Simulation Studies of Adaptive Predictive Control for Small Hydro Power Plant

Z. Zidane, M. A. Lafkih, M. Ramzi
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引用次数: 4

Abstract

Small hydro power is one of the most important renewable energy in the world. It does not encounter the problem of population displacement and is not as expensive as solar or wind energy. However, small hydro electrical generating units are usually isolated fro m the grid network; thus, they require control to maintain of constant the power for any working conditions. This paper presents a flow control approach for the speed control of hydro turbines. Power can be controlled by controlling the amount volume of water running into turbine. In this study, the adaptive predictive control is designed to control a flow for the automatic control of s mall hydro power plants. The standard Generalized Predictive Control (GPC) algorith m is presented. The Adaptive Generalized Predictive Control is then applied to achieve set point tracking of the output of the plant. A Single Input Single Output (SISO) model is used for control purposes. The model parameters are estimated on-line using an identification algorith m based on Recursive Least Squares (RLS) method. The performance of the proposed controller is illustrated by a simulation examp le of Small hydro power plant. Obtained results have shown better characteristics concerning both set point tracking and disturbance robustness for adaptive predictive control.
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小水电厂自适应预测控制仿真研究
小水电是世界上最重要的可再生能源之一。它不会遇到人口流离失所的问题,也不像太阳能或风能那样昂贵。然而,小型水力发电机组通常与电网隔离;因此,他们需要控制,以保持恒定的功率在任何工作条件。本文提出了一种用于水轮机调速的流量控制方法。功率可以通过控制进入涡轮机的水量来控制。本文针对5座小型水电厂的自动控制,设计了自适应预测控制系统。提出了标准的广义预测控制(GPC)算法。然后应用自适应广义预测控制实现对对象输出的设定值跟踪。单输入单输出(SISO)模型用于控制目的。采用基于递推最小二乘(RLS)方法的辨识算法m在线估计模型参数。通过小水电厂的仿真算例说明了所提控制器的性能。结果表明,自适应预测控制具有较好的设定值跟踪和扰动鲁棒性。
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