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Real-time implementation of an intelligent algorithm for electric ship power system reconfiguration

机译:船舶电力系统重构智能算法的实时实现

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The naval electric ship is often subject to severe damages under battle conditions. The damages or faults might even affect the generators and as a result, critical loads might suffer from power deficiency which may lead to an eventual collapse of rest of the system. In order to serve the critical loads and maintain a proper power balance without excessive generation, the ship power system requires a fast reconfiguration of the remaining system under fault conditions. A fast intelligent algorithm using the Small Population based Particle Swarm Optimization (SPPSO) for dynamic reconfiguration of the available generators and loads when a fault in the ship power system is detected is presented in this paper. SPPSO is a variant of PSO which operates with fewer particles and a regeneration concept, where new potential solutions are generated every few iterations. This concept of regeneration makes the algorithm fast and enhances its exploration capability to a large extent. The strength of the proposed reconfiguration strategy is first illustrated with Matlab results and then with a real-time implementation on a real time digital simulator and a digital signal processor
机译:海军电动船经常在战斗条件下遭受严重破坏。损坏或故障甚至可能影响发电机,结果,关键负载可能会遭受功率不足的困扰,这可能导致系统其余部分最终崩溃。为了满足关键负载并保持适当的功率平衡而又不会产生过多的功率,船舶动力系统需要在故障情况下快速重新配置其余系统。本文提出了一种基于小种群的粒子群优化算法(SPPSO)的快速智能算法,用于在检测到船舶电力系统故障时对可用发电机和负荷进行动态重新配置。 SPPSO是PSO的变体,它使用较少的粒子并具有再生概念,每隔几次迭代就会生成新的潜在解决方案。再生的概念使算法更快,并在很大程度上增强了其探索能力。首先通过Matlab结果说明了所提出的重新配置策略的优势,然后在实时数字仿真器和数字信号处理器上进行了实时实现

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