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Integrated Technologies for Improved Plant Performance and Availability: Application of First Principles and Empirical Modeling Technologies

机译:综合技术,提高植物绩效及可用性:第一次原则和经验造型技术的应用

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FirstEnergy Corp. has recently selected and installed first principles thermodynamic models and empirical, advanced-pattern recognition-based models to monitor and predict the capacity, efficiency and condition of the units, systems and equipment in its 16-unit/7-site fleet of coal-fired supercritical power plants. This single software platform will be used at both the plants and at the new Information Diagnostic Evaluation and Analysis (IDEA) Center to continually improve the reliability, availability and efficiency of these power stations.First principles power plant thermodynamic models are developed for verifying plant design, establishing performance benchmarks, and evaluating current operating data and, in many cases, conducting performance tests. These models are then used to determine the cost of off-design operation, identify load-limiting factors, and quantify the effects of degradation of key plant equipment. Empirical models, based on historical operating plant data, are effective at identifying abnormal operating conditions, equipment degradation, and faulty instrument indications thereby providing information for condition-based maintenance. Models based on Advanced Pattern Recognition (APR) tend to be less susceptible to instrument errors and are particularly effective at identifying equipment problems well before a catastrophic upset.FirstEnergy has been using independent systems that incorporate most of the capabilities for years. Enhancement and integration of these technologies allows access to the raw data and calculated results in a single platform, substantially expanding their capability for advanced equipment diagnostics and accurate, actionable information. FirstEnergy is also leveraging these systems and key operations, engineering and maintenance expertise through the establishment of centralized monitoring and diagnostic center, the IDEA Center, located in Akron, Ohio, and piloting the same system at one of its nuclear plants through an internal Synergy Initiative.This presentation will provide an overview of the technologies utilized and present several case studies identifying the problems and issues identified by the system and FirstEnergy diagnostic team(s) and quantifying the benefits to FirstEnergy.
机译:Firstenergy公司最近选择并安装了第一个原理的热力学模型和基于经验,先进的模式识别的模型,以监控和预测其16单元/ 7站队列中的单位,系统和设备的容量,效率和条件燃煤超临界发电厂。该单一软件平台将在植物和新的信息诊断评估和分析(想法)中心使用,以不断提高这些电站的可靠性,可用性和效率。发电厂热力学模型是用于验证工厂设计的原理。 ,建立绩效基准,以及评估当前的操作数据,在许多情况下进行性能测试。然后使用这些模型来确定非设计操作的成本,识别有限因素,并量化关键植物设备的降解的影响。基于历史操作厂数据的经验模型在识别异常操作条件,设备劣化和故障仪器指示方面是有效的,从而为基于条件的维护提供信息。基于先进模式识别的模型(APR)往往不易受仪器错误的影响,并且在灾难性的镦粗之前识别设备问题特别有效.Firstenergy一直使用多年来包含大部分功能的独立系统。这些技术的增强和集成允许访问原始数据并在单个平台中计算结果,基本上扩展了他们的高级设备诊断和准确,可操作的信息的能力。 Firstenergy还利用这些系统和关键的运营,工程和维护专业知识,通过建立集中式监测和诊断中心,该中心,位于Akron,俄亥俄州,通过内部协同倡议在其核电站中的一家核电站试验相同的系统这篇文章将提供所使用的技术概述,并呈现了几个案例研究,确定了系统和Firstenergy诊断团队所识别的问题和问题并量化Firstenergy的福利。

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