PowerGraph

We have created a comprehensive graph dataset that models power flow (PF), optimal power flow (OPF), and cascading failure events in power systems. To generate the dataset for PF and OPF, we utilized MATPOWER, and for the cascading failure events, we employed a physics-based cascading failure model called Cascades. This model simulates the propagation of failures within a power grid, resulting in unmet demand (DNS). Each power grid state is represented as a graph, where buses (including loads and generators) form the nodes and branches (including transmission lines and transformers) form the edges.For PF and OPF, we treat the problem as a regression task to predict electrical quantities at the node level. In contrast, for cascading failure analysis, we assign graph-level labels based on the outcomes of the physics-based model. This dual approach allows our dataset to support a variety of tasks, including node regression, graph-level multi-class classification, binary classification, and regression. Additionally, we provide ground-truth explanations for the cascading failure analysis, enabling our dataset to serve as a benchmark for evaluating GNN explainability models in graph-level tasks.<br>The PF and OPF dataset is in 'dataset_pf_opf' for the IEEE24, IEEE39, UK, and IEEE118 bus systemsThe Cascading failure dataset is in 'dataset_cascades' for the IEEE24, IEEE39, UK, and IEEE118 bus systems.

本团队构建了一套面向电力系统的全流程图数据集，可对电力潮流（Power Flow, PF）、最优潮流（Optimal Power Flow, OPF）以及连锁故障事件进行建模。针对PF与OPF数据集的生成，本团队采用了MATPOWER工具；而针对连锁故障事件数据集，则使用了基于物理机理的连锁故障模型Cascades。该模型可模拟电网内故障的传播过程，最终导致未满足需求（DNS）的产生。每个电网状态均以图结构表征：其中母线（包含负荷与发电机）作为节点，支路（包含输电线路与变压器）作为边。针对PF与OPF任务，本团队将其视为节点级电气量预测的回归任务。与之相对，针对连锁故障分析任务，则基于该物理模型的输出结果赋予图级标签。这种双任务适配的设计思路，可支撑多种下游任务，涵盖节点回归、图级多分类、二分类以及回归任务。此外，本数据集还为连锁故障分析任务提供了真值解释（ground-truth explanations），使其可作为评估图级任务下图神经网络（Graph Neural Network, GNN）可解释性模型的基准数据集。
PF与OPF数据集存储于`dataset_pf_opf`目录下，涵盖IEEE24母线、IEEE39母线、英国电网以及IEEE118母线系统。
连锁故障数据集存储于`dataset_cascades`目录下，涵盖IEEE24母线、IEEE39母线、英国电网以及IEEE118母线系统。

搜集汇总

背景与挑战

背景概述

PowerGraph是一个综合性的电力系统图数据集，包含电力流、最优电力流和级联故障模拟数据，支持多种图神经网络任务并提供了真实解释基准。数据集覆盖多个标准电力系统模型，分为两个主要部分存储。