Abstract
An optimal design of a hybrid stand-alone photovoltaic system is essential to ensure reliable electricity supply to the loads and low cost of electricity generation. This paper presents an optimal design of an AC coupled hybrid stand-alone photovoltaic system which consists of photovoltaic modules, batteries, grid inverters, bi-directional inverters and diesel generator. A computational intelligence known as Honey Badger Algorithm (HBA) was employed to minimize either the loss of power supply probability or the levelized cost of electricity by selecting the optimal model of system components. For validation purpose, an iterative sizing algorithm (ISA) was developed to yield optimal design solution without the usage of computational intelligence. The HBA was found to be a faster algorithm than ISA in both design cases, i.e. minimizing loss of power supply probability and minimizing levelized cost of electricity. In addition, HBA was also discovered to be superior than Particle Swarm Optimization, Teaching Learning Based Optimization and Firefly Algorithm during the design optimization by producing minimum loss of power supply probability and minimum levelized cost of electricity with lower computational time, population size and minimum number of iterations for convergence.
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