Study on Small Sample Data Parameter Identification for Power System Static Load Model

Using traditional least squares criterion suitable for big sample data to identify the parameters, the small data quantity, the noise disturbance and the unusual data will bring about some adverse effects. In order to overcome these adverse effects, minimum sum of absolute residual criterion suitable for small sample data is applied to identify model parameters in this article. Genetic algorithm is used to gain the optimal solution of the parameters. Proved by the practical example, higher accuracy and reliability can be obtained by using this method to build model.