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A Novel Swarm Optimization Algorithm for Optimal Performance of NPC Rectifiers

机译:NPC整流器最佳性能的新型群优化算法

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With steps towards green energy, the demand of electric vehicles has increased in recent years. The electric vehicle charging is the trending research area including all the interdisciplinary fields. The neutral point clamped (NPC) rectifiers play crucial role in charging, power handling and enhancing the performance of the electric vehicle charging stations. The increase in dc and non linear loads, causes the problem of power quality in the ac side of three level NPC Rectifiers. Also, the NPC rectifier faces the problem of variations in the neutral point voltages, which is a great cause of concern for optimal charging of DC link capacitors. The paper proposes implementation of a novel swarm optimization algorithm (NSOA) based on cloud travel phenomena in Balanced Decoupled Controller (BDC) of NPC rectifiers to achieve optimal and robust performance. The NSOA comparison with standard Particle Swarm Optimization (PSO) algorithm is done on standard test function. Further, using proposed NSOA algorithm the optimized control parameters are obtained for balanced decoupled controller of NPC rectifier. The reliable performance of NPC rectifiers is validated using the MATLAB simulations results.
机译:随着对绿色能源的措施,电动车的需求在最近几年有所增加。电动车充电是包括所有的跨学科领域的趋势的研究领域。钳位(NPC)整流器中性点充电,功率处理能力,提高电动汽车充电站的表现起到至关重要的作用。在DC和非线性负载的增加,导致三级NPC整流器的交流侧电能质量的问题。此外,NPC整流器面临的中性点电压,这是值得关注的直流母线电容器的最佳充电大业变化的问题。本文提出了实施新群优化算法的基础上平衡解耦控制器(BDC)云旅游现象(NSOA)的NPC整流器以达到最佳的和强大的性能。与标准的粒子群优化(PSO)算法的NSOA比较是在标准测试函数来完成。此外,使用提出NSOA算法优化控制参数是针对NPC整流器的平衡解耦控制器获得。 NPC整流器的性能可靠使用MATLAB仿真结果验证。

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