Details

Autor(en) / Beteiligte

• Sun, Tingxi
• Guo, Xiaokai
• Cui, Jiangjing
• Nan, Baofeng

Titel

The Analysis of Multi Objective Reactive Power Optimization Based on Improved Particle Swarm Algorithm

Ist Teil von

• 2023 International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE), 2023, p.1-6

Ort / Verlag

IEEE

Erscheinungsjahr

2023

Quelle

IEEE Xplore

Beschreibungen/Notizen

• This paper discusses the Multi-Objective Reactive Power Analysis of the improved particle swarm optimization algorithm, adjusts the transformation ratio of the on load regulating transformer, and changes the output measures of the reactive power compensation device, so that the system can achieve the optimization of multiple performance indicators under the premise of meeting the relevant constraints. The traditional particle swarm optimization algorithm has local extremum problem, and the optimization results are different from the actual results. In order to improve the limitations of particle swarm optimization, the simulated annealing algorithm is introduced to weight the PSO to improve the accuracy of calculation. The simulation results show that the improved particle swarm optimization algorithm optimizes the terminal voltage and reactive power compensation measures of reactive power target, and obtains a more effective power system optimization scheme. Therefore, the improved particle swarm optimization algorithm provides more accurate guidance for multi-objective non-function analysis, and adjusts the terminal voltage and power compensation measures of reactive power target.