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Automatic generation control of interconnected hydro-thermal system in deregulated environment considering generation rate constraints

机译:考虑发电量约束的管制环境下互联水热系统的自动发电控制

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Automatic Generation Control (AGC) is an integral part of Energy Management System. It is required to be innovated for the adaptation of the market system with several kind of bidding strategies. This paper deals with the automatic generation control of interconnected hydro-thermal system in market based deregulated system. In this particular work hydro unit is considered with electric governor and thermal unit is considered with reheat turbine and mechanical governor. The primary purpose of the AGC is to balance the total system generation against system load and losses so that the desired frequency and power interchange with neighboring systems are maintained. Any mismatch between generation and demand causes the system frequency to deviate from scheduled value. Thus high frequency deviation may lead to system collapse. This necessitates an accurate and fast acting controller to maintain constant nominal frequency. The limitations of the conventional controls viz., Integral, PI, and PID are slow and lack of efficiency in handling system non-linearities. Which leads to develop a new Artificial Intelligence based control technique for AGC. In this paper both conventional and Artificial Intelligence technique viz. Fuzzy Logic, Artificial Neural Network and Neurofuzzy based novel approach of automatic generation control has been examined. Genetic algorithm has been used for all optimization purposes. System performance has been evaluated at various loading disturbances. Various responses due to various controllers have been compared at various loading disturbances.
机译:自动发电控制(AGC)是能源管理系统的组成部分。为了适应市场体系,需要采用多种招标策略进行创新。本文研究了基于市场的管制系统中互联水热系统的自动发电控制。在这个特殊的工作中,水力单元与电调速器一起考虑,而热力单元与再热汽轮机和机械调速器一起考虑。 AGC的主要目的是在整个系统发电量与系统负载和损耗之间取得平衡,从而保持与相邻系统的所需频率和功率交换。发电量和需求量之间的任何不匹配都会导致系统频率偏离计划值。因此,高频偏差可能会导致系统崩溃。这需要一个精确且快速起作用的控制器来维持恒定的标称频率。常规控制(即积分,PI和PID)的局限性是缓慢的,并且在处理系统非线性方面缺乏效率。这导致开发了一种新的基于AGC的基于人工智能的控制技术。在本文中,常规技术和人工智能技术都应运而生。研究了基于模糊逻辑,人工神经网络和神经模糊的自动发电控制新方法。遗传算法已用于所有优化目的。已在各种负载干扰下评估了系统性能。在各种负载干扰下,已经比较了由于各种控制器引起的各种响应。

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