Optimal Economical sizing of a PV-Wind Hybrid Energy System using Genetic Algorithm and Teaching Learning Based Optimization | Abstract

ISSN ONLINE(2278-8875) PRINT (2320-3765)

Research Article Open Access

Optimal Economical sizing of a PV-Wind Hybrid Energy System using Genetic Algorithm and Teaching Learning Based Optimization

Abstract

In this paper, a new approach of optimal Economical sizing of a Hybrid PV-Wind energy system is presented in order to assist the designers to take into consideration both the economic and ecological aspects. This paper presentsthe various optimization techniques to design the hybrid PV-wind system. The hybrid system consists of photovoltaic panels, wind turbines and storage batteries. Genetic Algorithm (GA) and Teaching Learning Based Optimization (TLBO) optimization techniquesare utilized to minimize the formulated objective function, i.e. total cost which includes initial costs, yearly replacement cost, yearly operating costs and maintenance costs and salvage value of the proposed hybrid system. It also presents the application and performance comparison of GA and TLBO optimization techniques for optimal sizing of Hybrid PV/Wind energy system. Two computer programsare designed, using MATLAB code to formulate the optimization problem by computing the coefficients of the objective function. Finally, the optimal solution is achievedby GA& TLBO optimization method.

Satish Kumar Ramoji, B.Jagadish Kumar

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