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Predictive control strategy for a supercritical power plant and study of influences of coal mills control on its dynamic responses

机译:超临界发电厂的预测控制策略及煤磨厂控制对动力响应的影响研究

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The paper is to investigate dynamic responses of supercritical power plants (SCPP) and study the potential strategies for improvement of their responses for Grid Code compliance. An approximate mathematical model that reflects the main features of SCPP is developed. The model unknown parameters are identified using Genetic Algorithms (GA) and the model is validated over a wide operating range. A model based predictive control (MPC) is then proposed to speed up the dynamic responses of the power plant by adjusting the reference of the plant local controls instead of direct control signal applications. Simulation results have shown encouraging improvement in performance of the plant with no interference with its associated local controllers.
机译:本文是调查超临界发电厂(SCPP)的动态响应,并研究改进其对网格代码合规性的响应的潜在策略。开发了一种反映SCPP主要特征的近似数学模型。使用遗传算法(GA)识别模型未知参数,并且在宽的工作范围内验证模型。然后提出基于模型的预测控制(MPC)来加速电厂通过调整工厂本地控制的参考而不是直接控制信号应用来加速发电厂的动态响应。模拟结果表明,植物性能的令人震惊的改善,没有干扰其相关的本地控制器。

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