XAI4HEAT SCADA Dataset 2024

Real-world heating data were extracted from the SCADA system of a local District Heating System (DHS) at the Faculty of Mechanical Engineering in Niš, Serbia. The dataset includes one-hour resolution parameters from five substations in residential buildings over five heating seasons, capturing temperatures of the heating fluid in supply and return lines, energy transmission metrics, and outdoor temperatures. It enables research on explainable intelligent control of DHS, focusing on heat demand response and load shifting to optimize performance and sustainability. Additionally, it enhances transparency in urban heat consumption through Explainable AI, offering interpretable insights into heat supply variations and facilitating what-if analyses for stakeholders.本数据集从塞尔维亚尼什机械工程学院当地区域供热系统（DHS）的SCADA系统中提取了真实世界的供热数据。数据集涵盖了五个住宅小区变电站自五个供暖季节以来的每小时分辨率参数，包括供应和回路线中的供热流体温度、能源传输指标以及室外温度。该数据集有助于研究可解释的智能控制DHS，聚焦于热需求响应和负载转移以优化性能和可持续性。此外，通过可解释人工智能增强了城市热消费的透明度，提供了对供热供应变化的可解释洞察，并促进了利益相关者的假设分析。

搜集汇总

背景与挑战

背景概述

该数据集包含从塞尔维亚尼什机械工程学院区域供热系统SCADA系统提取的五个住宅楼宇子站、五个供暖季节的一小时分辨率加热数据，包括供回水温度、能量传输指标和室外温度。它旨在支持可解释智能控制研究，特别是热需求响应和负荷转移，并通过可解释AI增强城市热消费透明度，便于利益相关者进行假设分析。