NSGA-II Multi-Objective Reactive Power Optimization Algorithm

In this article, we discuss a multi-objective reactive power optimization algorithm called NSGA-II. This algorithm integrates genetic algorithms, non-dominated sorting, and forward-backward sweep power flow calculations. The NSGA-II algorithm is designed to solve reactive power optimization problems in power grids. The core approach involves using genetic algorithms to search for optimal solutions while employing non-dominated sorting to obtain a diverse set of Pareto-optimal solutions. The forward-backward sweep power flow calculation method validates the feasibility of discovered solutions by iteratively solving voltage magnitudes and angles. Notably, the algorithm's implementation typically includes population initialization with reactive power control variables, tournament selection for parent chromosomes, simulated binary crossover for offspring generation, and polynomial mutation for maintaining diversity. The algorithm's application scope is extensive, covering various power system types including traditional AC power systems, DC power systems, microgrids, and distributed generation scenarios. Therefore, NSGA-II stands as one of the most significant algorithms in contemporary power system optimization research.