Tri-Stage Optimization Framework for Optimal Clustering of Power Distribution Systems into Sustainable Microgrids.
Saved in:
| Title: | Tri-Stage Optimization Framework for Optimal Clustering of Power Distribution Systems into Sustainable Microgrids. |
|---|---|
| Authors: | Ahmed, Yahia N.1 (AUTHOR), Elsayed, Ahmed Abd Elaziz1 (AUTHOR), Farag, Hany E. Z.1 (AUTHOR) hefarag@yorku.ca |
| Source: | Energies (19961073). May2026, Vol. 19 Issue 9, p2050. 21p. |
| Subject Terms: | *Microgrids, *Mathematical optimization, *Energy storage, *Electric power system stability, *Distributed resources (Electric utilities), *Greenhouse gases, *Electrical load, *Electric power distribution grids |
| Abstract: | Decentralized sustainable microgrids are emerging as a promising approach for addressing the increasing complexity of modern power systems while ensuring reliable and efficient operation. A fundamental driver of this transition is the partitioning of distribution networks into self-sufficient microgrids supported by the effective integration of Distributed Energy Resources (DERs) and Energy Storage Systems (ESSs), enabling improved power flow management and enhanced voltage stability. In this regard, this paper proposes a tri-stage optimization framework designed to segment power distribution systems into multiple self-sustaining microgrids while maintaining optimal network performance. In the first stage, the distribution grid is partitioned into microgrid clusters based on electrical distance metrics and bus correlation analysis. The second stage focuses on the optimal sizing and operational management of DERs and ESSs within each identified microgrid to ensure energy self-sufficiency and minimize greenhouse gas (GHG) emissions. In the third stage, an optimal resource allocation strategy is implemented, where the resources determined in the previous stage are optimally placed within the distribution network to achieve optimal power flow, reduce system losses, and maintain voltage stability under worst-case operating conditions. The proposed framework is validated using the IEEE 33-bus test system. Simulation results demonstrate its effectiveness in multi-microgrid classification, coordinated planning, and resource allocation, highlighting its superiority in enhancing system performance and resilience. [ABSTRACT FROM AUTHOR] |
| Database: | Energy & Power Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
Be the first to leave a comment!
