Summary
An improved whale optimization algorithm (IWOA) for the design of a robust power system stabilizer (PSS) for the multi‐machine power system is developed in this paper. Tuning of PSS parameters using the proposed IWOA is carried out by minimizing a multi‐objective function comprising the damping ratio and damping factor of lightly damped oscillating modes of all the generators. The advantage of considering the objective function is that the lightly damped and undamped oscillating modes of all the generators can shift to a prespecified zone of the s‐plane. The performance of the proposed IWOA is tested on standard benchmark test functions and compared with familiar optimization algorithms. The efficacy of the proposed design technique is tested on three benchmark test systems: three‐generator nine‐bus system, two‐area four‐machine interconnected system, and the New England 10‐generator 39‐bus system working on various operating conditions under several typical disturbances. The potential of the proposed method is demonstrated through eigenvalue analysis. The proposed IWOA‐based PSS is compared with the other stabilizers to show its efficacy.
In a deregulated power system uncertainty exists and lack of sufficient damping can lead to Low Frequency Oscillations (LFO). The problem can be addressed using robust Power System Stabilizers (PSS). In this paper, an optimal procedure to design a robust PID-PSS using interval arithmetic for the Single Machine Infinite Bus (SMIB) power system is proposed. The interval modelling captures the wide variations of operating conditions in bounds of system coefficients. In the proposed design procedure, simple and new closed loop stability conditions for an SMIB interval system are developed and are used to design an optimum PID-PSS for improving the performance of an SMIB system. The optimum PID-PSS is attained by tuning the parameters using the FMINCON tool provided in MATLAB. The robustness of the proposed PID-PSS design is validated and compared to other notable methods in the literature when the system is subjected to different uncertainties. The simulation results and performance error values show the effectiveness of the proposed robust PID-PSS controller.
In this paper, a Pareto multiobjective and grasshopper optimization algorithm (GOA) based optimum proportional–integral–derivative (P–I–D) controller design is proposed for improving the vehicle active suspension system dynamics under road disturbance conditions. The Pareto objectives considered are minimization of sprung mass suspension deflection, tyre deflection, sprung mass acceleration minimization and eigenvalue-based objective function. State space model for quarter vehicle active suspension system with P–I–D controller is developed for analyzing the stability and dynamic performance of the system. The sinusoidal-based bump road disturbances are used for testing the robustness of the proposed control technique. Simulation results have been presented to show the advantage of the proposed Pareto multiobjective and GOA-based P–I–D controller over the weighted multiobjective and genetic algorithm-based P–I–D controller in terms of stability and dynamics of the active suspension system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.