多风电场相关性的优化建模及其在经济调度中的应用

发布时间：2018-03-04 20:40

本文选题：多维相关性　切入点：模型优化　出处：《西南交通大学》2017年硕士论文　论文类型：学位论文

【摘要】：随着风电并网规模的不断扩大,在相邻区域存在多个风电场接入的情况,而地理位置相近的风电场,气流速度显现出较强的相关性,这使得各风电场出力也具有显著的空间相关性,如果忽略这种相关性,将导致系统调度过程中出现有功调度困难、系统潮流越限等问题。因此构建一个能准确描述多风电场出力相关性的模型,对研究含大规模风电场电力系统经济调度至关重要。本文通过分析多风电场出力的随机特性和相关特性,建立了考虑多风电场相关性的场景调度模型,并将其运用到电力系统的调度研究中,进一步提高了系统运行的经济性。首先,基于Pair Copula理论构建了不同维度的风电功率的相关性模型,并且选取澳大利亚多个风电场出力样本进行实例分析,结果表明Pair Copula模型能较好地描述高维相关性,但随着维度增加模型精度有所下降。为此,采用智能优化算法(粒子算法和差分进化算法)对Pair Copula模型进行参数优化,优化结果表明,优化后模型相比于传统模型,一定程度上提高了模型精度,从而验证了所提方法的有效性和优越性。而后,将多风电场出力相关性的优化模型与基于最佳聚类数的K-means聚类聚类分析技术相结合,建立一种考虑多风电场相关性的场景概率模型。为了验证多风电场相关性对电力系统经济调度的影响以及本文提出场景概率模型的有效性,将场景概率模型与经济调度模型相结合,建立了以系统运行成本最小的场景调度模型,并选用了10机系统及其扩展系统(20机系统)进行算例仿真,仿真结果表明本文构建的场景调度模型的能够为电力系统的实际运行节约一定的成本,从而验证了该场景调度模型的有效性。
[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.
【学位授予单位】：西南交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614;TM73

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