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A novel robust automatic generation control in interconnected multi-area power system based on bat inspired algorithm

机译:基于蝙蝠启发算法的互联多区域电力系统鲁棒自动发电控制

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This paper deals with the design of a new robust controller to solve automatic generation control (AGC) problems in interconnected multi-area power system using the meta-heuristic Bat Inspired Algorithm (BA). The novel design approach based on Bat algorithm is proposed to reach the optimal values of the Proportional-Integral-Derivation (PID) controller parameters in order to improve the load frequency control (LFC) and automatic voltage regulator (AVR). The three equal area thermal interconnected power system is considered for the simulation. The superiority of the proposed approach is demonstrated by comparing the results with some recently published techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Bacteria Foraging Optimization (BFO), Artificial Bee Colony (ABC) and Ziegler-Nichols based PID controller for the same interconnected power system. Robustness analysis is carried out by varying the step load disturbance in each area, to demonstrate the capability of the proposed Bat Inspired Algorithm (BA) to solve AGC problems (LFC / AVR) and optimized PID controller.
机译:本文研究了一种新的鲁棒控制器的设计,该解决方案使用元启发式蝙蝠启发算法(BA)解决了互连多区域电力系统中的自动发电控制(AGC)问题。提出了一种基于蝙蝠算法的新颖设计方法,以达到比例积分微分(PID)控制器参数的最优值,以改善负载频率控制(LFC)和自动电压调节器(AVR)。仿真中考虑了三个等面积的热互连电力系统。通过将结果与一些最近发表的技术进行比较,证明了该方法的优越性,例如遗传算法(GA),粒子群优化(PSO),细菌觅食优化(BFO),人工蜂群(ABC)和Ziegler-Nichols同一互连电源系统的PID控制器。通过改变每个区域的阶跃负载扰动来进行鲁棒性分析,以证明所提出的Bat Inspired算法(BA)解决AGC问题(LFC / AVR)和优化PID控制器的能力。

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