Analysis of Radial Distribution Systems Using Particle Swarm Optimization under Uncertain Conditionsditions (Contemporary Mathematics, 2025)
Efficiently mitigating losses in power distribution networks is imperative for their optimal operation. This research employs the particle swarm optimization (PSO) algorithm to investigate the joint optimization of phase balance and conductor sizing in imbalanced distribution systems. Objective functions encompass power loss, voltage unbalance, total neutral current, and complex power unbalance. Each objective is individually optimized before being integrated with weights to address multi-objective optimization. The study aims to minimize losses in inherently unequal electrical distribution networks. PSO techniques, namely power flow and optimal distributed generation (DG) placement, effectively curtail losses. These techniques are seamlessly integrated into existing systems using a tailored load-flow method for three-phase imbalanced radial distribution networks. Precise evaluation of network conditions relies on key metrics, including node voltage, angle, branch current, active and reactive power losses, and branch losses. A systematic approach identifies relevant variables, calculating target voltage angle and magnitude. Despite the time and effort required, this process yields accurate outcomes. A uniform voltage of 1 p.u. is maintained from substation to terminal node, with variable magnitude and phase angle adjustments yielding voltage drop computations. The proposed study is demonstrated on 19- and 25-node networks with unbalanced distribution. The results of the study underscore DG's potential for cost reduction and performance enhancement.
Keywords: DG; radial distribution network; PSO; unbalanced system