@article{Johar_Shu Ai_Mohd Siam_2020, title={Sizing Optimization of Hybrid Photovoltaic-Wind-Battery System towards Zero Energy Building using Genetic Algorithm}, volume={36}, url={https://matematika.utm.my/index.php/matematika/article/view/1237}, DOI={10.11113/matematika.v36.n3.1237}, abstractNote={<p><span class="fontstyle0">A new topic of Zero Energy Building (ZEB) is getting famous in research area<br />because of its goal of reaching zero carbon emission and low building cost. Renewable<br />energy system is one of the ideas to achieve the objective of ZEB. Genetic Algorithm (GA)<br />is widely used in many research areas due to its capability to escape from a local minimal<br />to obtain a better solution. In our study, GA is chosen in sizing optimization of the<br />number of photovoltaic, wind turbine and battery of a hybrid photovoltaic-wind-battery<br />system. The aim is to minimize the total annual cost (TAC) of the hybrid energy system<br />towards the low cost concept of ZEB. Two GA parameters, which are generation number<br />and population size, have been analysed and optimized in order to meet the minimum<br />TAC. The results show that the GA is efficient in minimizing cost function of a hybrid<br />photovoltaic-wind-battery system with its robustness property</span> <br /><br /></p>}, number={3}, journal={MATEMATIKA}, author={Johar, Farhana and Shu Ai, Julies Bong and Mohd Siam, Fuaada}, year={2020}, month={Dec.}, pages={235–250} }