Microgrid Using Intelligent Variable Droop Coefficient for Power Quality Improvement

An intelligent variable droop coefficient estimation is proposed for a droop controlled microgrid operated in islanded mode to improve the transient performance under the sudden load variation. Owing to the constant droop coefficient of the active power/frequency droop characteristic, the traditional droop controlled microgrid has some disadvantages, such as slow transient response and poor disturbance rejection, resulted in the degenerate stability and poor power quality. Hence, the conventional droop controlled microgrid using the fixed droop coefficient is unable to provide the load support instantly, which has been distinguished as the tardy load support issue. In this study, a novel variable droop coefficient estimation is proposed to overcome the shortcomings of the traditional droop controlled microgrid under the sudden load variations. Moreover, a probabilistic fuzzy neural network (PFNN) considered as an angular frequency controller is adopted for the proposed variable droop coefficient estimation to rapidly estimate the suitable droop coefficient of the microgrid. Finally, some simulation results are provided to verify the effectiveness of the droop controlled microgrid using the PFNN-based variable droop coefficient estimation for the power quality improvements under sudden load variation.