A technique to optimize reactive power using gbest Guided Artificial Bee Colony Algorithm

A. Thorat, I. Korachagaon, A. Mulla
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Abstract

Reactive power play an important role in voltage stability and economic activities of power system. To maintain power quality and security, voltage at each bus should be within its acceptable limit. Reactive power is one of the important aspects of active power loss minimization. Optimizing reactive power is a process of minimizing total active power loss by handling all the parameters of generation and transmission network without violating any specified constraints. The complex nonlinear optimization problem can be solved by classical optimization technique and experimental based technique. For handling wide complex network the experiment based techniques gives good results over numerical technique in most of the cases. This paper presents an application of gbest ABC algorithm to solve reactive power optimization problem. gbest guided ABC algorithm uses swarm intelligence techniques. To check the effectiveness and robustness of gbest-guided ABC algorithm it is applied on IEEE 30, IEEE57 and IEEE 118 standard test bus system. To validate results of gbest – guided ABC algorithm for the application of reactive power optimization problem it is compared with existing available literature data. The statistical analysis of gbest guided ABC algorithm is also carried out for IEEE 30, IEEE57 and IEEE 118 standard test bus system.
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一种基于最佳引导人工蜂群算法的无功优化技术
无功功率对电力系统的电压稳定和经济运行起着重要作用。为了保证电能质量和安全性,每个母线的电压应在其可接受的范围内。无功功率是实现有功损耗最小化的重要方面之一。无功优化是指在不违反任何规定约束条件的情况下,通过处理发输电网的所有参数,使总有功损耗最小的过程。复杂的非线性优化问题可以通过经典优化技术和基于实验的技术来解决。对于处理大范围复杂网络,基于实验的方法在大多数情况下都比数值方法具有更好的效果。本文介绍了gbest ABC算法在无功优化问题中的应用。gbest引导ABC算法采用群体智能技术。为了验证gbest-guided ABC算法的有效性和鲁棒性,将该算法应用于ieee30、IEEE57和ieee118标准测试总线系统。为了验证gbest - guided ABC算法在无功优化问题中的应用结果,并与已有文献数据进行了比较。并对ieee30、IEEE57和ieee118标准测试总线系统进行了gbest引导ABC算法的统计分析。
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