The Study Of On-line Load Model Parameters Identification And Modification

Load model is one of the crucial factors that influence the accuracy and reliability of the simulation results. To overcome the shortcomings of basic genetic algorithm in selection and mutation, proportional selection and linear self-adaptive mutation strategies are designed. The developed algorithm is used to identify load model based on measurement-based modeling. Practical modeling process shows that the proposed genetic algorithm is excellent in accelerating convergence, shortening identification time, overcoming dispersivity of model parameters and improving the identification precision. The idea of integrating composite load models in different time slots is proposed to in order to take full advantage of the previous identification results and to reduce identification process. An overview of current research situation of the impact of distributed generation on distribution networks load characteristics is presented. The idea that uses constant-power to depict the output power of grid wind turbine in steady-state and when voltage fluctuation is small is put forward. The power characteristics of DFIG with and without LVRT is discussed, when wind speed are fixed.