Abstract
The small-signal stability is the cause of concern for modern-day power engineers. These mostly go undetected at the sender end but causes voltage fluctuations at the receiver end/ distributor end. The main reason behind this instability is the continuously varying operating point of the power system. Due to this, many types of controllers are being used whose nature are non-linear in nature. Thus, their effectiveness and swiftness to tackle such small-signal instability depend merely on their parameters. To fulfil this demand, various hybrid methods are being utilized. In this article, a novel optimization algorithm, Hybrid Butterfly Optimization Algorithm—Particle Swarm Optimization (HBOAPSO), has been used to tune the parameters of the Power System Stabilizer (PSS) employed in the Two Area Four Machines system. The obtained performance of HBOAPSO-PSS is then compared to other metaheuristic methods. The HBOAPSO-PSS has shown promising results. This can also be observed by the convergence graph of the HBOAPSO with respect to iteration. The inability of BOA to maintain a balance between local and global optima is removed by hybridizing it with PSO.
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The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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Gude, M.K., Salma, U. A novel approach of PSS optimal parameter tuning in a multi-area power system using hybrid butterfly optimization algorithm- particle swarm optimization. Int J Syst Assur Eng Manag 13, 2619–2628 (2022). https://doi.org/10.1007/s13198-022-01678-2
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DOI: https://doi.org/10.1007/s13198-022-01678-2