用于风电机组容量评估的容量可信度快速算法

发布时间：2018-05-09 04:23

本文选题：风电机组容量 + 容量可信度　；参考：《西安交通大学学报》2017年06期

【摘要】：针对以往在利用风电机组容量可信度这一指标来评价风电机组容量时,准确度与计算速度不能兼顾的问题,提出了一种基于负载-失负荷概率曲线来快速准确计算风电机组容量可信度的最大公因子步长算法(GCDS)。该方法首先将风速分布信息和风电机组特性曲线离散化,把风电机组出力建模为多状态,然后应用负载-失负荷概率的递推关系式和以各个机组装机容量最大公约数为步长进行遍历的算法,快速得出加入风电机组前后系统的负载-失负荷概率曲线,最终得出风电机组的容量可信度。仿真和实验结果表明:把1个风电机组加入到41个常规机组的系统中,使用GCDS算法对风电机组容量可信度进行计算,在准确度可以保证的前提下,计算时间仅为0.015 6s,与穷举法相比,计算效率有了极大提升。
[Abstract]:In order to evaluate the capacity of the wind turbine by using the reliability index of the wind turbine capacity to evaluate the capacity of the wind turbine, the maximum common cause subdivision algorithm (GCDS) based on the load loss probability curve, which is based on the load loss probability curve, is proposed. The characteristic curve of cloth information and wind turbine is discretized, and the output of wind turbine is modeled as multi state. Then the recursive relation of load loss probability and the maximum common number of unit capacity of each unit are traversed. The load loss probability curve of the front and rear system of the wind turbine is quickly obtained, and the final result is obtained. The simulation and experimental results show that the 1 wind turbines are added to the 41 conventional units, and the GCDS algorithm is used to calculate the reliability of the wind turbine capacity. The calculation time is only 0.015 6S under the premise of accuracy. Compared with the exhaustion method, the calculation efficiency has been greatly improved.

【作者单位】：西安交通大学智能网络与网络安全教育部重点实验室;
【基金】：国家自然科学基金资助项目(61174146,61221063,U1301254,61304212)
【分类号】：TM614

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