本文選題：機組組合 + 混合整數(shù)二階錐規(guī)劃�。� 參考：《廣西大學》2014年博士論文

【摘要】：考慮低碳環(huán)境下的碳交易和碳稅政策、權衡魯棒利潤和電價風險、合理制定含風電場發(fā)電機組的最優(yōu)調度方案,以期減少耗煤所排放的二氧化碳、消納風電波動的影響、降低發(fā)電成本,對大力推進節(jié)約型社會的建設,促進社會經(jīng)濟效益的進一步提高,具有顯著的理論意義和現(xiàn)實價值。然而,極其復雜的低碳政策、電價波動和風電波動等因素,以及它們之間的相互作用,導致現(xiàn)有的相關理論無法有效研究發(fā)電優(yōu)化調度問題。為此,本論文研究了低碳環(huán)境下基于成本和利潤的機組組合模型求解策略、考慮碳交易和碳稅的機組組合建模及求解、計及魯棒利潤和風險價值的發(fā)電優(yōu)化調度模型及求解、風場風電容量的分配方法、以及含風電波動和碳交易的機組組合模型及求解等系列問題。論文共分為六章,第一章為緒論,第二章至第五章為主要研究工作,第六章對全文進行了總結。本文主要研究成果如下：第二章討論了發(fā)電優(yōu)化調度的基于成本的機組組合模型和基于利潤的機組組合模型,并研究了兩個模型的求解策略。首先利用一個更緊的二階錐松弛方法將兩個模型的混合整數(shù)二次規(guī)劃形式轉化為混合整數(shù)二階錐規(guī)劃形式。進一步,提出二階錐線性化方法將混合整數(shù)二階錐規(guī)劃形式轉化為混合整數(shù)線性規(guī)劃形式。仿真結果表明,本文所構造的混合整數(shù)線性規(guī)劃模型是解決機組組合問題更好的求解策略,能獲得高質量的次優(yōu)解。第三章提出考慮碳交易和碳稅的發(fā)電優(yōu)化調度模型和求解方法,并對碳交易和碳稅機制進行了比較分析。首先,建立了基于碳交易的發(fā)電優(yōu)化調度模型,該模型不僅考慮了碳排放配額約束,同時也考慮了碳排放權交易；基于分段線性化和二階錐線性化方法,提出一種求解考慮碳交易的發(fā)電優(yōu)化調度問題的新方法。其次,建立了考慮碳稅的發(fā)電優(yōu)化調度模型,可分析不同碳稅場景對發(fā)電商利潤和碳排放的影響；利用二階錐線性化方法將考慮碳稅的發(fā)電優(yōu)化調度模型轉化為混合整數(shù)線性規(guī)劃進行求解。最后,從減排效果和抑制需求兩方面對碳交易和碳稅機制進行了比較分析。10機組24時段系統(tǒng)上進行仿真計算,驗證了上述模型和方法的有效性。第四章提出計及條件魯棒利潤和碳交易的發(fā)電優(yōu)化調度模型和求解方法。首先,考慮電價波動對發(fā)電商利潤的影響,定義條件魯棒利潤和最壞情況條件魯棒利潤,將基于利潤的機組組合模型拓展到基于條件魯棒利潤和最壞情況條件魯棒利潤的機組組合模型。進一步,考慮碳交易,建立了計及條件魯棒利潤和碳交易的發(fā)電優(yōu)化調度模型。借助蒙特卡羅方法模擬電價場景,將所建模型轉化為混合整數(shù)二階錐規(guī)劃進行求解。通過10機24時段系統(tǒng)的算例仿真,驗證了所建模型和求解方法的有效性。發(fā)電商可以利用該模型優(yōu)化發(fā)電,平衡利潤和風險,根據(jù)碳市場價格的高低做出相應的碳交易策略。第五章提出平抑風電波動的多風場風電容量的分配方法,并建立了含風電和碳交易的機組組合模型。首先,運用Copula函數(shù)分析了風電場風速的相關關系,并構造了適合風電場的均值-方差模型優(yōu)化各風場風電容量的分配。進一步,考慮到均值-方差對參數(shù)靈敏的特點,提出基于魯棒優(yōu)化思想的多風場魯棒優(yōu)化模型,并在盒式不確定集和橢球不確定集下將該模型轉化為可用內點法計算的線性規(guī)劃模型和二階錐規(guī)劃模型。最后,引入碳總量控制和交易模式,建立了含風電波動和碳交易的機組組合模型,采用二階錐線性化和分段線性化方法,將模型轉化為混合整數(shù)線性規(guī)劃形式進行求解。10臺火電機組和1個風電場仿真驗證風電波動和碳價的變化對系統(tǒng)運行成本以及碳排放量的影響。
[Abstract]:Considering the carbon trading and the carbon tax policy under the low carbon environment, weighing the robust profit and the electricity price risk, making the optimal plan for the wind farm generating set, it is expected to reduce the carbon dioxide emissions from coal consumption, reduce the influence of wind power fluctuation, reduce the cost of generating electricity, and promote the construction of the saving society and promote the social and economic benefits. Further improvement has significant theoretical and practical value. However, the extremely complex low carbon policies, electricity price fluctuations and wind power fluctuations, and their interaction have led to the existing theory that the optimal scheduling problem can not be studied effectively. Therefore, this paper studies the cost and profit based on the low carbon environment. Unit combination model solving strategy, considering the modeling and solving of unit combination of carbon trading and carbon tax, generating optimal scheduling model and solving of robust profit and risk value, distribution method of wind field wind capacitance, and unit combination model and solution containing wind wave and carbon trading. The paper is divided into six chapters, first The main research work and the sixth chapter are summarized in the second chapter to the fifth chapter. The main research results in this paper are as follows: the second chapter discusses the cost based unit combination model and the profit based unit combination model for the optimal scheduling of power generation, and studies the solution strategy of the two models. First, a more compact model is used. The two order cone relaxation method transforms the mixed integer two programming form of two models into the mixed integer two order cone programming. Further, the two order cone linearization method is proposed to transform the mixed integer two order cone programming form to the mixed integer linear programming. The simulation results show that the mixed integer linear programming model constructed in this paper is the model of the mixed integer linear programming. The better solution strategy to solve the problem of unit combination can obtain high quality suboptimal solution. In the third chapter, the optimal scheduling model and solution method of carbon trading and carbon tax are proposed, and the carbon transaction and carbon tax mechanism are compared and analyzed. First, a carbon trading based optimal dispatch model is established, which not only considers carbon. At the same time, the carbon emission trading is considered, and a new method to solve the optimal scheduling problem considering carbon trading is proposed based on piecewise linearization and two order cone linearization. Secondly, an optimal scheduling model with carbon tax is established to analyze the effect of different carbon tax scenes on the profit and carbon emissions of power producers. The two order cone linearization method is used to transform the optimal dispatching model of electricity generation considering carbon tax into mixed integer linear programming. Finally, the comparison and analysis of carbon trading and carbon tax mechanism are carried out from two aspects of the reduction effect and the suppression demand. The simulation of the 24 period system of the.10 unit in the 24 period system is carried out, and the above models and methods are verified. In the fourth chapter, the optimal scheduling model and solution method for robust profit and carbon trading are proposed. Firstly, the effect of the price fluctuation on the profit of the generator is considered, the robust profit and the worst case condition are defined, and the profit based unit combination model is extended to the condition robust profit and the worst case. Further, considering the carbon trading, a power generation optimization scheduling model considering the condition of the condition robust profit and carbon trading is established. The model of electricity price is simulated with the Monte Carlo method, and the model is converted to the mixed integer two order cone programming. The simulation of the 24 period system of the 10 machine is proved to be built. The model and the solution method are effective. The generator can make use of the model to optimize the power generation, balance the profit and risk, make the corresponding carbon trading strategy according to the price of the carbon market. In the fifth chapter, the distribution method of the wind capacity of the wind power fluctuation is put forward, and the unit combination model with wind power and carbon trading is established. The correlation of wind speed in wind farms is analyzed with Copula function, and a mean variance model suitable for wind farms is constructed to optimize the distribution of wind capacitance in each wind field. Further, considering the sensitivity of mean variance to parameter sensitivity, a robust optimization model of multi wind field based on robust optimization is proposed, and the box uncertainty set and ellipsoid inaccuracy are presented. In the set, the model is transformed into a linear programming model and a two order cone programming model. Finally, a combination model of wind power fluctuation and carbon trading is established by introducing the carbon total control and transaction mode. The two order cone linearization and piecewise linearization are used to convert the model into mixed integer linear programming. The effects of wind power fluctuation and carbon price change on the operation cost and carbon emissions of.10 thermal power plant and 1 wind farms are simulated.

【學位授予單位】：廣西大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TM73

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