船舶区域配电系统全智能体重构及其优化研究
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张 威(1987-),女,博士研究生,研究方向为电力系统控制与优化;E-mail: viweizhang@163.com

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高等学校博士学科点专项科研基金项目(20123121110003);上海海事大学研究生创新基金资助项目(2014ycx056)


Research on agent based reconfiguration and its optimization for shipboard zonal power systems
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    摘要:

    为确保船舶电力系统故障发生时主电力推进动力系统不失去供电,对电力推进船舶区域配电系统的拓扑结构重构方法进行了深入研究。依托智能体理论,设计了一种环境智能感知、信念产生、目标控制、粒子群最优决策的全智能体重构方法,实施船舶区域配电系统故障的拓扑重构。重构策略以保证全船的不间断供电、负荷损失最小、继电保护效率最高等为目标。对某电力推进船舶区域配电系统电网发生三相短路工况的仿真实验表明,所设计的全智能体方法相比粒子群算法、遗传算法的电力系统重构更能保证船舶电力系统的安全运行,且具有电力系统故障时重构功率损耗更小、开关效率更高的优点;进一步提高了船舶电力系统的安全可靠性。

    Abstract:

    In order to ensure that the main electric propulsion power system do not lose power for the shipboard power system under fault condition, the shipboard power system topology reconfiguration method is studied. Based on the intelligent agent theory, a kind of all agent based reconfiguration method is established. This method is composed of intelligent environment perception, belief generator, target control and the particle swarm optimal decision. Reconfiguration strategies are used to ensure the uninterrupted power supply, minimization of the shipboard power system loss and maximum of relay protection efficiency, etc. The simulation for a certain type power grid of electric propulsion shipboard distribution system under the three-phase short circuit conditions is conducted. Compared with the particle swarm particle algorithm and genetic algorithm from the simulation result, it shows that the proposed method can ensure the safety operation of the shipboard power system and also has the benefit of less power loss and higher switch efficient under power system fault condition. It can further improve the safety and reliability for shipboard power system.

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张威,施伟锋,胡红钱.船舶区域配电系统全智能体重构及其优化研究[J].电力系统保护与控制,2016,44(4):9-15.[ZHANG Wei, SHI Weifeng, HU Hongqian. Research on agent based reconfiguration and its optimization for shipboard zonal power systems[J]. Power System Protection and Control,2016,V44(4):9-15]

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  • 收稿日期:2015-03-09
  • 最后修改日期:2015-12-11
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  • 在线发布日期: 2016-02-03
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