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Survey on Intelligent Control Approaches for Prediction of Boiler Efficiency in Thermal Power Plant

机译:智能控制方法在火电厂锅炉效率预测中的应用

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Thermal power plant consumes large amount of coal to generate heat and electricity. Scarcity of coal targets energy saving and emission reduction. Optimal usage of coal in boiler of thermal plant can be achieved through accurate values of boiler operation parameters. Power plant operator faces the challenge of examining the data and evaluates these values for optimal performance of the plant operation. Usage of theory of thermodynamics in complex, uncertain, non-stable, inertial, time-delaying, and nonlinear of combustion process is difficult. Hence, many researchers proposed expert systems (called as combustion model of the boiler) to monitor and control the run-time efficiency and heat rate of the boiler and to suggest appropriate actions for the operation. Recent, expert system used to model the thermal efficiency of the pulverized coal furnace are mainly based on intelligent control approaches. In this paper, we categorize all up-to-date and published works based on current intelligent control approaches for prediction of boiler efficiency into three groups' rule-based expert systems, soft-computing techniques and hybrid system. Their findings and important contributions are highlighted.
机译:火力发电厂消耗大量的煤炭来产生热量和电力。煤炭稀缺的目标是节能减排。通过精确地设定锅炉运行参数,可以实现热电厂锅炉中煤炭的最佳利用。电厂运营商面临着检查数据和评估这些值以实现电厂运营最佳性能的挑战。在复杂,不确定,不稳定,惯性,时滞和非线性的燃烧过程中很难使用热力学理论。因此,许多研究人员提出了专家系统(称为锅炉的燃烧模型)来监视和控制锅炉的运行时效率和热量率,并提出适当的操作建议。最近,用于建模煤粉炉热效率的专家系统主要基于智能控制方法。在本文中,我们将基于当前用于预测锅炉效率的智能控制方法的所有最新和已发表的著作归类为三组基于规则的专家系统,软计算技术和混合系统。他们的发现和重要贡献突出。

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