INTEGRATED DATA ACQUISITION PLATFORM FOR EXPLAINABLE CONTROL IN DISTRICT HEATING SYSTEMS

This paper presents a comprehensive data acquisition platform designed for the intelligent management of District Heating Systems (DHS), aiming to optimize energy efficiency, reduce environmental impact, and minimize heat loss. A DHS is a centralized network that transfers thermal energy to multiple buildings via an insulated pipeline infrastructure. Traditional DHS configurations rely on PLCs and SCADA for data collection and heating control, but integrating real-time monitoring and advanced decision-making capabilities can significantly enhance system efficiency. Our Data Acquisition Platform aggregates data from diverse sources, including IoT sensors, weather stations, and smart meters, into a unified database for time-series analysis. The platform supports automated data retrieval through cron job scheduling and integrates with SCADA systems for remote data collection and monitoring. It is integral part of an intelligent DHS control approach named XAI4HEAT. This approach leverages explainable artificial intelligence algorithms and model-based predictive control to dynamically adjust heat supply based on demand and weather forecasts. Key benefits of this approach include improved load balancing, optimized energy distribution, and the potential integration of alternative energy sources.