Radial distribution systems performance enhancement through RE (Renewable Energy) integration and comprehensive contingency ranking analysis

This research focuses on restructuring medium-level voltage (MLV) distribution systems by integrating distributed renewable energy resources (DER) at multiple feed points. It examines the impact of incorporating renewable energy and evaluates system performance metrics such as robustness, static voltage stability, line carrying capacity, utility grid effectiveness, and losses within the conventional radial distribution framework commonly used in educational institutions. The contingency ranking of the real-time radial distribution system (RTRDS) for a typical educational institution consisting of N buses was conducted. Parameters such as the Voltage Performance Index (PIV) and Flow Performance Index (PIF) were evaluated. The results support the integration of distributed renewable energy sources within the existing radial distribution grid infrastructure. This research proposes enhanced contingency analyses through a straightforward reconfiguration process involving an additional tie line ( N + 1) for the existing N bus radial distribution system (RDS). Load flow analysis of the RDS with distributed renewable energy resources (DER) for both N bus and N + 1 bus systems was conducted using the Gauss-Seidel and Newton–Raphson methods. Simulation results indicate that baseline loading is consistently maintained by grid sources and DER sources connected at multiple feed points. The proposed configuration of the N + 1 bus system for the existing RTRDS was evaluated for voltage performance and compared with the Grey Wolf Optimization (GWO) algorithm. The results indicate that the N + 1 bus configuration modeled using the MiPower tool performed comparably to the GWO results. Additionally, the contingency ranking for the proposed N + 1 configuration was validated using the IEEE 10 and 30 bus system. • Load flow analysis was performed on the existing power system (RDS) network, examining key parameters such as power flow, node voltages, line loading between nodes, and real and reactive power losses. • The performance of the existing power system (RDS) network, when integrated with distributed renewable energy (DER), was assessed. System performance parameters for the N bus system configuration were evaluated. • Contingency ranking analysis of the ​ N bus and ​ N + 1 ​bus systems with DER was performed. This analysis included identifying parameters such as PIV (Post-Contingency Injection Voltage) and PIF (Post-Contingency Injection Flow). • Grey Wolf Algorithm (GWO) was implemented for the proposed N + 1 bus system and evaluated the PIV. • Proposed Configuration of N + 1 bus is tested in IEEE 10 bus and 30 bus system. The ​ N + 1 ​bus system outperforms the N bus system.