Smart Control of Photovoltaic Systems

This lecture presents a project focused on increasing self-consumption in households by utilizing the thermal inertia of a hot-water tank. Starting with a heuristic algorithm for optimizing power profiles, the lecture explores the development of rule-based and indicator-based solutions to enhance grid fluxes and system wear. The latter approach, based on indicators, proves to be the most efficient, cost-effective, and parameter-less. Additionally, the integration of electric heating into the algorithm improves peak response and self-consumption flexibility. The lecture emphasizes the robustness of the algorithm in forecasting weather and consumption data, ensuring low costs due to unpredictable events. Ultimately, the tool efficiently stores excess PV production as heat in existing facilities.