Solving a Multi-objective Reactive Power Market Clearing Model Using Nsga-ii

This paper presents an application of elitist non-dominated sorting genetic algorithm (NSGA-II) for solving a multi-objective reactive power market clearing (MO-RPMC) model. In this MO-RPMC model, two objective functions such as total payment function (TPF) for reactive power support from generators/synchronous condensers and voltage stability enhancement index (VSEI) are optimized simultaneously while satisfying various system equality and inequality constraints in competitive electricity markets which forms a complex mixed integer nonlinear optimization problem with binary variables. The proposed NSGA-II based MO-RPMC model is tested on standard IEEE 24 bus reliability test system. The results obtained in NSGA-II based MORPMC model are also compared with the results obtained in real coded genetic algorithm (RCGA) based single-objective RPMC models.