Final Year Project

Project Title

Smart Energy Management Application for Maximizing Renewable Energy Penetration

Description

Ever since the penetration of renewable energy technologies in commercial and residential use has increased, the complexity of electrical distribution grids has also seen a significant increase. This increased complexity has necessitated the development of advanced analytical tools in order to ensure grid stability and efficiency. This project introduces an open-source distribution network analysis and control tool designed to ensure smooth and efficient power supply while accommodating renewable energy sources. Leveraging OpenDSS and Python, the tool seamlessly integrates real-time analysis and control functionalities on a Raspberry Pi platform, enhancing flexibility and usability. It facilitates automated network modeling, simulation, and analysis, offering optimization features for utility operators to maintain system reliability. By employing modbus communication protocol, the tool establishes a direct link between the virtual environment and real-world sensors and actuators, enabling immediate decision-making and implementation of control strategies based on grid readings. Furthermore, it supports hosting capacity analysis and inverter control modes, crucial for integrating distributed energy resources (DERs) into the grid without compromising stability. The tool operates in two modes, Snapshot and Timeseries, allowing operators to evaluate hosting capacity by assessing reverse power flow and voltage violations. Additionally, it provides control mode options specified in IEEE-1547, such as VoltWatt and Constant Power Factor, enabling operators to optimize DER performance. With its open-source nature, the tool encourages collaboration and customization among utility operators and researchers, facilitating continuous enhancement and scalability. Validation on the standard IEEE-13 Bus System demonstrates the tool's accuracy and reliability, positioning it as a valuable asset for advanced electrical distribution grid analysis and renewable energy integration.