汽轮机组变工况特性分析与优化研究

发布时间：2018-01-04 05:07

本文关键词：汽轮机组变工况特性分析与优化研究　出处：《东南大学》2015年硕士论文　论文类型：学位论文

【摘要】：火电厂是一次能源耗费大户,为保证火电厂在同行业中的竞争力,适应国家的可持续发展战略要求,需要对发电企业的运行特性以及优化进行深入研究。为此,本文以某电厂#8机组为研究对象,开展喷嘴配汽机组现场试验、动态特性建模、热经济性分析以及配汽优化等方面的相关工作。首先,进行对象机组的现场试验,包括汽机负荷阶跃响应试验、深度调峰试验以及快速调峰试验,得到汽机不同负荷下调节阀的阶跃响应特性,同时在保证机组运行安全的前提下通过快速升降负荷试验手动获得了高速调峰时允许的最快升降负荷速率,为同类机组提供了参考,并为后续建模、调试及优化工作提供试验数据。其次,基于APROS分析型支撑平台,利用机组设计数据建立汽轮机及其热力系统模型,并通过模型试验计算获得的机组动态特性与现场特性试验的数据进行对比,验证模型的可靠性。基于建立的APROS详细计算模型,针对不同典型工况定量分析对机组经济性的影响因素,包括初压、初温和背压,获得各因素对功率和热耗率的影响曲线以及修正曲线,为现场不同工况下的经济性分析提供参考。然后,通过详细的变工况计算获得调节阀的综合流量系数曲线以及调节阀和调节级的组合特性曲线,建立了其理论计算模型,并基于理论计算模型对仿真模型进行调节阀和调节级的调试,在以往重叠度研究的基础上,将仿真模型计算数据与现场调节阀特性试验数据进行对比验证仿真模型的可靠性。在此基础上,联合采用负荷和阀位的思想,对机组进行配汽优化研究,获得机组多种配汽方式下的热耗变化曲线,通过与现场实际运行数据对比表明优化的可行性,进而得到机组最佳配汽方式和最优初压曲线,并建立了机组热耗率随主汽压力变化的理论数学模型,其结论可用于指导机组现场试验,为现场实际运行曲线的进一步优化提供方向。针对对象机组背压受季节影响大的问题,根据机组最佳配汽方式基于所建模型获得机组最优初压曲线簇以及背压对主汽压力的逻辑修正参考曲线。最后,引进先进的萤火虫智能优化算法,探讨了其与标准粒子群算法在解决不同优化问题时的优劣,根据机组配汽优化前后获得的煤耗特性曲线,验证萤火虫算法相对于传统算法在解决此类问题上的有效性,并根据电网调度要求在机组不同最快升降负荷速率的限制下计算获得全厂的负荷经济分配方案。
[Abstract]:Thermal power plant is a major consumer of primary energy. In order to ensure the competitiveness of thermal power plants in the same industry and to meet the requirements of the national sustainable development strategy, the operation characteristics and optimization of power generation enterprises need to be studied in depth. In this paper, a power plant #8 unit as the research object, to carry out the nozzles steam distribution unit field test, dynamic characteristics modeling, thermal economic analysis and steam distribution optimization and other related work. The field test of the object unit including step response test of turbine load, deep peak-shaving test and fast peak-shaving test were carried out, and the step response characteristics of regulating valve under different loads were obtained. At the same time, under the premise of ensuring the operation safety of the unit, through the rapid lifting load test to manually obtain the fastest load rate allowed in the high speed peak-shaving, which provides a reference for the similar units, and for the subsequent modeling. Debugging and optimization work provides test data. Secondly, based on the APROS analytical support platform, the steam turbine and its thermodynamic system model are established by using the unit design data. The reliability of the model is verified by comparing the dynamic characteristics of the unit with the field characteristic test data. Based on the established APROS detailed calculation model. According to the influence factors of quantitative analysis on unit economy in different typical working conditions, including initial pressure, initial temperature and back pressure, the influence curves and correction curves of various factors on power and heat consumption rate were obtained. Then the comprehensive flow coefficient curve and the combined characteristic curve of regulating valve and regulating stage are obtained by detailed calculation of variable working conditions. The theoretical calculation model is established, and the simulation model is debugged based on the theoretical calculation model. Based on the previous research of overlap degree, the adjustment valve and the regulating stage of the simulation model are debugged. The reliability of the simulation model is verified by comparing the simulation model calculation data with the field control valve characteristic test data. On this basis, combined with the idea of load and valve position, the steam distribution optimization of the unit is studied. The change curves of heat consumption under various steam distribution modes are obtained, and the feasibility of optimization is proved by comparing with the actual operation data, and then the optimal steam distribution mode and the optimal initial pressure curve are obtained. The theoretical mathematical model of the heat consumption rate with the main steam pressure is established, and the conclusions can be used to guide the field test of the unit. It provides the direction for the further optimization of the actual operation curve on the spot, aiming at the problem that the back pressure of the object unit is greatly affected by the season. According to the optimal steam distribution mode of the unit, the optimal initial pressure curve cluster of the unit and the logical modified reference curve of the back pressure to the main steam pressure are obtained based on the established model. Finally, the advanced intelligent optimization algorithm of firefly is introduced. The advantages and disadvantages of PSO and PSO in solving different optimization problems are discussed, and the coal consumption characteristic curves before and after steam distribution optimization are obtained. The effectiveness of the firefly algorithm in solving this kind of problem is verified compared with the traditional algorithm, and the economic load distribution scheme of the whole plant is obtained according to the requirements of the power grid dispatching under the limitation of the different fastest load rate of the unit.
【学位授予单位】：东南大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TM621

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