This work proposes the implementation of a recently invented meta-heuristic optimization solver namely, an adaptive multiple teams perturbation-guiding Jaya (AMTPG-Jaya) technique to tackle with diverse single goal optimum power flow (OPF) forms. The AMTPG-Jaya solver employs numerous populations named as teams to investigate the search domain. Each team is guided by a number of movement equations (exploration pathways). The algorithm adjusts the number of teams along with the approaching to the finest so-far nominee solution. In this study, an original AMTPG-Jaya inspired approach to handle the OPF formulation is suggested. The efficacy of the AMTPG-Jaya solver is scrutinized and tested on two well-known standard power systems with different goal functions. The optimization outcomes reveal that the AMTPG-Jaya is able to reach an optimal solution with brilliant convergence speed. In addition, a robustness examination is implemented to evaluate the reliability of the AMTPG-Jaya solver. The simulation results disclose the dominance and potential of the AMTPG-Jaya over many solvers recently stated in the previous publications with regard to solution quality and validity.

这项工作提出了一种新发明的元启发式优化求解器的实现方法，即一种自适应的多团队摄动引导Jaya（AMTPG-Jaya）技术，以解决各种单目标最优潮流（OPF）形式。AMTPG-Jaya解算器雇用了许多人为团队来调查搜索范围。每个团队都受到许多运动方程式（探索路径）的指导。该算法会调整团队数量，并寻求最佳的迄今​​为止的被提名人解决方案。在这项研究中，建议使用原始的AMTPG-Jaya启发性方法来处理OPF配方。AMTPG-Jaya解算器的功效已在具有不同目标功能的两个知名标准电源系统上进行了仔细检查和测试。优化结果表明AMTPG-Jaya能够以出色的收敛速度达到最佳解决方案。此外，还进行了鲁棒性检查，以评估AMTPG-Jaya解算器的可靠性。仿真结果揭示了AMTPG-Jaya在解决方案质量和有效性方面在先前出版物中最近指出的许多求解器上的优势和潜力。