首页> 外文会议>ASME international mechanical engineering congress and exposition;IMECE2011 >A GENETIC ALGORITHM FOR OPTIMIZING HEAT RECOVERY STEAM GENERATORS OF COMBINED CYCLE POWER PLANTS
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A GENETIC ALGORITHM FOR OPTIMIZING HEAT RECOVERY STEAM GENERATORS OF COMBINED CYCLE POWER PLANTS

机译:联合循环电厂热回收蒸汽发电机优化的遗传算法

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Improving performance of combined cycle power plants has been the target of numerous investigations. Most of the researchers have focused their attention on the heat recovery steam generator (HRSG), the connecting equipment between the gas turbine group and the steam section. On the other hand, almost all equipment in a combined cycle is a fairly standard design available from a manufacturer, while the HRSG is one of the few components that may be somewhat customized. In fact, the HRSG provides many different design options with respect to the layout of heat transfer sections and their operating parameters. The aim of this work is the development of a model for optimizing the main operating parameters of the heat recovery steam generator of a CCGT. The thermodynamic behaviour of the power plant has been simulated through the commercial software GateCycle, whereas the optimization has been carried out using a genetic algorithm. The objective function to be minimized is the cost of electricity, evaluated through a cash flow analysis in constant or in current dollars. Two CCGT power plant configurations, with one or three-pressure reheat HRSG, are simulated and optimized, evaluating the influence of fuel price variation on the optimal operating parameters of HRSG.
机译:提高联合循环发电厂的性能一直是众多调查的目标。大多数研究人员都将注意力集中在热回收蒸汽发生器(HRSG)上,燃气轮机组和蒸汽部分之间的连接设备。另一方面,综合循环中的几乎所有设备都是制造商可获得的标准设计,而HRSG是可能有些可能有些可以稍微定制的组件之一。事实上,HRSG相对于传热部分的布局及其操作参数提供了许多不同的设计选项。这项工作的目的是开发用于优化CCGT的热回收蒸汽发生器的主要操作参数的模型。通过商业软件Gatecycle模拟了发电厂的热力学行为,而优化已经使用遗传算法进行。要最小化的目标函数是电力成本,通过现金流分析以恒定或以当前美元进行评估。模拟和优化了两个CCGT发电厂配置,具有一个或三次压力再加热HRSG,评估燃料价格变化对HRSG最佳操作参数的影响。

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