Parameter Identification Of Complex Load Model And Its Effect On Grid Stability

With the continuous development of the power system,large-scale wind power,photovoltaic and other new energy sources in the grid are constantly connected.At the same time,the application of power electronic equipment in the power grid is more and more extensive.These factors make some traditional characteristics of the power grid have more obvious changes.Therefore,in this context,there may be a risk that the existing simulation model parameters are difficult to accurately reflect the real dynamic characteristics of the power grid.At the same time,the interaction of the new energy,load,and power electronic equipment makes the characteristics of the power grid more complex.The wide area measurement system,fault recorder system and manual short circuit test have provided us with a large amount of measured data,but these measured data have not been fully utilized at present.Based on this,the research work done in this article is as follows:(1)On the basis of various existing load models,a complex load model structure including doubly-fed wind turbines is first proposed,and the principles of each part of the complex load model are introduced in detail,and the parameters required to be identified by the model are summarized.To reduce the parameter identification time and improve the identification accuracy,the perturbation method and the median sensitivity method are used to calculate the trajectory sensitivity of each parameter of the complex load model,and the final parameters to be identified and their identification range are selected;(2)To improve the accuracy and applicability of parameter identification,a model parameter identification method based on improved whale optimization algorithm and multi-running curve identification method is proposed.For the basic whale optimization algorithm,there are some disadvantages such as low solution accuracy and easier to fall into local optimization.From the aspects of initialization of Sine chaotic map population,non-linearization of convergence factor,increasing adaptive weight strategy and chaotic optimization,the improved whale algorithm is proposed.Taking the simulation system as an example,the improved whale optimization algorithm is compared with other intelligent optimization algorithms in terms of accuracy and convergence.The results show that the improved whale optimization algorithm has the advantages of faster convergence speed and more accurate identification effect.At the same time,in view of the limitations of single-curve identification,a multi-running curve identification method is proposed.The comparison between the multi-running curve identification method and the single-curve identification method also proves that the identification method is effective;(3)Based on the actual power system,first process the data,and then use the variable impedance method to inject the measured data.MATLAB and PSD-BPA software are used to simulate the actual power grid.The results verify the effectiveness of the algorithm and method proposed in this paper.At the same time,the parameter results before and after the identification are used to analyze its influence on the stability of the power grid.