Abstract

With a large number of wind farms integrated into power systems, the load characteristics of the power systems will vary, resulting in the inapplicability of the traditional load model. Thus, it is of great importance to describe the load characteristics of power systems by taking the impact of the integration of the wind power into consideration. This paper first discusses the influence of wind power integration on the original load model. Wind speed, which has the most direct impact on the output of the wind turbine, is introduced as a new variable for load modelling. By combing the voltage variation of the system, a static equivalent load model is proposed in this paper, wherein, the structure of the proposed load model is also discussed. Measurement-based load Modelling with large amount of measurements requires to process a large number of measured data. This paper utilizes the density based clustering algorithm (DBSCAN) to mine the core data, and reconstructs the surface of the load characteristic based on the mined core data. A static equivalent load model with wind power integration is then established. Compared with the model that is modeled directly without data processing, the proposed load model is more accurate.

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