百万超超临界机组汽轮机抽汽回热系统能效评价与诊断的研究

发布时间：2018-10-16 11:12

【摘要】：汽轮机抽汽回热系统节能优化的核心和难点在于抽汽回热系统能效指标基准状态的确定。复杂多变的边界条件以及能效指标间的耦合问题给汽轮机抽汽回热系统的节能优化研究带来了很大的挑战。目前,汽轮机抽汽回热系统关键能效指标的基准值确定往往仅仅采用设计值、变工况计算值或者热力试验值,每种基准值确定方法都有其局限性。随着机组运行工况变化和设备性能状态的改变,基准值已无法匹配抽汽回热系统的实际运行状态,使得运行指导受到很大限制,无法发现引起能效水平降低的真正原因。基于汽轮机抽汽回热系统海量历史数据的数据挖掘方法能够较好地匹配机组的实际运行状态,因此能够很好地确定目标工况下抽汽回热系统实际可达的能效指标基准状态。针对目前抽汽回热系统数据挖掘中面临的多变复杂的边界条件,多且耦合的能效指标以及指标差异的问题。本文通过基于k-means聚类的数据挖掘方式提取出目标工况下抽汽回热系统实际可达的能效指标基准状态。但是基于数据挖掘得到的能效指标基准状态受到运行边界条件和实际设备状态的影响,主要反映的是操作人员运行水平的高低,而没有反映出目标工况下设备性能的基准状态。因此,本文结合抽汽回热系统实际情况通过进一步构建设备性能类指标的基准状态模型,对挖掘得到的反映设备性能的能效指标进行修正,从而得到整个汽轮机抽汽回热系统能效指标实际可达的基准状态,完成了关键能效指标的耗差因子分析,同时采用基于机理与Ebislon仿真建模的方法完成了端差及给水温度的基准值及耗差因子的验证,从而为汽轮机抽汽回热系统不同工况的能耗分析与能效诊断提供依据。最后,本文基于抽汽回热系统能效指标基准状态的研究,对抽汽回热系统能效分析、评价与诊断系统展开了设计研究工作。对某1000MW汽轮机回热系统组通过耗差因子分析找到影响该抽汽回热系统能耗的主要能效指标,基于能效指标的优化知识库,指导能效指标的优化调整,最终达到提高抽汽回热系统能效水平的目的。
[Abstract]:The core and difficulty of energy saving optimization of steam turbine extraction recuperation system lies in the determination of the benchmark state of energy efficiency index of extraction steam recovery system. The complex boundary conditions and the coupling problem between energy efficiency indexes have brought great challenges to the optimization of energy conservation of steam turbine extraction heat recovery system. At present, the reference value of the key energy efficiency index of steam turbine extraction recuperation system is usually determined only by the design value, the calculation value under off-condition or the thermal test value, and each method has its limitations. With the change of unit operating condition and equipment performance state, the reference value can not match the actual operation state of the extraction steam recovery system, so the operation guidance is greatly restricted, and the real cause of the reduction of energy efficiency level can not be found. The data mining method based on the massive historical data of steam turbine extraction recuperation system can well match the actual operating state of the unit, so it can determine the actual energy efficiency index reference state of the extraction regenerative system under the target working condition. In order to solve the problem of variable and complex boundary conditions, multiple coupled energy efficiency indexes and different indexes in data mining of extraction steam recuperation system. In this paper, the data mining method based on k-means clustering is used to extract the actual energy efficiency standard state of the extraction regenerative system under the target working condition. But the datum state of energy efficiency index based on data mining is affected by the operation boundary condition and the actual equipment state, which mainly reflects the operating level of the operator, but does not reflect the standard state of the equipment performance under the target working condition. Therefore, according to the actual situation of the extraction heat recovery system, this paper modifies the energy efficiency index which can reflect the equipment performance by further constructing the benchmark state model of the equipment performance index. Thus, the reference state of the energy efficiency index of the whole steam turbine recovery system is obtained, and the consumption difference factor analysis of the key energy efficiency index is completed. At the same time, based on mechanism and Ebislon simulation modeling method, the standard value and consumption factor of end difference and feed water temperature are verified, which provides the basis for energy consumption analysis and energy efficiency diagnosis of steam turbine recovery system under different working conditions. Finally, based on the research of the energy efficiency benchmark state of the extraction steam recovery system, the energy efficiency analysis, evaluation and diagnosis system of the extraction steam recovery system are designed and studied. The main energy efficiency indexes affecting the energy consumption of the recovery system of a 1000MW steam turbine are found through the analysis of the consumption difference factor. The optimization knowledge base based on the energy efficiency index is used to guide the optimization and adjustment of the energy efficiency index. Finally, the purpose of improving the energy efficiency of the extraction steam recuperator system is achieved.
【学位授予单位】：华北电力大学(北京)
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM621.3

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