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

P. Mitra, G. Venayagamoorthy
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引用次数: 10

Abstract

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.
船舶电力系统重构智能算法的实时实现
海军电动船在战斗条件下经常受到严重的损坏。损坏或故障甚至可能影响发电机,因此,关键负载可能遭受电力不足,这可能导致系统的其余部分最终崩溃。船舶电力系统需要在故障情况下对剩余系统进行快速重构,以服务于临界负荷并保持适当的功率平衡。提出了一种基于小种群粒子群优化的船舶电力系统故障动态重构快速智能算法。SPPSO是PSO的一种变体,它使用更少的粒子和再生概念,每隔几次迭代就会产生新的潜在解决方案。这种再生的概念使得算法速度很快,在很大程度上增强了算法的探索能力。首先用Matlab结果说明了所提出的重构策略的强度,然后在实时数字模拟器和数字信号处理器上进行了实时实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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