COCOON pv_2_3 input dataset and results

Power Systems State Estimation Results - COCOON Project This repository contains a dataset and a set of results derived from a cybersecurity-oriented analysis carried out within the framework of the European COCOON project. The data focus on power system state estimation applied to a photovoltaic (PV) plant, with the objective of assessing the resilience of monitoring functions against cyberattacks, specifically False Data Injection (FDI). In line with COCOON’s vision of strengthening cyber-physical security in Electric Power and Energy Systems, the analysis evaluates both the detection and identification of malicious data manipulations, contributing to improved trustworthy information exchange between TSOs, DSOs, aggregators, and distributed renewable energy sources. This repository contains the results of the power systems state estimation developed by the University of Seville (USE), focusing on the monitoring and security of PV infrastructures. Description of the PV Plant The analysis is based on a PV plant layout consisting of two Medium Voltage (MV) feeders, each equipped with 3 inverters. The inverters are connected to the MV feeder through transformers, and the plant evacuates energy to the main grid via an electrical substation. The following files in the root directory define the system's topology and monitoring setup: pv_2_3.svg: A graphical representation of the PV plant. Measurements are assumed to be available at all points marked with red squares in this diagram. pv_2_3.json: A data file containing the technical parameters and connectivity of the network. meas.zip: A compressed archive containing the measurements considered for the state estimation analysis. Repository Structure The code and results are organized into multiple folders, each representing a specific test case or scenario. Each folder follows a consistent internal structure: /test_case_name/ │ ├── data/ # JSON files containing results from simulation tests ├── figs/ # Graphical representations (plots, charts, etc.) of the results └── README.md # Interpretation and explanation of the specific test case Folder Details: data/: Contains .json files with the output data generated from the simulations. These files can be used for further analysis or validation. figs/: Includes visualizations of the simulation results (PDF format). These plots help in understanding trends, anomalies, and overall system behavior. README.md: Each test case includes its own documentation offering key findings and relevant notes for understanding the results. Analysis Methodology All test cases are analyzed from two perspectives to evaluate system resilience: Detection Phase: Focuses on determining whether a cyberattack has occurred. This involves evaluating the system's ability to distinguish between normal operation and compromised scenarios. Identification Phase: Aims to identify which specific measurement(s) have been manipulated by the attacker. This allows for a deeper understanding of the attack vector and its impact on the system. For both aspects, relevant metrics are provided to quantify the performance of the detection and identification processes, as well as their effects on the accuracy of the state estimation. If further details are required or any questions need clarification, please contact Álvaro Rodríguez at [e-mail].电力系统状态估计结果——COCOON项目 本仓库收录了依托欧洲COCOON项目框架开展的面向网络安全的分析所生成的数据集与一系列结果。该数据集聚焦于应用于光伏（Photovoltaic, PV）电站的电力系统状态估计，核心目标为评估监控功能抵御虚假数据注入（False Data Injection, FDI）网络攻击的韧性。 契合COCOON项目强化电力与能源系统信息物理安全的愿景，本次分析同时覆盖了恶意数据篡改的检测与识别环节，有助于提升输电系统运营商（Transmission System Operators, TSOs）、配电系统运营商（Distribution System Operators, DSOs）、聚合商与分布式可再生能源之间的可信信息交互水平。本仓库包含塞维利亚大学（University of Seville, USE）开发的电力系统状态估计相关结果，研究重点为光伏基础设施的监控与安全防护。 ## 光伏电站说明 本次分析基于一款包含两条中压（Medium Voltage, MV）馈线的光伏电站拓扑布局，每条馈线配备3台逆变器。逆变器通过变压器连接至中压馈线，该电站通过一座变电站将电能输送至主电网。 根目录下的以下文件用于定义系统拓扑与监控配置： - pv_2_3.svg：该图形文件直观展示了光伏电站的结构，本分析假设该图中所有红色方块标记的点位均可获取测量数据。 - pv_2_3.json：包含电网技术参数与网络连通性的数据文件。 - meas.zip：压缩归档文件，内含用于状态估计分析的各类测量数据。 ## 仓库组织结构 代码与分析结果被划分为多个文件夹，每个文件夹对应一个特定的测试用例或场景。所有文件夹均遵循统一的内部结构： /test_case_name/ │ ├── data/ # 存储仿真测试生成结果的JSON文件 ├── figs/ # 分析结果的可视化图表（折线图、柱状图等） └── README.md # 对应测试用例的解读与说明文档 ### 文件夹详情 - data/：内含仿真实验生成的输出数据JSON文件，可用于后续二次分析或结果验证。 - figs/：收录仿真结果的可视化文件（均为PDF格式），这些图表可辅助研究人员理解系统运行趋势、异常特征与整体行为特性。 - README.md：每个测试用例均配有专属文档，其中包含核心研究结论与有助于理解结果的相关注释。 ## 分析方法论 所有测试用例均从两个维度展开分析，以评估系统抵御网络攻击的韧性： 1. 检测阶段：聚焦于判定是否发生了网络攻击，即评估系统区分正常运行工况与受攻击场景的能力。 2. 识别阶段：旨在确定攻击者篡改了哪些具体的测量数据，从而能够深入解析攻击路径及其对系统的影响。 针对上述两个分析环节，均提供了对应的量化指标，用于评估检测与识别流程的性能，及其对状态估计精度的影响。 如需获取更多细节或有任何疑问，请联系Álvaro Rodríguez，邮箱地址为[e-mail]。