Study on the Reduction of Identified Parameters of the Power Load´s Aggregated Motor Model with the Aim of Sustaining Its Representability

There exists a fatal disadvantage for the integrated induction motor load model of too many parameters, which leads to the difficulty of finding optimal parameters set in the identification process. For this reason, a model parameter reduction method is proposed in this paper, which divides the above 14 parameters into two parts: one fixed parameters part alpha_F and the other part alpha_C : parameters needing identification. After defining of the representability of the load model, the criterion of rational division of alpha_F and alpha_C is set as remaining the representability of the load model. Thus the strategy of parameter reduction belongs to the optimization methods. For avoiding the large scale optimizing process, the reduction method of building priority sequence based on parameters´ sensitivity is proposed. In the end, a case study is given out on the basis of certain power grid measurement data, which verified the simplicity and effectiveness of the proposed method