基于SOM-Kmeans算法的自备电厂参与新能源消纳状态判断方法

Jijun Dong, Zhijun Bai, Xiaohua Liu, Hangming Liu, D. Peng, Huirong Zhao, Mingming Pan, Jindou Yuan
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引用次数: 0

摘要

波动型可再生能源并网比例高,对电力系统的稳定性和灵活性提出了新的要求。在供给侧结构性变化和新电改的大环境下,如何协调自主电厂与电网的发展面临新的挑战。判断自有电厂参与新能源消纳的条件是电厂源网互动的重要前提。因此,本文提出了一种基于SOM-Kmeans算法的新能源消纳交互场景下自主电厂参与条件判断方法。首先,根据一年内的日风速和光照强度数据,通过新能量输出模型得到风机和光伏发电机组的日出力数据。其次,对新能源输出场景进行聚类和裁剪,基于SOM-Kmeans算法得到典型的新能源输出场景;最后,对典型输出场景进行分析,结合自备电厂日前发电计划数据,判断自备电厂的响应量和响应时间条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Condition Judgment Method of Self-owned Power Plant Participating in New Energy Consumption Based on SOM-Kmeans Algorithm
The high proportion of fluctuating renewable energy connected to the grid puts forward new requirements for the stability and flexibility of the power system. Under the environment of supply side structural change and new electricity reform, how to coordinate the development of self-owned power plants and power grids faces new challenges. The judgment of the conditions for the participation of self-owned power plants in new energy consumption is an important prerequisite for the source-network interaction of the power plant. Therefore, this paper proposes a method based on SOM-Kmeans algorithm to judge the participation conditions of self-owned power plants in the interactive scene of new energy consumption. Firstly, based on the daily wind speed and illumination intensity data within a year, the sunrise force data of fans and photovoltaic power generation units are obtained through the new energy output model. Secondly, the new energy output scenes are clustered and cut, and the typical new energy output scenes are obtained based on the SOM-Kmeans algorithm. Finally, the typical output scenes are analyzed, and the response quantity and response time conditions of the self-supplied power plant are judged by combining the day-ahead generation plan data of the self-supplied power plant.
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