基于图模型的电力系统碳流计算模式优化分析
Optimization Analysis of Carbon Flow Calculation Model Based on Graph Models
王炎 1宋金珠 2李晓东2
作者信息
- 1. 国网河南省电力公司直流中心,河南 郑州 450000
- 2. 国网河南省电力公司超高压公司,河南 郑州 450000
- 折叠
摘要
针对传统碳流计算方法在处理电力系统复杂性方面的局限性,提出了一种基于图模型和图神经网络的电力系统碳流计算模式优化分析方法.该方法将电力系统表示为图结构,充分考虑节点之间的关联关系,更准确地描述碳流分布特征.在此基础上,引入图神经网络优化计算模式,利用其强大的特征提取和关联建模能力,自动学习电力系统中复杂的碳流分布模式.结果表明,所提优化方法在计算精度和效率上具有显著提升,为实现低碳电力系统提供了有力的技术支持.
Abstract
Aiming at the limitations of traditional carbon flow calculation methods in dealing with the complexity of power systems,a graph model and graph neural network-based optimization analysis method for power system carbon flow calculation mode is proposed.This method represents the power system as a graph structure,fully considering the correlation between nodes,and more accurately describing the distribution characteristics of carbon flow.On this basis,the graph neural network optimization calculation mode is introduced,utilizing its powerful feature extraction and correlation modeling capabilities to automatically learn the complex carbon flow distribution patterns in the power system.The results indicate that the proposed optimization method has significantly improved computational accuracy and efficiency,providing strong technical support for achieving low-carbon power systems.
关键词
碳流计算/图模型/电力系统Key words
carbon flow calculation/graph model/power system引用本文复制引用
出版年
2024
NETL
NSTL
万方数据