發(fā)布時間：2018-02-20 17:09

  本文關(guān)鍵詞： 火力發(fā)電 負荷分配 多目標(biāo)優(yōu)化 動態(tài)規(guī)劃 自適應(yīng)網(wǎng)格 多屬性決策　出處：《東北大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著我國電力體制改革的不斷深化,“廠網(wǎng)分開,競價上網(wǎng)”機制的推行,使發(fā)電企業(yè)從生產(chǎn)型企業(yè)轉(zhuǎn)變?yōu)榻?jīng)營型企業(yè),電廠作為獨立的經(jīng)濟實體參與市場競爭,電網(wǎng)不再對單元機組下發(fā)負荷指令,而是對電廠中所有機組下發(fā)總的負荷指令。因此,科學(xué)合理地分配每臺機組的負荷,將有利于優(yōu)化機組的運行水平,有利于降低全廠的供電煤耗,為發(fā)電廠在電力市場中競價上網(wǎng)提供科學(xué)依據(jù)。同時,國家的對企業(yè)的節(jié)能減排和可持續(xù)發(fā)展政策,也給發(fā)電企業(yè)帶來了新的要求�；痣姀S在發(fā)電過程中會產(chǎn)生大量有害氣體,對環(huán)境造成嚴重的污染,污染物排放已成為火電廠機組負荷分配中不可忽略的因素。因此,電廠機組負荷優(yōu)化分配問題的研究具有非常重大的現(xiàn)實意義。本文介紹了機組負荷優(yōu)化分配的基本概念,根據(jù)國內(nèi)外機組負荷分配的研究現(xiàn)狀,并結(jié)合火電廠機組的實際運行情況,選定供電煤耗作為負荷分配的經(jīng)濟性指標(biāo),確定單元機組的供電煤耗特性曲線是火電廠機組負荷優(yōu)化分配的基礎(chǔ),采用最小二乘法對單元機組的煤耗特性曲線進行擬合。在對單目標(biāo)負荷優(yōu)化分配算法的研究中,利用機組的煤耗特性曲線建立了基于經(jīng)濟性的單目標(biāo)負荷優(yōu)化分配數(shù)學(xué)模型,然后詳細介紹了等微增率法和動態(tài)規(guī)劃法應(yīng)用于負荷優(yōu)化分配的方法,并對比了它們的特點,選用動態(tài)規(guī)劃法作為單目標(biāo)負荷優(yōu)化分配算法,并對算法進行詳細的設(shè)計和說明。算例結(jié)果表明,動態(tài)規(guī)劃法可以在一定程度上優(yōu)化全廠機組的運行,從而降低全廠煤耗,保證了機組負荷分配的經(jīng)濟性。本文在單目標(biāo)優(yōu)化模型基礎(chǔ)上,進一步考慮減排目標(biāo),建立了基于環(huán)境和經(jīng)濟的多目標(biāo)負荷優(yōu)化分配模型,設(shè)計了基于自適應(yīng)網(wǎng)格的多目標(biāo)粒子群算法,并對該算法得到的Pareto解集進行多屬性決策,得到最滿意的負荷分配方案。對基于自適應(yīng)網(wǎng)格的多目標(biāo)粒子群算法的設(shè)計主要包括：對等式約束和不等式約束的處理；自適應(yīng)網(wǎng)格法對Pareto外部檔案的維護；粒子個體最優(yōu)位置和全局最優(yōu)位置的選取。文中通過實例計算,將實驗結(jié)果與基于遺傳算法的多目標(biāo)優(yōu)化算法比較,驗證了該方法的有效性。文中對多目標(biāo)算法產(chǎn)生的Pareto解集的多屬性決策,首先采用客觀賦權(quán)的信息熵法對經(jīng)濟和環(huán)境兩個屬性進行權(quán)值計算,然后用逼近理想解的排序方法(TOPSIS)對Pareto解集給出排序,得到最滿意的解。本文還將上述機組負荷優(yōu)化分配方法應(yīng)用到某火電廠生產(chǎn)運營管理系統(tǒng)中,搭建了基于Flex+Spring+Hibernate的系統(tǒng)框架,設(shè)計了簡潔美觀的界面,實現(xiàn)了機組負荷基礎(chǔ)數(shù)據(jù)的管理、機組煤耗特性曲線的擬合、機組單目標(biāo)負荷優(yōu)化分配和多目標(biāo)優(yōu)化分配,提高了企業(yè)的管理和生產(chǎn)效率,為企業(yè)帶來了經(jīng)濟效益。
[Abstract]:With the deepening of China's electric power system reform, the implementation of the mechanism of "separation of power plants from power plants and power grids, bidding for the Internet" has transformed power generation enterprises from production-oriented enterprises to profit-oriented enterprises, and power plants, as independent economic entities, have participated in market competition. The power network no longer issues the load instruction to the unit unit, but issues the total load instruction to all the units in the power plant. Therefore, the scientific and reasonable distribution of the load of each unit will help to optimize the operation level of the unit. It will help to reduce the coal consumption of the whole plant, and provide the scientific basis for the power plants to compete for electricity in the electricity market. At the same time, the national policies on energy saving and emission reduction and sustainable development of enterprises, Thermal power plants will produce a large number of harmful gases in the process of generating electricity, which will cause serious pollution to the environment, and pollutant emission has become a factor that can not be ignored in the load distribution of thermal power plants. It is of great practical significance to study the optimal load distribution of power plant units. This paper introduces the basic concept of unit load optimal distribution, according to the research status of unit load distribution at home and abroad. Combined with the actual operation of thermal power plant, the coal consumption of power supply is selected as the economic index of load distribution, and the characteristic curve of power supply coal consumption of unit is the basis of optimal load distribution of power plant. The coal consumption characteristic curve of the unit is fitted by the least square method. In the study of the single objective load distribution algorithm, a single objective load optimal distribution mathematical model based on economy is established by using the coal consumption characteristic curve of the unit. Then, this paper introduces in detail the methods of load optimal distribution using the equal differential rate method and dynamic programming method, and compares their characteristics, and chooses dynamic programming method as the single objective load allocation algorithm. The algorithm is designed and explained in detail. The results show that the dynamic programming method can optimize the operation of the whole plant to a certain extent, thus reducing the coal consumption of the whole plant. On the basis of single objective optimization model and considering emission reduction target, a multi-objective load distribution model based on environment and economy is established in this paper. A multi-objective particle swarm optimization algorithm based on adaptive mesh is designed, and the Pareto solution set obtained by the algorithm is used for multi-attribute decision making. The design of multi-objective particle swarm optimization algorithm based on adaptive mesh mainly includes the processing of equal constraints and inequality constraints, the maintenance of Pareto external files by adaptive mesh method. In this paper, the experimental results are compared with the multi-objective optimization algorithm based on genetic algorithm. The effectiveness of this method is verified. In this paper, for the multi-attribute decision of the Pareto solution set generated by the multi-objective algorithm, the weights of the economic and environmental attributes are calculated by the objective weighted information entropy method. Then the Pareto solution set is sorted by using the ranking method of approximating the ideal solution, and the most satisfactory solution is obtained. In this paper, the optimal load distribution method of the unit is also applied to the production and operation management system of a thermal power plant. The system frame based on Flex Spring Hibernate is built, and the simple and beautiful interface is designed. The management of basic data of unit load, the fitting of unit coal consumption characteristic curve, the optimization of unit single objective load distribution and multi-objective optimization distribution are realized. It improves the management and production efficiency of the enterprise and brings economic benefits to the enterprise.
【學(xué)位授予單位】：東北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM621

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本文編號：1519528