基于风速时间周期特征的风电并网系统风险评估方法

目前的风电并网系统风险评估方法多采用风速的概率分布模型,评估的是系统全年的风险指标,不能反映风速和系统风险的时变特征。提出了风速的时间周期特征,并将其描述为风速长期、平缓的月变化趋势和短期、快速的日波动特征两部分的叠加。用时间周期拟合函数表示风速的月变化趋势,用服从特定概率分布的随机变量表示风速的日波动特征,通过对多年风速样本进行曲线拟合来建立风速的时间周期特征模型。根据该模型模拟得到的时变风速建立风电场出力模型,采用蒙特卡洛模拟方法计算风电并网系统中长期风险指标,反映了系统风险的时变特征。以IEEE-RTS79系统及某风电场实际风速为例,验证了所提方法的有效性。评估结果可为电力系统规划、中长期调度和月发电计划制定等提供重要参考。

Risk assessment of wind power integrated system based on time-periodic characteristics of wind speed

The probability distribution model of wind speed is widely used in risk assessment of wind power integrated system. Unfortunately, the current risk assessment mainly focuses on annual risk indices and cannot reflect the time-varying characteristics of wind speed and system risk. In this paper, the time-periodic characteristics of wind speed are proposed and it is described as two parts superposition. The first part is the long-term and gentle monthly trend which can be represented as a time-periodic fitting function, while the other one is the short-term and rapid daily fluctuation characteristics which can be denoted as a random variable that obeys a certain probability distribution. The wind speed model with time-periodic characteristics is built through curve fitting based on wind speed data for several years. Accordingly, wind power output of wind farms can be determined. Furthermore, the mid- and long-term risk indices of wind power integrated system can be calculated through Monte Carlo simulation, and can reflect time varying characteristic of system risk. The validity of proposed method is verified through a case analysis adopting IEEE-RTS79 system and actual wind speed of a wind farm. The result of risk assessment can provide reference for power system planning, mid- and long-term dispatching and monthly generation scheduling making. This work is supported by National Natural Science Foundation of China (No. 51707018) and State Grid Gansu Electric Power Company (No. 52272815001A).