本文關(guān)鍵詞：基于機(jī)會(huì)約束規(guī)劃的含風(fēng)場(chǎng)的優(yōu)化調(diào)度問(wèn)題　出處：《哈爾濱工業(yè)大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 風(fēng)電 電力系統(tǒng) 波動(dòng)特性 機(jī)會(huì)約束規(guī)劃 優(yōu)化調(diào)度 頻率偏差

【摘要】：隨著經(jīng)濟(jì)社會(huì)的不斷發(fā)展，人類對(duì)能源的需求量越來(lái)越大，化石能源儲(chǔ)量的日漸減少以及環(huán)境污染問(wèn)題的日益嚴(yán)重使得風(fēng)能的重要性越來(lái)越受到人們的重視。風(fēng)能具有可再生、無(wú)污染、成本低、儲(chǔ)量大等優(yōu)點(diǎn)，在新能源發(fā)電領(lǐng)域具有不可替代的地位，但是，風(fēng)能的分布受氣候的影響比較大，具有隨機(jī)性、間歇性、波動(dòng)性和不確定性等特點(diǎn)，風(fēng)電的大規(guī)模并網(wǎng)會(huì)給電力系統(tǒng)帶來(lái)很多不利影響。為了減小風(fēng)電并網(wǎng)對(duì)電力系統(tǒng)的影響，傳統(tǒng)的優(yōu)化調(diào)度方法存在很多局限性，因此需要尋求更為合理有效的方法對(duì)含風(fēng)場(chǎng)的電力系統(tǒng)進(jìn)行優(yōu)化調(diào)度研究。 首先從風(fēng)功率波動(dòng)特性分析入手，，采用Mallat分解算法對(duì)風(fēng)電場(chǎng)的風(fēng)功率實(shí)測(cè)數(shù)據(jù)進(jìn)行分解，分解出風(fēng)功率平均值數(shù)據(jù)和小時(shí)級(jí)分量的波動(dòng)量，擬合得到兩者之間具體的函數(shù)關(guān)系，將風(fēng)功率的波動(dòng)量用含有風(fēng)功率平均值的函數(shù)關(guān)系式來(lái)表示，從而可以根據(jù)每一時(shí)刻風(fēng)功率的平均值計(jì)算出該時(shí)刻風(fēng)功率波動(dòng)量的大小，將風(fēng)功率波動(dòng)量進(jìn)行量化。 其次，建立了基于機(jī)會(huì)約束規(guī)劃的優(yōu)化調(diào)度模型，使用機(jī)會(huì)約束規(guī)劃的方法對(duì)傳統(tǒng)的確定性優(yōu)化調(diào)度模型進(jìn)行改進(jìn)，將含有隨機(jī)變量的目標(biāo)函數(shù)和約束條件用滿足一定置信度水平的概率形式來(lái)表達(dá)，并將風(fēng)功率波動(dòng)特性的函數(shù)表達(dá)式用于機(jī)會(huì)約束規(guī)劃模型中，使得所建立的模型更加符合實(shí)際情況。 進(jìn)一步對(duì)所提出的模型進(jìn)行求解，由于模型中含有機(jī)會(huì)約束，傳統(tǒng)方法已不再適用，因此使用基于隨機(jī)模擬的遺傳算法對(duì)模型進(jìn)行求解，通過(guò)算例分析比較風(fēng)功率波動(dòng)特性和風(fēng)功率預(yù)測(cè)誤差對(duì)系統(tǒng)成本的影響，并對(duì)所提出的模型及算法的有效性進(jìn)行了驗(yàn)證。 最后，根據(jù)自動(dòng)發(fā)電控制(AGC)的原理與功能，分別搭建了單區(qū)域系統(tǒng)調(diào)頻模型和雙區(qū)域系統(tǒng)調(diào)頻模型，通過(guò)將前面得到的調(diào)度結(jié)果輸入模型并對(duì)模型進(jìn)行仿真，比較風(fēng)功率波動(dòng)特性與風(fēng)功率預(yù)測(cè)誤差對(duì)系統(tǒng)調(diào)頻的影響，通過(guò)仿真結(jié)果可以看出，區(qū)域系統(tǒng)互聯(lián)后，各個(gè)區(qū)域的頻率偏差都得到了相應(yīng)減小。 根據(jù)以上研究成果可以看出，本文提出的模型及算法更加符合風(fēng)電接入后電網(wǎng)調(diào)度的實(shí)際情況，可以起到降低系統(tǒng)成本、提高調(diào)度經(jīng)濟(jì)性、減小系統(tǒng)頻率偏差、優(yōu)化電網(wǎng)調(diào)度的目的，對(duì)大規(guī)模風(fēng)電接入電網(wǎng)后調(diào)度指令的制定具有一定的指導(dǎo)意義。 本文工作得到了國(guó)家重點(diǎn)基礎(chǔ)研究發(fā)展計(jì)劃(973計(jì)劃)《智能電網(wǎng)中大規(guī)模新能源電力安全高效利用基礎(chǔ)研究》（子課題一：新能源電力系統(tǒng)動(dòng)力學(xué)特性及建模理論）(2012CB215201)以及國(guó)家高技術(shù)研究發(fā)展計(jì)劃(863計(jì)劃)重大項(xiàng)目《高滲透率間歇性能源的區(qū)域電網(wǎng)關(guān)鍵技術(shù)研究和示范》(2011AA05A105)的資助。
[Abstract]:With the development of economy and society, the demand for energy is increasing. With the decrease of fossil energy reserves and environmental pollution, people pay more and more attention to the importance of wind energy. Wind energy has the advantages of renewable, pollution-free, low cost, large reserves and so on. In the field of new energy generation, there is an irreplaceable position. However, the distribution of wind energy is greatly affected by climate, with the characteristics of randomness, intermittence, volatility and uncertainty. The large-scale wind power grid connection will bring a lot of adverse effects to the power system. In order to reduce the impact of wind power grid connection on the power system, the traditional optimal dispatching method has many limitations. Therefore, it is necessary to find a more reasonable and effective method to study the optimal dispatching of power system with wind field. Firstly, the wind power fluctuation characteristics are analyzed, and the wind power measured data of wind farm are decomposed by Mallat decomposition algorithm to decompose the average wind power data and the fluctuation of the hourly component. The specific functional relationship between the two is obtained, and the fluctuation of wind power is expressed by the functional relationship with the mean wind power. According to the average value of wind power at each moment, the magnitude of wind power fluctuation can be calculated, and the fluctuation of wind power can be quantified. Secondly, the optimal scheduling model based on opportunistic constraint programming is established, and the traditional deterministic optimal scheduling model is improved by using the method of opportunistic constrained programming. The objective function and constraint conditions with random variables are expressed in the probability form of certain confidence level, and the function expression of wind power fluctuation characteristic is used in the opportunistic constrained programming model. The model is more in line with the actual situation. Further, the proposed model is solved. Because of the opportunity constraints in the model, the traditional method is no longer applicable, so the genetic algorithm based on stochastic simulation is used to solve the model. The effects of wind power fluctuation characteristics and wind power prediction error on the system cost are analyzed and compared by an example, and the validity of the proposed model and algorithm is verified. Finally, according to the principle and function of AGC, the single region system FM model and the dual area system FM model are built. By inputting the former scheduling results into the model and simulating the model, the influence of wind power fluctuation characteristics and wind power prediction error on the frequency modulation of the system is compared. The simulation results show that the regional system is interconnected. The frequency deviation of each region is reduced accordingly. According to the above research results, we can see that the model and algorithm proposed in this paper are more in line with the actual situation of grid dispatching after wind power access, can reduce the system cost and improve the dispatching economy. The purpose of reducing the system frequency deviation and optimizing the power grid dispatching has a certain guiding significance for the establishment of dispatching instructions after large-scale wind power is connected to the power network. The work of this paper has been obtained from the National key basic Research and Development Plan, "basic Research on the safe and efficient Utilization of Large-Scale New Energy and Electric Power in Smart Grid" (. Subproject 1: dynamic characteristics and Modeling Theory of New Energy Power system. Research and demonstration of key Technologies in Regional Power Grid for High permeability intermittent Energy.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TM614

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