Determination of power system controller parameters using fitness distance balance based social network search algorithm

In this thesis study, in order to determine optimal parameters of the controllers, which are of crucial importance in the safe operation of modern power systems and used in the solution of the transient stability analysis problem, the fitness-distance balance (FDB) based Social Network Search, (SNS) Algorithm (FDBSNS) has been improved. In this context, the thesis study consists of three general stages. In the first stage, the SNS algorithm was developed using the FDB selection method due to its insufficient exploration-exploitation capability and early convergence problems. The FDB method enables the solution candidates to be selected more efficiently by considering the fitness and distance values in the search process in the SNS algorithm. Accordingly, the performance of the improved FDBSNS algorithm was tested using IEEE CEC 2014 and CEC 2017 benchmark problems. In the second stage, the FDBSNS algorithm is applied to the problem of determining the optimal parameters of the Power System Stabilizers (PSS) in order to provide transient stability in power systems. In solving the problem, PSS parameters were optimized by using 10-different up-to-date and effective competitor Meta-heuristic Search (MSA) algorithms in addition to the proposed FDBSNS algorithm. Afterward, the fitness values obtained by MSA algorithms according to the proposed objective function were compared using various statistical analysis methods. In addition, the effect of FDBSNS was tested in the WSCC 3-Machine 9-Bus and New England 10-Machine 39-Bus test systems by conducting time domain analyses for the various fault scenarios. In the third stage, the FDBSNS is used to solve the problem of determining the optimal parameters of TCSC-based Controllers problem in order to provide transient stability in power systems. In the solution of the problem, the parameters of TCSC-based Lead-Lag (LL) and TCSC-based Proportional-Integral-Derivative, (PID) controllers were optimized by using 11 different up-to-date and effective competitor algorithms as well as FDBSNS. In addition, the effect of the FDBSNS on the solution of the problem has been investigated in terms of statistical analyzes and time domain analyses for the fault condition and different loading scenarios determined in a Single Machine Infinite Bus (SMIB) power system. When the results obtained are examined comprehensively, it is seen that the improved FDBSNS provides a superiority to all the competitor algorithms in solving the benchmark problems and in ensuring transient stability by optimizing the controller parameters in power systems.