Högskolan i Skövde

This thesis designs and evaluates a simulation-based Supervisory Control and Data Acquisition (SCADA) Energy Management System (EMS) for the HelioS Energy Hub at the University of Skövde. The Hub, equipped with a 200 kWp rooftop photovoltaic (PV) installation, monitors building loads and electric vehicle (EV) charging stations, but currently lacks an integrated con-trol framework, resulting in frequent PV surplus exports. To address this, a simulation-based EMS of the electrical subsystem was developed in Ignition SCADA using historical monthly data on PV generation, building demand, and grid exchange, complemented by simulated EV charging stations (EVCS) and a virtual battery energy storage system (BESS). Two surplus management strategies were evaluated: (i) direct allocation of PV surplus to EV charging, and (ii) storage of surplus in the BESS with state-of-charge-constrained discharge. Control logic, implemented with Python scripts, governed real-time allocation, efficiency-adjusted charging and discharging, and EV charging behaviour, while a Human-Machine Interface (HMI) supported operator monitoring and interaction. Results showed that Scenario 1 enabled EVs to absorb 69% of PV surplus energy, while Scenario 2 increased utilisation to 78% and reduced grid imports by about 3% through BESS integration. These findings demonstrate how SCADA-based EMS solutions can implement demand-side management strategies such as load shifting, peak shaving, and surplus absorption, thereby enhancing renewable self-consumption, reducing grid dependency, and improving cam-pus energy flexibility. Beyond technical outcomes, the thesis also highlights the contribution of such systems to the UN Sustainable Development Goals (SDGs) in the areas of clean energy, resilient infrastructure, sustainable communities, and climate action.