Static Voltage Stability Analysis Based on the Combination of Dynamic Continuous Power Flow and Adaptive Chaotic Particle Swarm Optimization

This paper proposes a method based on the combination of Dynamic Continuation Power Flow (DCPF) and Adaptive Chaotic Particle Swarm Optimization (ACPSO) to analyze the static voltage stability of the system. The method regards the combination of regulating voltage and controlling variables as particles and the system static voltage stability margin as the fitness value. The maximal adaptation value is the objective function. To solve the problem that there is deficiency in unbalanced power processing when continuous power flowcalculates the particle's fitness value, the dynamic power flow algorithm is introduced into the model of calculating fitness value. According to the principle of Primary Frequency Control, the unbalanced power of the system has been distributed and the DCPF model has been established, to calculate the corresponding fitness value of each particle. The chaos algorithm is introduced into the adaptive particle swarm optimization algorithm to form ACPSO, which is used to search for the optimal particle and calculate the maximum fitness value. By analyzing the relationship between particles and their fitness values, we find a way to improve the system's static voltage stability margin and examples verifythe effectiveness of the algorithm.