气体压缩机
燃气轮机
涡轮机
功率(物理)
联合循环
变量(数学)
汽车工程
控制理论(社会学)
机械工程
控制(管理)
工程类
计算机科学
数学
物理
热力学
数学分析
人工智能
作者
Qi’an Xie,Hu Wu,Liping Deng
标识
DOI:10.1177/09576509241254578
摘要
The variable geometry methods currently used in combined-cycle gas turbines are compressor variable inlet guide vanes (VIGV) or power turbine variable area nozzles (VAN). On this basis, this study presents the optimal variable geometry control strategy for compressor and power turbine combined adjustment ([Formula: see text]) using the Differential Evolutionary Algorithm with the LM2500+ gas turbine. The aim is to further improve the part-load performance of the combined-cycle gas turbine. Firstly, a part-load performance prediction model for variable geometry gas turbines is established based on the component method. Subsequently, a variable geometry gas turbine part-load performance optimization model is developed by combining the Differential Evolution Algorithm. Finally, the optimum combination of stagger angles for the compressor inlet vane and power turbine nozzle is calculated at each part-load condition. Compared to the VIGV and VAN control strategies, the [Formula: see text] control strategy proposed in this paper shows a higher stability margin and better economy. The [Formula: see text] control strategy maintains a constant exhaust temperature within a part load range from 20% to 100% with the stability margin exceeding 14%. In comparison with the VAN control strategy, the fuel flow rate decreases by 1.152% at 45% relative load power and by 3.435% at 20.0% relative load power with the [Formula: see text] control strategy.
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