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Runge Kutta (RUN) is an up-to-date and well-founded metaheuristic algorithm. The RUN algorithm aims to find the global best in solving problems by going beyond the traps of metaphors. For this purpose, enhanced solution quality mechanism is used to avoid local optimum solutions and increase the convergence speed. Although the RUN algorithm offers promising solutions, it is seen that this algorithm has shortcomings, especially in solving high dimensional multimodal problems. In this study, the solution candidates that guide the search process in the RUN algorithm are developed using the Fitness-Distance Balance (FDB) method. Thus, using the FDB-based RUN algorithm, the global optimum value of many optimization problems will be obtained in the future. CEC 2020 which has current benchmark problems was used to test the performance of the developed FDB-RUN algorithm. 10 different unconstrained benchmark problems taken from CEC 2020 were designed by arranging them in 30/50/100 dimensions. Experimental studies were carried out using the designed benchmark problems and analyzed with Friedman and Wilcoxon statistical test methods. According to the results of the analysis, it was seen that the FDB-RUN variations showed a superior performance compared to the base algorithm (RUN) in all experimental studies. In particular, it has been shown to provide more effective results for the continuous optimization of high-dimensional problems.

Low-frequency oscillations due to unpredictable disturbances in an interconnected power grid are a serious threat to the stability of the power system. Reliable operation of a modern power system, when exposed to sudden disturbances, is crucial, and the safe operation of the system is directly related to success in damping oscillations. Power System Stabilizer (PSS) devices have been used to reduce fluctuations caused by short-time disturbances in power systems. These devices provide additional damping torque components to the generators as an auxiliary control device of the excitation system. Due to the non-linearity of electrical power systems, it is significant to design multi-machine power systems with optimum PSS parameters under critical conditions. In this paper, the PSS design problem was solved using the Runge Kutta Algorithm (RUN). The PSS design problem was considered an optimization problem in which an eigenvalue-based objective function has developed, and the proposed RUN method was tested in a WSCC 3-machine 9-bus test system using the linearized Heffron-Phillips model. In the linearized model, system stability has been enhanced by shifting the eigenvalues to the stability regions. When the results obtained from the test system are examined, it has seen that the proposed RUN is the most effective method in terms of system stability.

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Copyright of Duzce University Journal of Science & Technology is the property of Duzce University Journal of Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)