Neuro-fuzzy system for power generation quality improvements

A. Sallama, M. Abbod, P. Turner
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引用次数: 4

Abstract

This paper describes the design and implementation of advanced Power Stability System Controller (PSSC) using neuro-fuzzy system, the controller is taught from data generated by simulating the system for the optimal control regime. The controller is compared to a multi-band control system which is utilized to stabilize the system for different operating conditions. Simulation results shows that the fuzzy logic controller has produced better control action in stabilizing the system for conditions such as: normal, after disturbance in the electrical national grid as a result of changing of the plant capacity like renewable energy units or in the worst case of fault operating conditions, e.g. phase short circuit to ground. The new controller led to making the settling time and overshoot proved to be lower which means that the system can reach to stability is the shortest time and with minimum disruption. Such behaviour will improve the quality of the provided power to the national grid.
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用于发电质量改进的神经模糊系统
本文介绍了一种基于神经模糊系统的先进电力稳定系统控制器(PSSC)的设计与实现,该控制器通过模拟系统产生的数据来获得最优控制状态。将该控制器比作一个多波段控制系统,用于在不同运行条件下稳定系统。仿真结果表明,模糊控制器在正常情况下、可再生能源机组等电厂容量变化引起的国家电网扰动后,以及相接地短路等最坏的故障运行情况下,都能产生较好的稳定系统的控制作用。该控制器使系统的稳定时间和超调量都较低,从而使系统在最短的时间内以最小的干扰达到稳定。这种行为将提高向国家电网提供电力的质量。
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