Optimal sizing of a grid integrated solar photovoltaic system

This study proposes an optimal sizing methodology for a solar photovoltaic (SPV) system considering lifetime cost requirements. The aim of the design is optimal sizing of SPV system, which is obtained by calculating SPV system output power at certain location, taking into account the calculated optimal number of SPV modules, optimal number of inverters, optimal tilt angle, for a given dimension of land. This design is aimed for minimising the annual cost of grid-integrated SPV system over its life or years of operation. The cost function takes into account the capital cost of installation, operation and maintenance, for each component of the system and the cost of selling energy to the grid. The sizing optimisation has been formulated as a non-linear, multi-variable problem and the particle swarm optimisation algorithm has been tested using MATLAB platform for a particular location to swot up the feasibility of integrated system. The monthly averaged daily and hourly solar radiation data for a given location is calculated using empirical relations on MATLAB platform. Other inputs are specifications of commercially available devices and meteorological details of location.

[1]  D. Weinstock,et al.  Shadow variation on photovoltaic collectors in a solar field , 2004, 2004 23rd IEEE Convention of Electrical and Electronics Engineers in Israel.

[2]  Francisco Jurado,et al.  Optimal placement and sizing from standpoint of the investor of Photovoltaics Grid-Connected Systems using Binary Particle Swarm Optimization , 2010 .

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

[4]  Lingfeng Wang,et al.  Compromise Between Cost and Reliability In Optimum Design of An Autonomous Hybrid Power System Using Mixed-Integer PSO Algorithm , 2007, 2007 International Conference on Clean Electrical Power.

[5]  W. Prommee,et al.  A study of particle swarm technique for renewable energy power systems , 2010, Proceedings of the International Conference on Energy and Sustainable Development: Issues and Strategies (ESD 2010).

[6]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[7]  I. Musirin,et al.  Artificial immune system for sizing grid-connected photovoltaic system , 2011, 2011 5th International Power Engineering and Optimization Conference.

[8]  Keiichiro Yasuda,et al.  Adaptive particle swarm optimization using velocity information of swarm , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[9]  Saman K. Halgamuge,et al.  Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients , 2004, IEEE Transactions on Evolutionary Computation.

[10]  Badrul H. Chowdhury Optimizing the integration of photovoltaic systems with electric utilities , 1992 .