火力发电厂水和蒸汽质量的循环化学监测仿真建模

IF 0.9 Q4 ENERGY & FUELS
O. V. Egoshina, S. K. Lukutina
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引用次数: 0

摘要

循环化学监控系统用于对电力设备在所有运行状态下(包括启动和停机)的水化学进行在线综合自动监控、分析、诊断和预测,以及对所服务工艺设备中的一个或多个工艺过程进行远程自动控制。制定了循环化学监测系统的基本要求。基于物料平衡、冷却剂离子成分和递归神经网络的数学模型已被开发和研究。通过这些数学模型,我们可以预测机组运行过程中的杂质浓度,从而防止水化学失效。基于无量纲系数,我们开发了一种在线质量评估算法,该算法可提供有关水化学条件的公平信息,并有助于检测影响水化学的故障。考虑到循环化学监测系统的要求,如可视化、交互性、报告、定制、可扩展性、连续性和简易性,基于一套算法开发了一个带有用户界面的模拟模型。该模型有助于电厂运行人员进行决策和预防电厂机组水化学故障,使我们能够实时监测电厂机组的工艺参数,分析统计数据,使用基于物料平衡、离子平衡和神经网络的算法预测参数。为帮助用户了解程序界面,我们还编写了用户手册。手册中简要介绍了系统结构,包括信息和诊断功能、记忆图的基本要素以及一组控制按钮。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Simulation Modelling of Cycle Chemistry Monitoring of Water and Steam Quality at Thermal Power Plants

Simulation Modelling of Cycle Chemistry Monitoring of Water and Steam Quality at Thermal Power Plants

Cycle chemistry monitoring systems are intended for online comprehensive automatic monitoring, analysis, diagnostics, and prediction of the water chemistry in power equipment in all regimes of its operation, including startups and shutdowns, as well as for remote automatic control of one or several processes in the serviced process facility. Basic requirements for cycle chemistry monitoring systems are formulated. Mathematical models, which are based on the material balance, ionic composition of the coolant, and recurrent neural networks, have been developed and studied. They enable us to predict the concentration of impurities along the power unit’s path to prevent failures of the water chemistry. An algorithm has been developed for online quality assessment, based on dimensionless coefficients that provide fair information on the water-chemistry conditions and help to detect failures affecting the water chemistry. A simulation model with a user interface has been developed based on a set of algorithms considering the requirements for cycle chemistry monitoring systems, such as visualization, interactivity, reporting, customization, scalability, continuity, and simplicity. The model facilitates the activities performed by the operational personnel of power plants as to decision-making and prevention of failures of the water chemistry of the power unit, enables us to monitor the process parameters of the power unit in real time, analyze statistical data, predict parameters using algorithms on the basis of the material balance, ionic equilibriums, and neural networks. A user manual has been prepared to help one to understand the program interface. The manual contains a brief description of the system structure, including information and diagnostic functions, basic elements of the mnemonic diagram, and a set of control buttons.

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来源期刊
CiteScore
1.30
自引率
20.00%
发文量
94
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