Mohamed Omar, Wang Jihong, Khalil Ashraf, Limhabrash Marwan
Department of Electrical Engineering, Princess Sumaya University for Technology, P.O. Box 1438, Al-Jubaiha, 11941 Jordan.
School of Engineering, University of Warwick, Coventry, CV4 7AL UK.
Springerplus. 2016 Jul 4;5(1):980. doi: 10.1186/s40064-016-2679-2. eCollection 2016.
This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load-frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.
本文提出了一种将模型预测控制（MPC）应用于大型燃气轮机发电厂的新策略，作为我们研究进展的一部分，以提高电厂热效率和负荷频率控制性能。根据子空间辨识方法，以闭环数据作为辨识算法的输入，设计了涵盖整个稳定运行范围的大型燃气轮机广义状态空间模型。然后将该模型用于开发MPC，并集成到电厂现有的控制策略中。该策略的原理是，用MPC给出的优化决策来输入导阀、天然气阀和压缩机压力比控制器的参考信号，而不是直接应用控制信号。如果及时发送压缩机控制器和涡轮阀的设定点，电厂将有更多动能，从而在输出上实现更快响应，并提高整个系统效率。仿真结果表明了所提应用的可行性，该应用在频率变化和负荷跟踪能力方面取得了显著改善，与现有情况相比，整体联合循环热效率也提高了约1.1%。
