Reliability evaluation method, device and equipment for new energy power system and storage medium

Abstract

The invention discloses a new energy power system reliability evaluation method, and the method selects a net load continuous curve as a wind-light-load scene feature to carry out the data analysis ofa net load, covers the uncertainty caused by the wind, light, load and other factors in original data, and achieves the comprehensive analysis of conditions. Meanwhile, based on the idea of stratified sampling, the daily net load continuous curve is clustered and then the wind-light load scene is stratified, so that the commonality among units in each hierarchy is increased; and then dimension reduction is performed on the original wind-light charge time sequence curve, and each layer of curve is clustered by using a K-means clustering algorithm so that the reduced scene can be enabled to beapplied to the result obtained in the specific occasion while the calculation burden can be reduced, and thus screening can be performed to obtain the optimal scene of which the characteristics accordwith the requirements and the excellent evaluation effect of the power system can be realized. The invention further provides a new energy power system reliability evaluation device and equipment anda readable storage medium, which have the above beneficial effects.

Description

technical field [0001] The present application relates to the technical field of power systems, and in particular to a reliability evaluation method, device, equipment and a readable storage medium of a new energy power system. Background technique [0002] With the rapid development of wind power and photovoltaic technology, the proportion of new energy power generation is gradually increasing. Compared with traditional energy power generation, wind power generation has the advantages of no pollution, renewable and low cost. However, due to factors such as wind and light, new energy power generation has the characteristics of volatility and intermittency, and has a significant impact on the long-term operation of the power system. Therefore, it is of great significance to evaluate the reliability of the power system containing new energy to ensure the safe operation of the power system. [0003] At present, the research on the reliability of power systems containing new e...

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Problems solved by technology

Although the algorithm realizes the selection of wind-load joint typical scenes, in order to preserve the wind, light, load correlation and time-series characteristics of the wind-light-load scene, it is necessary to cluster high-dimensional data, but the K-means algorithm handles high-dimensional The effect of the data is limited, and considering the photovoltaic output will further increase the dimension of the data, resulting in the current clustering algorithm is not ideal for direct clustering of high-dimensional data

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