基于Beta分布最小置信区间的主动配电网鲁棒优化研究

Robust Optimization Study on Active Distribution Network Based on Beta Distribution Minimum Confidence Interval

随着分布式能源渗透率的逐步提高,传统的优化模型已难以满足主动配电网稳定高效运行的要求。为了降低发布式能源不确定性对配电网的影响,本文提出了一种基于Beta分布最小置信区间的主动配电网鲁棒性优化方法。首先,建立一个包含储能装置、电容器组、静止变阻补偿器、风力发电机和光伏发电的二阶配电网模型。然后对相关分布式能源的历史数据进行分析,并用概率密度函数进行描述,通过区间搜索得到最小置信区间。最后将最小置信区间作为不确定区间,建立了一个两阶段鲁棒优化模型,并对配电网进行求解。针对IEEE33节点配电网的仿真结果验证了与传统鲁棒优化方法相比,本文所提出的方法能实现配电网更稳定、更高效的运行。

With the gradual increase in the penetration rate of distributed energy resources,the traditional optimization model is difficult to meet the requirements of stable and efficient operation of active distribution network.In order to reduce the impact of published energy uncertainty on distribution network,a robustness optimization method for active distribution network based on the minimum confidence interval of Beta distribution is proposed in this paper.Firstly,a second-order distribution network model consisting of energy storage devices,capacitor banks,static rheostat compensators,wind turbines and photovoltaic power generation is established.Then,the historical data of relevant distributed energy resources are analyzed and described by probability density function,and the minimum confidence interval is obtained through interval search,and finally the minimum confidence interval is used as the uncertainty interval to establish a two-stage robust optimization model and solve the distribution network.The simulation results of IEEE33 node distribution network verify that compared with the traditional robust optimization method,the proposed method can achieve more stable and efficient operation of the distribution network.