Ecology, Environment and Conservation Paper

Vol 23, Sept. Suppl. Issue 2017; Page No.(308-320)

PARAMETERS ESTIMATION OF SOLAR PV MODELS USING GRASS HOPPER OPTIMIZATION ALGORITHM

Adla Vinod and Ashoke Kumar Sinha

Abstract

Photovoltaic (PV) parameter estimation become necessary for optimum performance of various diode models, as variance of temperature and irradiance is presented in this paper. Researchers applied genetic algorithm, particle swarm optimization, different evolution, simulated annealing, least squares method, pattern search, cuckoo search, memetic algorithm and multi-verse optimizer to achieve as close as possible to the experimental V-I characteristics by utilizing the above algorithms. In this work proposed four diode model tuned grass hopper optimizer algorithm (GOA) which is bio-inspired behavior utilized as a latest technique and approach to find the optimum parameters of PV models. Estimated parameters and performance results on Root mean square error depicted are compared with above algorithms and it is found that proposed approach is having better performance than others and moreover experimental validation results are compared with theoretical results.

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