Dynamic Multi-Groups Self-Adaptive Differential Evolution Algorithm with Local Search for Reactive Power Optimization

This paper proposes a novel algorithm, dynamic multi- groups self-adaptive differential evolution with local search (DMSDELS), for reactive power optimization of power system. The objective of optimization is minimizing active power losses in transmission network while maintaining the quality of voltages. The new method is tested on IEEE 118-Bus power system. The numerical results, compared with other stochastic search algorithms, show that DMSDELS could find high-quality solutions with more reliability and efficiency.