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Dynamic optimization of start-up and load-increasing processes in power plants - methodology and application

机译:发电厂启动和载荷过程的动态优化 - 方法论和应用

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The fast start-up and load-increasing of power plants is a complex task involving several restrictions that have to be fulfilled simultaneously. An important restriction is the maximum allowed thermal stress of the steam generator pipes and thesteam turbines caused by temperature gradients.In this paper the start-up process is treated as a dynamic optimization problem. Any appropriate objective function can be used in this optimization problem. Examples include the minimization of fuel consumption, or the minimization of the time requiredto reach the desired load. The maximum allowable temperature and pressure gradients in major plant components appear as additional constraints.A general methodology for solving these problems is presented: The dynamic process model, consisting of first-order ordinary differential equations (ODEs) and algebraic equations, is discretized over the time horizon using well established methods for the solution of ODEs. Thus, the continuous dynamic optimization problem is transformed into a large-scale non-linear parameter optimization problem with up to 20,000 optimization parameters and constraints. Such parameter optimization problems can be solvedwith appropriate sequential quadratic programming (SQP) methods that have become available lately.The application of this method is demonstrated by optimizing the proof rapid load-increase in a single-pressure combined-cycle power ton the base of a simplified model.
机译:发电厂的快速启动和负载增加是一个复杂的任务,涉及必须同时满足的几种限制。一个重要的限制是蒸汽发生器管道的最大允许热应力和由温度梯度引起的蒸汽发生器管道的热应力。本文将启动过程视为动态优化问题。任何适当的目标函数都可以在该优化问题中使用。实例包括最小化燃料消耗,或者最小化所需的时间达到所需负载。主要植物组件中的最大允许温度和压力梯度显示为额外的约束。提出了用于解决这些问题的一般方法:由一阶常微分方程(ODES)和代数方程组成的动态过程模型被离散化使用成熟的方法来解决杂散的时间范围。因此,连续动态优化问题转换为大规模的非线性参数优化问题,最多可达20,000个优化参数和约束。这种参数优化问题可以解决适当的顺序二次编程(SQP)方法最近可用。通过优化单压缩循环电源吨的依据优化证明快速负荷 - 增加来证明该方法的应用简化模型。

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