19]  Yaow-Ming Chen,et al.  Determination of the solar cell panel installation angle , 2001, 4th IEEE International Conference on Power Electronics and Drive Systems. IEEE PEDS 2001 - Indonesia. Proceedings (Cat. No.01TH8594).

[20]  Yaow-Ming Chen,et al.  Calculation of the optimum installation angle for fixed solar-cell panels based on the genetic algorithm and the Simulated-annealing method , 2005 .

[21]  Neven Duić,et al.  Increasing renewable energy sources in island energy supply : case study Porto Santo , 2004 .

[22]  A.H. Gastaj,et al.  Optimal sizing of hybrid power system using genetic algorithm , 2005, 2005 International Conference on Future Power Systems.

[23]  Gilbert M. Masters,et al.  Renewable and Efficient Electric Power Systems , 2004 .