Optimal Design of Photovoltaic–Battery Systems Using Interval Type-2 Fuzzy Adaptive Genetic Algorithm
- 1 Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia 60111
- 2 Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia 60111
- 3 Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia 60111
- 4 Department of Electrical Engineering, Institut Teknologi Sepuluh Nopember (ITS), Surabaya, Indonesia 60111
Abstract
Many countries have been triggered to provide a new energy policy which promotes renewable energy applications because of public awareness to reduce the global warming and rising in fuel prices. Renewable energy sources such as solar energy are green and promising energy in the future for widespread use. Combining renewable energy sources with battery makes electricity supply more economical and reliable to meet all possible load level . This paper propos ed a new hybrid method to optimiz e Photovoltaic ( PV) - Battery systems . The proposed method was name d Interval t ype -2 f uzzy adaptive g enetic a lgorithm ( IT2FAGA). Genetic a lgorithm ( GA) is one of modern optimization techniques that has been successfully applied in various areas of power systems . To enhance the ability of GA to prevent trapping in local optima and increase convergence in a global optima, the crossover probability ( p cross ) and the mutation probability ( p mut ) , parameters in GA, are tuned using i nterval t ype -2 f uzzy l ogic ( IT2FL) . Objective function used in this paper was the a nnual c ost of sytem ( ACS) consist ing of the a nnual c apital c ost ( ACC), a nnual r eplacement c ost ( ARC), a nnual o peration c ost m aintenance ( AOM). The proposed method was also compared to f uzzy a daptive g enetic a lgorithm (FGA) and s tandard g enetic a lgorithm (SGA) . S imulation results indicated that the proposed<
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