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Simultaneous adjustment of AVR and optimized PSS outputs effect in power systems for stability improvement

Salesi-Mousaabadi Majid, Shahgholian Ghazanfar

Journal of Power Technologies

2023

Vol. 103, nr 1

1--13

Due to the problems related to low-frequency oscillations (LFOs) and power systems complexities, using intelligent methods and optimization techniques is essential for solving power system stabilizer (PSS) problems. In this paper, power system stabilizer, based on the PSOPSS, is designed to set the parameters of PSS. Then, the FLC is designed to simultaneously weighting the automated voltage regulator and power system stabilizer outputs, to adjust the excitation controller facing with disturbance. The ability to optimize particle swarm algorithm, in combination with FLC ability to solve complex and nonlinear problems, will effectively improve the stability of the power system. Initially, the simulation was performed on a single machine system in which the PSS optimal parameters were obtained using particle swarm optimization (PSO). Afterwards, with simultaneous regulation of the voltage and damping by the fuzzy logic controller, the effectiveness of the proposed approach, compared with the PSS based on the linear optimization controller, is confirmed. Next, more effective results can be obtained on a multi-machine system with effective placement of the FLPSS, compared with the conventional PSS and with simultaneous adjustment of the output weights of voltage and damping controllers using FLC. The efficiency of the proposed method in response to a variety of disturbances is determined.

Fractional order PIλDμ controller with optimal parameters using Modified Grey Wolf Optimizer for AVR system

Verma Santosh Kumar, Devarapalli Ramesh

Archives of Control Sciences

2022

Vol. 32, No. 2

429--450

In this paper, an automatic voltage regulator (AVR) embedded with fractional order PID (FOPID) is employed for the alternator terminal voltage control. A novel meta-heuristic technique, a modified version of grey wolf optimizer (mGWO) is proposed to design and optimize the FOPID AVR system. The parameters of FOPID, namely, proportional gain (ΚP), the integral gain ( ΚI), the derivative gain ( ΚD), λ and μ have been optimally tuned with the proposed mGWO technique using a novel fitness function. The initial values of the ΚP, ΚI , and ΚD of the FOPID controller are obtained using Ziegler-Nichols (ZN) method, whereas the initial values of λ and μ have been chosen as arbitrary values. The proposed algorithm offers more benefits such as easy implementation, fast convergence characteristics, and excellent computational ability for the optimization of functions with more than three variables. Additionally, the hasty tuning of FOPID controller parameters gives a high-quality result, and the proposed controller also improves the robustness of the system during uncertainties in the parameters. The quality of the simulated result of the proposed controller has been validatedby other state-of-the-art techniques in the literature.