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

S. Thota, R. P. Mandi, S. Chaudhari
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Abstract

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.
火电厂锅炉效率预测智能控制方法研究
火力发电厂消耗大量的煤来产生热量和电力。煤炭短缺是节能减排的目标。通过锅炉运行参数的准确取值,可以实现火电厂锅炉煤的最优利用。电厂运营商面临着检查数据和评估这些值以实现电厂运行的最佳性能的挑战。热力学理论在复杂的、不确定的、不稳定的、惯性的、时滞的和非线性的燃烧过程中的应用是困难的。因此,许多研究者提出了专家系统(称为锅炉燃烧模型)来监测和控制锅炉的运行时效率和热率,并为运行提供适当的建议。目前,用于煤粉炉热效率建模的专家系统主要基于智能控制方法。在本文中,我们将所有基于当前锅炉效率预测智能控制方法的最新和已发表的研究成果分为基于规则的专家系统、软计算技术和混合系统三大类。他们的发现和重要贡献被强调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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