Study on unbalanced power flow in distribution network with distributed generators of power grid

With rapid increase in wind power penetration into the power grid, unbalanced power flow in distribution network with distributed generators is becoming increasingly important to power sysytem. Due to the variability and uncertainty of wind, such traditional unbalanced power flow analysis method for distributed power supply limit the use of the existing tools for decision-making under uncertain conditions. As a result, unbalanced power flow analysis method, which provides information on uncertainty associated with wind power analysis, is gaining increased attention. This paper presents a novel hybrid intelligent algorithm for deterministic unbalanced power flow in distribution network with distributed generators that utilizes a combination of Cauchy particle swarm optimization(CPSO) and fuzzy ARTMAP (FA) network, which is optimized by using PSD-BPA. The performance of the proposed model is assessed utilizing wind power data from the Baolihua wind farm in Southern China. Unbalanced power flow in distribution network with distributed generators is researched. The typical static load model is established and the impact of distributed generators on feeder voltage profile is analyzed under unbalanced loads. The simulation results are given. References for the global planning of unbalance compensation in distribution network can be provided by the study.