A QOBL-SAO and its variant: An open source software for optimizing PV/wind/battery system and CEC2020 real world problems

• Published in: SOFTWARE IMPACTS
• Main Authors: Mas'ud, Abdullahi Abubakar; Salawudeen, Ahmed T.; Umar, Abubakar A.; Shaaban, Yusuf A.; Muhammad-Sukki, Firdaus; Musa, Umar; Alshammari, Saud J.
• Format: Article
• Language: English
• Published: ELSEVIER 2024
• Subjects: Computer Science
• Online Access: https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001199634100001

The Quasi oppositional smell agent optimization (QOBL-SAO) and its levy flight variant (LFQOBL-SAO) are two cutting-edge software tools for optimizing PV/wind/battery power systems. They can also be used to solve real-world CEC2020 optimization problems and are as good as top-performing software such as IUDE, epsilon MAgES and the iLSHAD epsilon. The QOBL-SAO exploits the random mode's weakness and then adds a number to the initial population. The LFQOBL-SAO, on the other hand, improves the random mode's weakness in order to solve this problem. The LFQOBL-SAO improves performance and search space by using levy flight instead of random code.