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Artificial Immune Systems Optimization Approach for Multiobjective Distribution System Reconfiguration

机译:多目标配电系统重构的人工免疫系统优化方法

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摘要

In order to optimize their assets, electrical power distribution companies seek out various techniques to improve system operation and its different variables, like voltage levels, active power losses and so on. A few of the tools applied to meet these objectives include reactive power compensation, use of voltage regulators, and network reconfiguration. One target most companies aim at is power loss minimization; one available tool to do this is distribution system reconfiguration. To reconfigure a network in radial power distribution systems means to alter the topology changing the state of a set of switches normally closed (NC) and normally opened (NO). In restructured electrical power business, a company must also consider obtaining a topology as reliable as possible. In most cases, reducing the power losses is no guarantee of improved reliability. This paper presents a multiobjective algorithm to reduce power losses while improving the reliability index using the artificial immune systems technique applying graph theory considerations to improve computational performance and Pareto dominance rules. The proposed algorithm is tested on a sample system, 14-bus test system, and on Administración Nacional de Electricidad (ANDE) real feeder (CBO-01 23-kV feeder).
机译:为了优化其资产,配电公司寻求各种技术来改善系统运行及其不同的变量,例如电压水平,有功功率损耗等。用于实现这些目标的一些工具包括无功功率补偿,电压调节器的使用和网络重新配置。大多数公司的目标之一是最大程度地降低功耗。实现此目的的一种可用工具是配电系统重新配置。在径向配电系统中重新配置网络意味着要更改拓扑,从而更改一组常闭(NC)和常开(NO)开关的状态。在重组的电力业务中,公司还必须考虑获得尽可能可靠的拓扑。在大多数情况下,减少功耗并不能保证可靠性的提高。本文提出了一种多目标算法,该算法使用人工免疫系统技术,在降低功耗的同时提高了可靠性指标,并运用了图论的考虑来提高计算性能和帕累托优势规则。所提出的算法在示例系统,14总线测试系统以及美国国家电力公司(ANDE)真实馈线(CBO-01 23-kV馈线)上进行了测试。

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