基于灵敏度分析的中小水电机群动态等值方法研究

发布时间：2018-06-21 01:00

本文选题：参数灵敏度 + 动态等值　；参考：《华中科技大学》2015年硕士论文

【摘要】：随着我国水电开发脚步加速,中小水电机群越来越多,其影响不可忽视。由于其机组数量众多、分布广泛、网络结构复杂,在对电网进行仿真时,迫切需要对其进行动态等值,便于对电力系统进行分析。目前,对动态等值的分析方法主要有同调等值法、参数辨识法。同调等值法需要知道外部系统全部参数,理论基础较为雄厚,在工程中应用的时间较长,有具有丰富的理论研究基础和实际应用经验。然而在电力系统规模越来越大、结构越来越复杂的当下,对电力系统提出了在线等值的要求,同调等值法难以完成。于是参数辨识法以其实时性的优势越来越受欢迎,在动态等值中应用越来越广泛。另外,参数灵敏度在动态等值中有广泛应用,对系统动态特征分析有很大帮助。本文首先对同调等值法进行了介绍,对其具体方法步骤进行了详细的研究,并采用具体算例进行等值计算,得到理想的等值结果;其次,概述了参数辨识方法,对等值模型、智能优化算法进行了详细的阐述。随后,对轨迹灵敏度、特征根灵敏度进行了重点研究,从参数灵敏度的角度出发分析了参数可辨识性,为参数可辨识性分析提供了一种新途径。综合同调等值法与参数辨识法,本文提出了基于灵敏度分析的动态等值改进方法,通过灵敏度判断参数辨识的难易度,以此将待辨识参数加以区分,进而辨识出易于辨识的参数,而其他参数采用同调等值的结果。最后通过实际算例的仿真研究,验证了此方法的可行性和有效性。
[Abstract]:With the acceleration of hydropower development in China, there are more and more small and medium hydropower clusters, which can not be ignored. Because of the large number of units, widespread distribution and complex network structure, the dynamic equivalence of the power system is urgently needed in the simulation of the power grid to facilitate the analysis of the power system. At present, the analysis methods for dynamic equivalence are mainly the same It is necessary to know all the parameters of the external system. The method of homology equivalence needs to know all the parameters of the external system. The theoretical basis is relatively strong, the time of application in the project is longer, and it has rich theoretical research foundation and practical application experience. However, the power system is becoming more and more complex and the power system is becoming more and more large and the structure is more and more complex. It is difficult to complete the equivalence method. Therefore, the parameter identification method is becoming more and more popular with the advantages of its real time, and is widely used in the dynamic equivalence. In addition, the parameter sensitivity is widely used in the dynamic equivalence. It is very helpful to the dynamic characteristic analysis of the system. The specific method steps are studied in detail, and a specific example is used to calculate the equivalent value, and the ideal results are obtained. Secondly, the parameter identification method, the peer-to-peer model and the intelligent optimization algorithm are described in detail. Then, the trajectory sensitivity and the characteristic root sensitivity are focused on, from the angle of the parameter sensitivity. The identifiability of parameters is analyzed. A new approach for parameter identifiability analysis is provided. A dynamic equivalence method based on sensitivity analysis is proposed. The sensitivity analysis is used to judge the difficulty of parameter identification by sensitivity. The identification parameters are distinguished and identified easily. The parameters of knowledge are used, while the other parameters are based on the result of homology equivalence. Finally, the feasibility and effectiveness of the method are verified through the simulation study of practical examples.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TV742;TV734

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