Högskolan i Skövde

This thesis presents the development and validation of a smart thermal energy management system designed to reduce grid dependency by dynamically utilizing surplus photovoltaic (PV) energy for building heating and cooling. Implemented within the Helios Hub where PV generation is a core energy source the system integrates Ignition SCADA software, real-time weather data, and historical PV production from June 2021 to simulate surplus-driven operation. The heat pump's thermal behaviour was modelled using empirical and thermodynamic principles, with heating COP derived from manufacturer data and cooling coefficient of performance calculated via a scaled reverse Carnot efficiency model. The control logic prioritized surplus PV energy for thermal operations and switched to grid fallback only when necessary, ensuring uninterrupted heating and cooling delivery. A buffer tank model enabled energy storage and passive redistribution, while SCADA logic dynamically adjusted based on environmental inputs. Real-time simulation demonstrated that 29 MWh/month of PV energy was consumed locally, with only 1.54 MWh/month exported, resulting in a self-consumption efficiency of 93%. The remaining demand was met by the grid, validating the fallback strategy and confirming operational continuity. The system was visualized using the Ignition Vision module, providing an intuitive, high-resolution interface for monitoring energy flows, thermal behaviour, and control states. Limitations included idealized tank modelling, simplified cooling assumptions, and reliance on MySQL for data replay instead of live metering. Nonetheless, the results confirm that SCADA-integrated surplus utilization can significantly enhance energy flexibility, lower operational emissions, and support sustainability objectives. Future work will focus on integrating PV cooling techniques, forecast-driven control, and hybrid SCADA interfaces to extend the system’s adaptability and real-world applicability.