Table 1 Comparative analysis of capacitor bank placement techniques in distribution networks.
Reference | Optimization method | Objective(s) | Test system | Considerations |
|---|---|---|---|---|
Graph Theory | Reactive Power Compensation, Voltage Balancing | IEEE 33-bus | High complexity, requires network modifications | |
Particle Swarm Optimization (PSO) | Loss reduction, Voltage profile improvement, Reactive power compensation | IEEE 33-bus | Premature convergence, non-optimal solutions | |
Genetic Algorithm (GA) | Power factor correction, Loss reduction | IEEE 69-bus | High computational cost, slow convergence | |
Mixed-Integer Quadratic Programming (MIQC) | Loss reduction, Voltage profile improvement | IEEE 33-bus | Limited efficiency under dynamic load conditions | |
Multi-objective GA | Loss reduction | IEEE 69-bus | Fixed capacity, limited optimization | |
Mixed-Integer Linear Programming (MILP) | Loss reduction, Voltage deviation minimization | IEEE 33-bus and 69-bus | High computational load, complex modeling | |
Hybrid GA-PSO Algorithm | Loss reduction, Voltage profile improvement, Reactive power compensation | IEEE 33-bus | Complex hybrid algorithm, longer processing time | |
Data-driven Load Forecasting | Voltage stability | IEEE 33-bus | Limited reactive power control under load variations | |
Multi-objective Optimization (MO) | Loss reduction, Cost minimization, Voltage stability | IEEE 69-bus | High complexity, long processing time | |
Artificial Bee Colony (ABC) Optimization | Voltage stability | IEEE 33-bus | Heavy computation for large networks | |
Differential Evolution (DE) | Loss reduction, Voltage profile improvement | IEEE 33-bus | Convergence issues in large networks | |
Simulated Annealing (SA) | Loss reduction, Voltage improvement | IEEE 33-bus | Risk of local optima, slow convergence | |
Tabu Search (TS) | Loss reduction | IEEE 33-bus | Limited global search capability | |
Ant Colony Optimization (ACO) | Power factor correction, Voltage stability | IEEE 33-bus and 69-bus | Slow convergence in large networks | |
Modified Swarm Optimization | Voltage profile improvement, Reactive power compensation | IEEE 33-bus | Complexity in large networks | |
Proposed study | Multi-Objective Particle Swarm Optimization (MOPSO) | Loss reduction, Voltage profile improvement, Cost minimization | IEEE 33-bus and 69-bus | Higher optimization efficiency, faster convergence, multi-objective adaptability |
