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A novel approach of intensified barnaclesmating optimization for the mitigation of power system oscillations

机译:一种新的强化雄性优化对电力系统振动性振动优化的新方法

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摘要

Optimization is the process of attaining the best solution from the available set of prioritized constraints to maximize or minimize the desired function involved in it. It is imperative in engineering to plan and design to find the best out of confined resource and time. A recently recommended barnacles matting optimization (BMO) has been recognized in computing the optimal parameters of the electric power system with excellent performance characteristics. In this paper, the intensified version of BMO has been proposed with the aid of cuckoo search (CS) and traditional particle swarm optimization (PSO). An in-depth analysis was made on the BMO technique and proposed suitable modifications to deal with the electrical power system stability enhancement issue efficiently. The proposed technique in the power system stabilizer (PSS) parameter computation is validated on the 23 benchmark functions to examine for its suitability. The robustness of the proposed method is presented via statistical analysis and boxplot of the 23 benchmark functions. The PSS parameters are computed in a benchmark two area four machine system using intensified BMO under self-clearing fault conditions. A multi-objective function is designed to improve the damping nature offered under system uncertainties, and the comparative analysis is presented among conventional PSS, BMO, intensified BMO with CS and PSO (BMO-CS and BMO-PSO), and harris hawks optimizer.
机译:优化是从可用的优先约束中获得最佳解决方案的过程,以最大化或最小化其涉及所涉及的所需功能。在工程方面必须计划和设计,以找到最佳资源和时间。最近推荐的菱形垫消光优化(BMO)在计算具有优异性能特性的电力系统的最佳参数时得到了认可。在本文中,借助Cuckoo搜索(CS)和传统粒子群优化(PSO)提出了BMO的强化版本。对BMO技术进行了深入的分析,并提出了有效地处理电力系统稳定性增强问题的合适修改。在23个基准函数上验证了电力系统稳定器(PSS)参数计算中的所提出的技术,以检查其适用性。所提出的方法的稳健性通过23个基准函数的统计分析和盒子盒呈现。 PSS参数在自清洁故障条件下使用强化BMO计算在基准两个区域四机器系统中。旨在改善系统不确定因素提供的阻尼性质的多目标函数,并且在常规PSS,BMO,CS和PSO(BMO-CS和BMO-PSO)中提出了比较分析,以及哈里斯鹰优化器。

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