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

• Published in: Software Impacts
• Main Author: Mas'ud A.A.; Salawudeen A.T.; Umar A.A.; Shaaban Y.A.; Muhammad-Sukki F.; Musa U.; Alshammari S.J.
• Format: Article
• Language: English
• Published: Elsevier B.V. 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186083090&doi=10.1016%2fj.simpa.2024.100630&partnerID=40&md5=76e4e338c27918cd461cd6c8346e32f3

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, ϵ MAgES and the iLSHAD ɛ. 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. © 2024 The Author(s)