700MW火电机组分磨掺烧及运行优化专家支持系统开发

发布时间：2018-06-03 19:38

本文选题：燃煤掺烧 + 物理规划　；参考：《华中科技大学》2014年硕士论文

【摘要】：近年来，我国火力发电机组因为煤电供需矛盾等诸多因素逐渐开始采用混煤掺烧，但不合理的掺烧和运行方式可能给机组的安全经济运行带来问题，也可能会导致SO2、氮氧化物等大气污染物排放增加。本文的工作主要是为了解决上述问题，保证配煤掺烧的安全经济环保性。物理规划方案被广泛用于优化设计领域，能反映设计者对目标的偏好，对配煤问题采用物理规划的方法，构建起智能配煤的各项偏好函数，建立起掺烧方案的优化模型，以锅炉燃烧的安全性、经济性和环保性作为优化目标，在已知掺配煤种和机组运行条件的情况下，求得用户最满意的配煤方案。对于配煤掺烧的效果建立在线评价模型，依靠电厂生产数字化管理系统(Supervisory InformationSystem, SIS)实时数据库自动、实时对掺烧的安全、经济、环保性做出评价，评价值能反映相同机组的燃烧效果相对优良程度。以某电厂700MW的机组的实际运行数据为例进行了评价。分磨掺烧是目前大型火力发电机组普遍采用的掺烧方式。在此方式下，配煤方案的执行要具体到上仓方案，不同的煤因其煤质的不同，，着火、稳燃、燃尽特性都不尽相同，所以不同的的上仓方式掺烧效果也不同。采用案例推理的方式对上仓方式及相应的运行优化调整模式进行学习和指导，是一种机器自学习的模式。采集SIS数据进行自动评价形成案例库，运行中更优的案例会被学习，案例检索到与当前案例相似的历史，提供历史案例的学习模式，供当前案例修正。对700MW的机组建立了实际运行的案例库，利用案例推理对实际运行案例进行上仓方案和运行优化指导。在此基础上，建立分磨掺烧及运行优化专家支持系统。系统集成配煤优化模型、综合评价模型、案例库优化等模块，对电厂运行人员配煤掺烧工作进行指导，促使配煤工作达到安全、经济、环保的效果。
[Abstract]:In recent years, because of many factors such as the contradiction between supply and demand of coal and electricity, coal-fired units in our country have gradually started to use mixed coal burning, but the unreasonable mixing burning and operation mode may bring problems to the safe and economic operation of the units. It may also lead to an increase in emissions of air pollutants such as so _ 2 and no _ x. The main purpose of this paper is to solve the above problems and to ensure the safety, economy and environmental protection of blending coal. The physical planning scheme is widely used in the field of optimization design, which can reflect the preference of the designer to the target, adopt the method of physical planning to solve the coal blending problem, construct the various preference functions of intelligent coal blending, and establish the optimization model of the blending scheme. Taking the safety, economy and environmental protection of boiler combustion as the optimization objective, the most satisfactory coal blending scheme is obtained under the conditions of known blending coal types and operating conditions of the unit. An online evaluation model for the effect of blending coal combustion is established, which depends on the automatic real-time database of Supervisory Information system (SISs), a power plant production digital management system, to evaluate the safety, economy and environmental protection of mixed coal combustion in real time. The evaluation value can reflect the relatively good degree of combustion effect of the same unit. Taking the actual operation data of 700MW unit in a power plant as an example, the evaluation is carried out. Mixed grinding is widely used in large-scale thermal power generating sets at present. In this way, the implementation of coal blending scheme should be specific to the silo plan, different coal because of its different coal quality, ignition, stable combustion, burnout characteristics are not the same, so different silo blending effect is also different. Case-based reasoning (CBR) is a kind of machine self-learning mode. The case base is formed by collecting SIS data for automatic evaluation, and the better cases will be learned in operation. The case will be retrieved to the history similar to the current case, and the learning model of historical case will be provided for the revision of the current case. The case base of actual operation is established for the unit of 700MW, and the plan of loading warehouse and the guidance of operation optimization are carried out by case-based reasoning (CBR). On the basis of this, the expert support system of mixed burning and operation optimization is established. The system integrated coal blending optimization model, comprehensive evaluation model, case base optimization and other modules to guide the coal blending of power plant operators to achieve safety, economic and environmental protection results.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM621

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