Teacher Learning based Optimization Algorithm for Optimal Sizing of Hybrid Wind and Solar Renewable Energy System
Diriba Kajela Geleta1, Mukhdeep Singh Manshahia2

1Diriba Kajela Geleta*, Department of Mathematics, Punjabi University, Patiala, India.
2Mukhdeep Singh Manshahia, Department of Mathematics, Punjabi University, Patiala, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on April 10, 2020. | PP: 2036-2041 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3408049620/2020©BEIESP | DOI: 10.35940/ijitee.F3408.049620
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In this paper the Teacher Learning process Based Optimization (TLBO) algorithm was employed in order to optimize wind and solar hybrid energy. Minimizing total annual cost, by determining appropriate numbers components to satisfy the desired load based on the given constraints is the main concern of this research. The algorithm was recently innovated random search meta heuristic algorithm. When it was signed the actual of process learning in a class was imitated. The result has shown that TLBO could be applied to optimize hybrid system. It was concluded that, the algorithm converges to optimal solution with relatively good convergence rate. It has shown that, TLBO has some advantage over other algorithms by comparing the result with some results in literature. 
Keywords: Hybrid Renewable Energy, Optimization, Nature Inspired Algorithm, Teaching Learning Based Optimization Algorithm.
Scope of the Article: Design Optimization of Structures