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The reliability evaluation of the power system containing wind farm using the improved state space partition method

机译:基于改进状态空间划分方法的含风电场电力系统可靠性评估

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The random mass access of wind power made the reliability assessment of power system with large-scale wind farms more significant. This paper proposed a new method of power system reliability assessment with large-scale wind power generation. The state-space partitioning algorithm is improved considering the forced shutdown of unit rate and its effect on the reliability of the system, using the minimum adjacent state instead of adjacent state sets. At the same time, the proposed method considered the wind turbine's own service model and the uncertainty of wind speed. Use the normal distribution function to simulate wind speed distribution. Use hierarchical cluster analysis technology to consider the uncertainty of the wind farms to join in the system. Compared with the fast sort method reduces the need to filter on the number of states and memory footprint, increasing the calculation speed. In this paper, finally, based on the Matlab program, using the IEEE-RTS79 reliability test system as an example verified the correctness and validity of the algorithm.
机译:风能的随机大规模访问使得具有大型风电场的电力系统的可靠性评估更加重要。提出了一种大规模风力发电系统可靠性评估的新方法。考虑到单位速率的强制关闭及其对系统可靠性的影响,使用最小相邻状态而不是相邻状态集对状态空间划分算法进行了改进。同时,该方法考虑了风机自身的服务模型和风速的不确定性。使用正态分布函数模拟风速分布。使用层次聚类分析技术来考虑风电场加入系统的不确定性。与快速排序方法相比,减少了对状态数和内存占用量进行过滤的需要,从而提高了计算速度。最后,以Matlab程序为基础,以IEEE-RTS79可靠性测试系统为例,验证了该算法的正确性和有效性。

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