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Collective animal behavior algorithm for optimal reactive power dispatch problems

机译:最优无功分配问题的集体动物行为算法

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摘要

This paper proposes collective animal behavior (CAB) algorithm for solving optimal reactive power dispatch (ORPD) problem of power systems. Typically, ORPD is defined as the minimization of active power transmission losses and/or total voltage deviation (TVD) of load buses by controlling a number of control variables such as settings of generator voltages, tap positions of tap changing transformers and amount of reactive compensation. In this paper, CAB algorithm has been applied for this optimization problem of power systems. It has been applied to three standard power networks like IEEE 30-, 57- and 118-bus test power systems with the above objectives. Both economical (in the form of minimization of active power loss) as well as technical (in the form of minimization of TVD) benefits arisen are presented in this paper.
机译:提出了一种集体动物行为(CAB)算法来解决电力系统的最优无功调度(ORPD)问题。通常,ORPD定义为通过控制许多控制变量(例如发电机电压的设置,抽头变换变压器的抽头位置和无功补偿量)来最小化有功功率传输损耗和/或负载母线的总电压偏差(TVD) 。本文将CAB算法应用于电力系统的优化问题。具有上述目的,它已应用于三种标准电源网络,如IEEE 30总线,57总线和118总线测试电源系统。本文介绍了既有经济效益(以有功功率损失最小化的形式)又有技术效益(以有损TVD形式的形式)。

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