Integrated Supervisory Control and Data Acquisition System for Optimized Energy Management: Leveraging Photovoltaic and Phase Change Material Thermal Storage

Abstract

Reliable energy sources are crucial for both economic growth and quality of life. In developing countries, where expensive fuels are often the primary energy source, governments are exploring innovative solutions like small-scale, IoT-based projects to achieve energy independence in buildings. This research investigates the integration of renewable energy technologies, statistical modeling, cloud computing, and IoT to develop a self-managing energy system for buildings. The system prioritizes renewable sources, specifically monocrystalline solar cells with 20% efficiency for photovoltaic (PV) energy and flat plate collectors with 90% efficiency and minimal energy loss for thermal energy. Thermal energy is stored in paraffin wax, chosen for its high storage efficiency and thermal properties. The system also utilizes an absorption chiller with a high coefficient of performance (COP) to provide cooling using solar thermal energy. The building's energy loads are categorized as A, B, C, and D, each utilizing both PV and thermal energy. A SCADA system oversees the operation, monitoring the on–off status of these loads. The system is designed for continuous operation, with simulations conducted using Anaconda Jupyter Notebook and Python. This model aims to offer a sustainable and efficient energy solution for buildings, meeting energy demands while optimizing energy use.