Probability statistics-based method for modeling generalized node characteristics

Abstract

The invention discloses a probability statistics-based method for modeling generalized node characteristics. The method comprises the steps of performing uniformly-spaced sampling on annual data of the voltage and active power at a root bus which is directly connected with a fan; performing compromised segmentation on active power data of annual root bus; performing numerical statement on probability distribution of the active power data of the annual root bus of a wind electric field; extracting a probability characteristic relation expression under each power segment by using a nerve network algorithm; establishing a final node characteristic model of the wind electric field; evaluating the fitting effect of each power segment and the fitting effect of an overall sample respectively. The method disclosed by the invention covers an annual sample rule and does not need to correct the model frequently, so that the method is superior to the conventional method in the aspects of self-description capability and generalization capability, and trend results of all power scenes under wind power fluctuation can be solved according to the segment probability model so as to provide a theoretical guidance for researching probability stability calculation, risk assessment, economic dispatch, wind power absorptive capability and the like.

Description

technical field [0001] The invention relates to a generalized node feature modeling method based on probability statistics. Background technique [0002] Traditional mechanism modeling starts with model selection and parameter identification, which can achieve higher accuracy in many application scenarios. However, in recent years, with the large-scale access of wind power and other new energy sources, its significant impact on the power grid has also achieved industry consensus. From the perspective of node external characteristics, wind power access not only changes the node composition and power flow direction, but also changes in real time with wind power fluctuations, which brings new challenges to node modeling and analysis. [0003] Traditionally, a polynomial model or a power exponential model is commonly used to identify the steady state. In order to characterize the time-varying characteristics of the load, many scholars have proposed the idea of ​​classification ...

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Problems solved by technology

Accurately determining the characteristics presented at the next moment depends on accurate load forecasting and wind power forecasting technologies, but current wind power forecasting cannot meet engineering needs

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