Sizing Optimization of Hybrid Photovoltaic-Wind-Battery System towards Zero Energy Building using Genetic Algorithm


  • Farhana Johar Department of Mathematical Sciences, Universiti Teknologi Malaysia
  • Julies Bong Shu Ai
  • Fuaada Mohd Siam



A new topic of Zero Energy Building (ZEB) is getting famous in research area
because of its goal of reaching zero carbon emission and low building cost. Renewable
energy system is one of the ideas to achieve the objective of ZEB. Genetic Algorithm (GA)
is widely used in many research areas due to its capability to escape from a local minimal
to obtain a better solution. In our study, GA is chosen in sizing optimization of the
number of photovoltaic, wind turbine and battery of a hybrid photovoltaic-wind-battery
system. The aim is to minimize the total annual cost (TAC) of the hybrid energy system
towards the low cost concept of ZEB. Two GA parameters, which are generation number
and population size, have been analysed and optimized in order to meet the minimum
TAC. The results show that the GA is efficient in minimizing cost function of a hybrid
photovoltaic-wind-battery system with its robustness property