微电网小干扰稳定概率分析

Probabilistic Analysis of Microgrid Small Signal Stability

微电网是智能电网的重要组成部分,在对微电网进行小干扰稳定性研究时存在一些不确定因素,如某些分布式电源由于自然环境等影响出力变化,当地负荷的随机波动,线路参数变化等,因而在确定性的系统运行方式和运行参数下得到的小干扰稳定结果无法准确地反映实际的微电网小干扰稳定性。采用基于点估计的微电网小干扰稳定的概率分析方法来分析微电网在不确定因素下的小干扰稳定性,通过蒙特卡罗仿真的结果验证了该方法计算结果的准确性和计算量少的优点。确定性微电网小干扰分析方法仅能判断在某一特定运行工况下系统是否稳定,而基于点估计法的微电网小干扰稳定概率分析方法可以确定系统特征值的分布范围以判断失稳风险。若在某些运行工况下特征值实部为正值即系统不稳定或阻尼较弱时,则计算状态变量的模式参与因子,通过调整与失稳模式强相关的发电机组出力或控制器参数使在计及不确定因素时仍能保证微电网小干扰稳定性。通过一个含有风电场、燃料电池及同步发电机的微电网算例验证了基于点估计的微电网小干扰稳定概率分析方法的有效性。

MG （microgrid） is an important part of smartgrid. Uncertainties such as random fluctuation of power generations and loads in MG should be taken into consideration to effectively analyze small signal stability of the MG. A TPE （two-point estimate） based method is thus presented to fulfill probabilistical analysis of small signal stability of MG with uncertain factors. Compared with the MCS （Monte Carlo simulation） method, the TPE based method has much lower computational burden while keeping equivalent performance. The TPE based method is used to determine the distribution of each eigenvalue in small signal stability analysis of MG due to the uncertain factors men- tioned above. The method may reveal the risk of instability even when a positive evaluation result is provided by con ventional deterministic analysis method. Further, the outputs of distributed generations and parameters of control lers in MG are adjusted to improve its small signal stability accordingly, even encountering such uncertain factors. Finally, the effectiveness of the proposed method is verified through case studies, in which a microgrid powered by wind farm, fuel cell and synchronous generator operates in connected and islanded modes.