Abstract
This paper discusses the use of a stochastic metaheuristic population-based optimization algorithm known as the sine cosine algorithm (SCA) to design the parameters of a power system stabilizer (PSS) for damping electromechanical oscillations in a single machine connected to a large power system. The design of the PSS parameters was formulated as an optimization problem to minimize the objective function value. The SCA was used to obtain the best values of the PSS parameters under the objective function. Simulation was carried out by a linearized power system model. The lead lag controller was used as the PSS structure and the results from that were compared with those obtained by moth flame optimization and evolutionary programming. The results showed that the SCA is more effective than are the other techniques in exploration and exploitation to tune the PSS parameters and enhance the power system stability by damping oscillations in a range of loading conditions.
Highlights
The main source of electrical power is a synchronous generator
Oscillations that are not damped completely may lead to an increase in low frequency oscillations in power networks, causing problems in system stability and reducing the power transfer capacity of transmission lines [1,2,3]
This research aimed to develop a model of a machine connected to large system and formulate the objective function based on a maximum damping factor to improve the angle stability of the power system
Summary
The main source of electrical power is a synchronous generator. The electric power system is complex, and a stable power system operates in equilibrium. This research aimed to develop a model of a machine connected to large system and formulate the objective function based on a maximum damping factor to improve the angle stability of the power system. The performance of the PSS lead lag controller was tuned with the SCA and the resulting parameters were compared with those optimized with moth flame optimization (MFO) and evolutionary programming (EP) to accurately and effectively predict and assess the angle stability before a power system collapse. This study presents the application of metaheuristic optimization algorithms and the objective function and proposes a design for a robust controller of the excitation of a machine-connected infinite bus system. The small signal stability of a power system was improved by mathematical modelling of a SMIB and formulation of an objective function based on a maximum damping factor.
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