Optimization of dynamic transmission network expansion planning using binary particle swarm optimization algorithm - Inyanga, Faith Eseri; Muisyo, Irene N.; Kaberere, Keren K. (Institute of Advanced Engineering and Science, 2025)
Increasing power demand is usually met by the expansion of generation capacity. The transmission network should be expanded in tandem to ensure power is evacuated from generation points to the load centres. Inadequate power capacity causes congestion. Congestion results due to under-voltages and violation of transmission lines’ loading limits. Constructing additional transmission lines is required to alleviate the congestion after measures of increasing the transmission line’s transfer capability are exploited. Transmission network expansion planning (TNEP) determines the transmission lines to be added to a power system at minimal construction cost, without violating network constraints. In this research, voltage limit violations are penalized in a constrained dynamic TNEP problem for a 10-year planning horizon. The optimal location and number of new transmission lines required at minimal construction cost, and transmission losses associated with the transmission network operations are determined. Improved binary particle swarm optimization (IBPSO) algorithm is applied to optimize the dynamic transmission network expansion planning (DTNEP) results. The developed model is tested on Garver’s 6-bus system using MATLAB. The construction cost for new transmission lines is minimized, and transmission losses reduced when compared to other published works without violating voltage limits (±5%) and transmission lines’ thermal capacities. The transmission network system adequacy is improved.