Condition-Aware Distribution Network Reconfiguration via Multi-Stage Optimization Framework

Date

2025-5-12

Author

Mohammadi Vaniar, Arash

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Distribution Network Reconfiguration (DNR) is one of the important techniques for enhancing the efficiency and flexibility of electrical distribution networks (DNs). DNR can significantly reduce power losses and improve voltage profiles by dynamically changing the network topology. This thesis presents a three-stage optimization framework for DNR, integrating topology optimization and reactive power compensation to enhance operational efficiency. The first stage, termed Reconfiguration of Tie-Line Switches (RTLS), employs a Particle Swarm Optimization (PSO) algorithm enhanced with Depth-First Search (DFS) algorithm to identify radial network topologies that minimize active power losses. Upon identifying a feasible topology, the network configuration is updated and passed to the second stage, termed Shunt Capacitor Sizing (SCS). In the SCS stage, another PSO algorithm is used to determine the optimal capacitor deployment at predefined locations. Once optimal reactive power injections are determined, the third stage re-applies the RTLS, now considering the updated load model. This final stage evaluates whether a further improvement in active power loss is achievable. If the third stage identifies a better radial topology, its results are adopted; otherwise, the solution from the second stage is finalized. This stepwise and feedback-driven approach ensures both topological efficiency and voltage support, providing a robust and scalable method for DNR in modern power DNs. This study is validated by using two well-established test cases: the IEEE 33-bus system and the IEEE 123 Feeder system. In addition, the proposed methodology is tested on a 7-bus case for further investigation. Five distinct scenarios were examined to evaluate the robustness and applicability of the proposed methodology under various operating conditions: heavily loaded network, lightly loaded network, normal loading conditions, poor power factor (PF), and good PF cases. Results demonstrate significant reductions in active power losses and enhanced voltage profiles.

Subject Keywords

Distribution Network Reconfiguration (DNR), Multi-Stage Optimization Framework, Particle Swarm Optimization (PSO), Tie-Line Switches, Shunt Compensation

URI

https://hdl.handle.net/11511/114621

Collections

Graduate School of Natural and Applied Sciences, Thesis