Optimal partitioning of unbalanced active distribution systems for supply-sufficient micro- grids considering uncertainty

Partitioning large-scale smart distribution systems into multiple microgrids (MG) are considered an effective solution to maintain system reliability and to improve the power system restoration under emergency conditions. The partitioning planning process faces many challenges especially if the uncertain nature of both renewable energy resources (RERs) and loads, and the unbalanced operation of the distribution systems are considered. In this paper, the active distribution system partitioning is handled through a proposed three stages method. The proposed method presents a parallel planning for both energy sources integration process and partitioning process, taking into consideration all the circumstances that the system is exposed to, with determining the optimal specification of the devices that will be added to the system to reach the required efficiency of the system during system partitioning and system unification. The proposed three-stage method considers the uncertainty of PV modules and wind turbines. A new criterion for modeling RERs uncertainty is developed. Four phases for uncertainty reduction are applied based on the main sources of uncertainty involving solar irradiation, temperature, wind speed for the loading ratio. Moreover, the load uncertainty and system unbalance have been considered. The proposed reduction strategy leads to 92% reduction of the uncertainty cases for 1 year is sufficient for effective modeling with an acceptable level of accuracy. The proposed method is tested on the IEEE 123-node as a large-scale unbalanced test feeder. The obtained results verify the effectiveness of the proposed method in partitioning the tested distribution system into five micro-grids with self-dependence exceeded 85%.