用于风电机组容量评估的容量可信度快速算法

A Fast Algorithm of Capacity Credit for Measuring Capacity of Wind Turbines

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。

A fast step algorithm GCDS based on greatest common divisor and the curve of the lost of load probability is proposed to solve the problem that the accuracy and calculation speed cannot be taken into consideration at the same time when evaluating the capacity of wind turbines by using wind turbine capacity credit.Firstly,both the wind speed distribution and the curve of wind turbine characteristic are discretized,and the output of a wind turbine is modeled with multi-state.Then,the recurrence relation between the load and the lost of load probability is used,and the maximum common divisor of each unit＇s installed capacity is taken as the step length to traverse the curve of the lost of load probability in order to quickly obtain the curves before and after the wind turbine is added.The capacity credit of a wind turbine is finally obtained.Numerical testing results show that when a wind turbine is added into a system with 41 conventional generators,the GCDS only uses 0.015 6second to complete the calculation on the premise of guaranteed accuracy.It＇s obviously agreat increase in computing speed compared to the exhaustive method.