本文選題：燃煤摻燒 + 物理規(guī)劃　； 參考：《華中科技大學(xué)》2014年碩士論文

【摘要】：近年來(lái)，我國(guó)火力發(fā)電機(jī)組因?yàn)槊弘姽┬杳艿戎T多因素逐漸開(kāi)始采用混煤摻燒，但不合理的摻燒和運(yùn)行方式可能給機(jī)組的安全經(jīng)濟(jì)運(yùn)行帶來(lái)問(wèn)題，也可能會(huì)導(dǎo)致SO2、氮氧化物等大氣污染物排放增加。本文的工作主要是為了解決上述問(wèn)題，保證配煤摻燒的安全經(jīng)濟(jì)環(huán)保性。 物理規(guī)劃方案被廣泛用于優(yōu)化設(shè)計(jì)領(lǐng)域，能反映設(shè)計(jì)者對(duì)目標(biāo)的偏好，對(duì)配煤?jiǎn)栴}采用物理規(guī)劃的方法，構(gòu)建起智能配煤的各項(xiàng)偏好函數(shù)，建立起摻燒方案的優(yōu)化模型，以鍋爐燃燒的安全性、經(jīng)濟(jì)性和環(huán)保性作為優(yōu)化目標(biāo)，在已知摻配煤種和機(jī)組運(yùn)行條件的情況下，求得用戶(hù)最滿(mǎn)意的配煤方案。對(duì)于配煤摻燒的效果建立在線(xiàn)評(píng)價(jià)模型，依靠電廠(chǎng)生產(chǎn)數(shù)字化管理系統(tǒng)(Supervisory InformationSystem, SIS)實(shí)時(shí)數(shù)據(jù)庫(kù)自動(dòng)、實(shí)時(shí)對(duì)摻燒的安全、經(jīng)濟(jì)、環(huán)保性做出評(píng)價(jià)，評(píng)價(jià)值能反映相同機(jī)組的燃燒效果相對(duì)優(yōu)良程度。以某電廠(chǎng)700MW的機(jī)組的實(shí)際運(yùn)行數(shù)據(jù)為例進(jìn)行了評(píng)價(jià)。 分磨摻燒是目前大型火力發(fā)電機(jī)組普遍采用的摻燒方式。在此方式下，配煤方案的執(zhí)行要具體到上倉(cāng)方案，不同的煤因其煤質(zhì)的不同，，著火、穩(wěn)燃、燃盡特性都不盡相同，所以不同的的上倉(cāng)方式摻燒效果也不同。采用案例推理的方式對(duì)上倉(cāng)方式及相應(yīng)的運(yùn)行優(yōu)化調(diào)整模式進(jìn)行學(xué)習(xí)和指導(dǎo)，是一種機(jī)器自學(xué)習(xí)的模式。采集SIS數(shù)據(jù)進(jìn)行自動(dòng)評(píng)價(jià)形成案例庫(kù)，運(yùn)行中更優(yōu)的案例會(huì)被學(xué)習(xí)，案例檢索到與當(dāng)前案例相似的歷史，提供歷史案例的學(xué)習(xí)模式，供當(dāng)前案例修正。對(duì)700MW的機(jī)組建立了實(shí)際運(yùn)行的案例庫(kù)，利用案例推理對(duì)實(shí)際運(yùn)行案例進(jìn)行上倉(cāng)方案和運(yùn)行優(yōu)化指導(dǎo)。 在此基礎(chǔ)上，建立分磨摻燒及運(yùn)行優(yōu)化專(zhuān)家支持系統(tǒng)。系統(tǒng)集成配煤優(yōu)化模型、綜合評(píng)價(jià)模型、案例庫(kù)優(yōu)化等模塊，對(duì)電廠(chǎng)運(yùn)行人員配煤摻燒工作進(jìn)行指導(dǎo)，促使配煤工作達(dá)到安全、經(jīng)濟(jì)、環(huán)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.
【學(xué)位授予單位】：華中科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TM621

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