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Adaptive neuro-fuzzy based AGC of hydro-thermal reheat deregulated power system

机译:基于自适应神经模糊的水热再热调节电力系统AGC

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With the increasing complexities and size of the electric power system, the gap between the electric power demand and generation is also becoming challenging. The wide and abrupt change in load consumptions results in frequency and voltage variations alongwith the variations in the power of the tieline. In order to tackle this problem, AGC plays a very significant role in centralised operation of the power system with the aim to reduce the transient deviations and make steady state error to zero. To make the power business profitable, the modern complex power system is restructured or deregulated taking into account the increasing competition. In a deregulated power system, private sectors manage the generation, transmission and distribution of the electrical power as a result of which AGC has been imposed with more significant roles. In this work, a hydro-thermal reheat based two area deregulated power system is being modelled and then the performance of the conventional controllers is being compared with the intelligent fuzzy controllers for different transaction cases.
机译:随着电力系统的复杂性和尺寸的增加,电力需求和发电之间的差距也变得具有挑战性。负载消耗的剧烈而突然的变化导致频率和电压的变化以及联络线功率的变化。为了解决这个问题,AGC在电力系统的集中运行中起着非常重要的作用,其目的是减少瞬态偏差并使稳态误差为零。为了使电力业务盈利,考虑到竞争的加剧,对现代复杂电力系统进行重组或放松管制。在放松管制的电力系统中,私人部门管理着电力的产生,传输和分配,因此,AGC被赋予了更重要的作用。在这项工作中,对基于水热再热的两区域失调电力系统进行建模,然后将常规控制器的性能与针对不同交易情况的智能模糊控制器进行比较。

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