Quasi-static analysis of power systems can be performed by means of timeseries-based and probability density function-based models. In this paper, the effect of different load and generation modelling approaches on the quasi-static analysis of distribution networks is investigated. Different simplified load and distributed renewable energy sources generation timeseries-based models are considered as well as probabilistic analysis. Moreover, a more sophisticated approach based on cluster analysis is introduced to identify harmonized sets of representative load and generation patterns. To determine the optimum number of clusters, a three-step methodology is proposed. The examined cases include the quasi-static analysis of distribution networks for different operational conditions to identify the simplified modelling approaches that can efficiently predict the network voltages and losses. Finally, the computational efficiency by using the simplified models is evaluated in temperature-dependent power flow analysis of distribution networks.

电力系统的准静态分析可以通过基于时间序列和基于概率密度函数的模型进行。在本文中，研究了不同负荷和发电建模方法对配电网准静态分析的影响。考虑了不同的简化负载和分布式可再生能源发电时间序列模型以及概率分析。此外，引入了一种基于聚类分析的更复杂的方法来识别协调的代表性负载和发电模式集。为了确定最佳聚类数，提出了一种三步法。检查的案例包括对不同运行条件下的配电网络进行准静态分析，以确定可以有效预测网络电压和损耗的简化建模方法。最后，在配电网络的温度相关潮流分析中评估了使用简化模型的计算效率。