本文選題：多維相關性　切入點：模型優(yōu)化　出處：《西南交通大學》2017年碩士論文　論文類型：學位論文

【摘要】：隨著風電并網規(guī)模的不斷擴大,在相鄰區(qū)域存在多個風電場接入的情況,而地理位置相近的風電場,氣流速度顯現(xiàn)出較強的相關性,這使得各風電場出力也具有顯著的空間相關性,如果忽略這種相關性,將導致系統(tǒng)調度過程中出現(xiàn)有功調度困難、系統(tǒng)潮流越限等問題。因此構建一個能準確描述多風電場出力相關性的模型,對研究含大規(guī)模風電場電力系統(tǒng)經濟調度至關重要。本文通過分析多風電場出力的隨機特性和相關特性,建立了考慮多風電場相關性的場景調度模型,并將其運用到電力系統(tǒng)的調度研究中,進一步提高了系統(tǒng)運行的經濟性。首先,基于Pair Copula理論構建了不同維度的風電功率的相關性模型,并且選取澳大利亞多個風電場出力樣本進行實例分析,結果表明Pair Copula模型能較好地描述高維相關性,但隨著維度增加模型精度有所下降。為此,采用智能優(yōu)化算法(粒子算法和差分進化算法)對Pair Copula模型進行參數(shù)優(yōu)化,優(yōu)化結果表明,優(yōu)化后模型相比于傳統(tǒng)模型,一定程度上提高了模型精度,從而驗證了所提方法的有效性和優(yōu)越性。而后,將多風電場出力相關性的優(yōu)化模型與基于最佳聚類數(shù)的K-means聚類聚類分析技術相結合,建立一種考慮多風電場相關性的場景概率模型。為了驗證多風電場相關性對電力系統(tǒng)經濟調度的影響以及本文提出場景概率模型的有效性,將場景概率模型與經濟調度模型相結合,建立了以系統(tǒng)運行成本最小的場景調度模型,并選用了10機系統(tǒng)及其擴展系統(tǒng)(20機系統(tǒng))進行算例仿真,仿真結果表明本文構建的場景調度模型的能夠為電力系統(tǒng)的實際運行節(jié)約一定的成本,從而驗證了該場景調度模型的有效性。
[Abstract]:With the continuous expansion of wind power grid scale, there are many wind farms connected in adjacent areas, and wind farms with similar geographical location show strong correlation with air velocity. This makes the wind farm have significant spatial correlation. If the correlation is ignored, it will lead to the difficulty of active power scheduling in the system scheduling process. Therefore, a model which can accurately describe the correlation of multi-wind farm output is constructed. It is very important to study the economic dispatch of power system with large scale wind farm. By analyzing the stochastic characteristics and related characteristics of multi-wind farm, a scenario scheduling model considering the correlation of multi-wind farm is established in this paper. It is applied to the power system dispatching research to further improve the economy of system operation. Firstly, based on Pair Copula theory, the correlation model of wind power in different dimensions is constructed. The results show that the Pair Copula model can well describe the high dimensional correlation, but the accuracy of the model decreases with the increase of dimension. The intelligent optimization algorithm (particle algorithm and differential evolution algorithm) is used to optimize the parameters of Pair Copula model. The optimization results show that compared with the traditional model, the optimized model improves the precision of the model to a certain extent. Finally, the effectiveness and superiority of the proposed method are verified. Then, the optimization model of multi-wind farm output correlation is combined with K-means clustering analysis technology based on optimal clustering number. In order to verify the influence of multi-wind farm correlation on economic dispatch of power system and the validity of the scenario probability model proposed in this paper, a scenario probability model considering the correlation of multi-wind farms is established. By combining the scenario probability model with the economic scheduling model, a scenario scheduling model with the minimum running cost of the system is established, and the 10-machine system and its extended system are selected to carry out the simulation. The simulation results show that the proposed scenario scheduling model can save a certain amount of cost for the actual operation of the power system, thus validating the effectiveness of the scenario scheduling model.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TM614;TM73

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本文編號：1567206