本文關(guān)鍵詞：電力系統(tǒng)經(jīng)濟調(diào)度及其多目標(biāo)優(yōu)化研究　出處：《華南理工大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 電力系統(tǒng)經(jīng)濟調(diào)度 多目標(biāo)優(yōu)化 非凸模型 混合整數(shù)規(guī)劃 線性近似

【摘要】：隨著我國經(jīng)濟的快速發(fā)展,我國對電能的需求量持續(xù)上升,與此同時,電力工業(yè)作為化石能源消耗和污染物排放的大戶,在節(jié)能減排上受到政府的嚴(yán)格管控。在此背景下,如何合理地分配電能,并兼顧由電力發(fā)展引起的環(huán)境問題,已成為電力系統(tǒng)調(diào)度領(lǐng)域的一個重要問題。為了更全面地考慮不同應(yīng)用情景下的電力調(diào)度問題,本文首先提出了三種確定性的電力系統(tǒng)調(diào)度模型,然后針對每一種模型提出相應(yīng)的優(yōu)化方法,接著通過標(biāo)準(zhǔn)測試系統(tǒng)驗證本文所提出的方法的有效性。首先,針對電力系統(tǒng)靜態(tài)經(jīng)濟調(diào)度問題,提出了非凸的電力系統(tǒng)靜態(tài)經(jīng)濟調(diào)度模型。該模型考慮發(fā)電機組的閥點效應(yīng)、機組禁運區(qū)約束、網(wǎng)絡(luò)損耗、爬坡約束和旋轉(zhuǎn)備用約束等。引入上述復(fù)雜約束后,提高了模型的完整性,但增加了問題的求解難度。為了求解非凸的電力系統(tǒng)靜態(tài)調(diào)度模型,本文提出了三種優(yōu)化方法,包括基于拋物線模型的快速?迭代方法、基于線性迭代和緊湊形式的方法和基于兩階段混合整數(shù)規(guī)劃的方法,并通過四個標(biāo)準(zhǔn)測試系統(tǒng)的對比結(jié)果驗證上述三種方法的有效性。然后,本文提出了兩種電力系統(tǒng)動態(tài)經(jīng)濟調(diào)度模型,包括考慮發(fā)電機組閥點效應(yīng)的非凸電力系統(tǒng)動態(tài)經(jīng)濟調(diào)度模型和考慮直流網(wǎng)絡(luò)損耗的電力系統(tǒng)動態(tài)經(jīng)濟調(diào)度模型。第一種模型在非凸的電力系統(tǒng)靜態(tài)經(jīng)濟調(diào)度模型的基礎(chǔ)上,考慮了不同調(diào)度時段之間的機組爬坡約束,因此問題規(guī)模更大。針對該大規(guī)模高度非凸的優(yōu)化模型,本文提出了基于兩階段混合整數(shù)線性規(guī)劃的電力系統(tǒng)動態(tài)調(diào)度方法和基于線性近似和混合整數(shù)規(guī)劃的電力系統(tǒng)動態(tài)調(diào)度方法。此兩種方法的核心是通過線性近似技術(shù)和混合整數(shù)編碼技術(shù)將原非凸優(yōu)化問題轉(zhuǎn)化為混合整數(shù)規(guī)劃問題。為了更準(zhǔn)確模擬網(wǎng)絡(luò)損耗,本文在第二種模型中考慮了直流網(wǎng)絡(luò)損耗。針對第二種模型,本文結(jié)合約束松弛技術(shù)和懲罰技術(shù),提出了帶懲罰因子的混合整數(shù)二次約束二次規(guī)劃電力系統(tǒng)動態(tài)調(diào)度方法,并與直流最優(yōu)潮流方法、交流最優(yōu)潮流方法和分段線性化方法進行對比。最后,針對考慮經(jīng)濟性和排放的電力系統(tǒng)多目標(biāo)調(diào)度模型,本文提出了一種基于權(quán)重的兩階段電力系統(tǒng)多目標(biāo)調(diào)度優(yōu)化方法。該方法主要結(jié)合權(quán)重的思想,根據(jù)不同目標(biāo)的重要程度對各個目標(biāo)進行加權(quán),將多目標(biāo)優(yōu)化問題轉(zhuǎn)化為單目標(biāo)優(yōu)化問題。在40機組標(biāo)準(zhǔn)測試系統(tǒng)上的仿真表明,本文提出的基于權(quán)重的兩階段電力系統(tǒng)多目標(biāo)調(diào)度優(yōu)化方法能夠有效求解考慮經(jīng)濟性和排放的電力系統(tǒng)多目標(biāo)調(diào)度模型。
[Abstract]:With the rapid development of China's economy, the demand for electric energy in China has been rising. At the same time, the electric power industry as a major consumer of fossil energy consumption and pollutant emissions. Energy saving and emission reduction is strictly controlled by the government. In this context, how to distribute electricity reasonably and take into account the environmental problems caused by the development of electricity. It has become an important problem in the field of power system dispatching. In order to consider the power dispatching problem in different application scenarios more comprehensively, three kinds of deterministic power system dispatching models are proposed in this paper. Then the corresponding optimization method is proposed for each model, and then the effectiveness of the proposed method is verified by the standard test system. Firstly, the static economic dispatch problem of power system is studied. A non-convex static economic dispatching model of power system is proposed, which takes into account the valve point effect of generating set, the constraint of unit embargoed zone, the network loss, the constraint of climbing slope and the constraint of rotating reserve, etc. The complex constraints mentioned above are introduced into the model. The integrity of the model is improved, but the difficulty of solving the problem is increased. In order to solve the non-convex static dispatching model of power system, this paper proposes three optimization methods, including the fast method based on parabola model. The iterative method is based on linear iteration and compact form method and based on two-stage mixed integer programming method. The effectiveness of the above three methods is verified by the comparison of four standard test systems. In this paper, two kinds of dynamic economic dispatching models of power system are proposed. The dynamic economic dispatching model of non-convex power system considering the valve point effect of generator set and the dynamic economic dispatching model of power system considering DC network loss are included. The first model is static economic dispatching model in non-convex power system. On the basis of. Considering the constraints of unit climbing between different scheduling periods, the scale of the problem is larger. For this large-scale non-convex optimization model. In this paper, a power system dynamic scheduling method based on two-stage mixed integer linear programming and a power system dynamic scheduling method based on linear approximation and mixed integer programming are proposed. The core of these two methods is linear approximation. In order to simulate the network loss more accurately, the original non-convex optimization problem is transformed into a mixed integer programming problem by using the hybrid integer coding technique and the hybrid integer coding technique. In this paper, the loss of DC network is considered in the second model. For the second model, the constraint relaxation technique and the penalty technique are combined in this paper. A hybrid integer quadratic constrained quadratic programming power system dynamic scheduling method with penalty factor is proposed and compared with DC optimal power flow method AC optimal power flow method and piecewise linearization method. Aiming at the multi-objective dispatching model of power system considering economy and emission, a two-stage multi-objective scheduling optimization method based on weight is proposed in this paper. This method mainly combines the idea of weight. According to the importance of different targets, the multi-objective optimization problem is transformed into a single-objective optimization problem, and the simulation results on the standard test system of 40 units show that the multi-objective optimization problem can be transformed into a single-objective optimization problem. In this paper, a weighted multi-objective scheduling optimization method for two-stage power system is proposed, which can effectively solve the multi-objective scheduling model of power system considering economy and emissions.
【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：TM73

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