Data-driven high-proportion renewable energy power system operation scene identification method
A renewable energy and power system technology, applied in the direction of electrical digital data processing, special data processing applications, information technology support systems, etc., can solve the problems of identifying high-proportion renewable energy power system operating scenarios and their changing laws The effect of improving identification ability and improving operation efficiency
Active Publication Date: 2021-01-26
TSINGHUA UNIV +1
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The invention provides a data-driven high-proportion renewable energy power system operation scene identification method, and belongs to the technical field of power system operation. The method comprises the following steps: firstly, carrying out refined operation simulation on a to-be-identified power system to obtain a daily operation mode vector corresponding to the system; preprocessing all daily operation mode vectors by using a principal component analysis method to obtain a preprocessed power system operation mode matrix; determining a typical operation scene of the power system through a Kmeans + + algorithm and the compactness index of the operation mode of the power system; and realizing visualization of the operation characteristics by utilizing a t-SNE algorithm to obtain an extreme operation scene. According to the method, a typical scene in planning and operation can be effectively determined by using a data driving method, an extreme operation mode in protection and stability analysis can be rapidly identified, important reference can be provided for planning and operation personnel of a power system, and the analysis capability of the high-proportion renewable energy power system is improved.
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