Application of efficient self-adaptive differential evolutionary algorithm for voltage stability analysis under practical security constraints

• Efficient and robust SADE algorithm is developed.
• Two innovative formulas for mutation factor and crossover rate are designed.
• New mathematical modeling of the objective function is developed considering SC.
• The proposed algorithm provides satisfactory results for all types of systems.
• For all cases, the best performances are achieved for the SADE algorithm.

In the deregulated energy market, detection of weaker buses, ceiling points are essential to avoid possible voltage collapse for the preventive control actions and voltage security assessment. In this paper, unique self-adaptive differential evolutionary (SADE) technique is developed to detect the ceiling point (CP), weaker buses under practical security constraints. Considering the best, worst and current objective functions, both crossover rate (CrCr) and mutation factor (FF) of DE algorithm are so designed that those tuning parameters will be adaptive with the generation. The new mathematical modeling of the objective function is developed considering the actual security limitations. For both standard IEEE test systems and ill-conditioned systems, the performances of the proposed algorithm are compared with the other evolutionary techniques like ordinary differential evolution (ODE), general particle swarm optimization (GPSO), real coded genetic algorithm (RCGA). The best performances in terms of convergence rate, success rate, and ceiling point are achieved for the SADE algorithm because of the innovative formula of adaptive CrCr and FF. The FACTS devices are placed on the weaker buses. In this paper, the weaker buses are also detected. Showing characteristics and results, the robustness and efficiency of the proposed algorithm are established.