Sustainability and Renewable Energy Challenge Winners
MathWorks announces the winners of the 2023 Sustainability and Renewable Energy Challenge. Congratulations and thanks to all the participating students.
1st Place
Selim Mustafa Karaoglu
TH Köln, Germany
Challenge Project completed: Control, Modeling, Design, and Simulation of Modern HVAC Systems
Selim submitted a Simulink® simulation of a modern HVAC system for a typical 4-room apartment in Germany to study thermal dynamics and air quality management for the tailored comfort of a family of four. From a basic thermal model of a single room to a complex simulation that captures the dynamic interactions across the rooms, this solution takes an in-depth look at the problem with detailed environmental controls for temperature, humidity, and air quality, and the inclusion of an air-handling unit with dehumidifying capabilities. A user-friendly interface allows for real-time adjustments to demonstrate the model's ability to maintain comfortable indoor conditions against extreme external temperatures.
Energy efficiency in residential HVAC systems is crucial for reducing the carbon footprint of buildings. By submitting a successful thorough solution to this challenge project, Selim has demonstrated an in-depth understanding of HVAC systems and control engineering. Congratulations to Selim on this first-place solution!
2nd Place
Jaidev Khalane
Indian Institute of Technology Gandhinagar, India
Challenge Project completed: Landslide Susceptibility Mapping using Machine Learning
Jaidev’s submission developed an approach to landslide susceptibility mapping using machine learning. This solution employs a MATLAB-based method to predict and visualize landslide-prone areas for advancement in environmental risk analysis. This solution involves collection and preprocessing of geographical data for training a cascade feedforward neural network, and using the model's predictions to generate a detailed susceptibility map in a target geographic area while leveraging Image Processing Toolbox™ for precise analysis. Technical soundness and user-friendly design are strong points of this solution.
Computational techniques for detection and early warning of disasters such as landslides are a key tool for enabling efficient resource allocation for disaster prevention and management. By successfully completing this challenge project, Jaidev has demonstrated a deep understanding of machine learning, geographic information system (GIS) tools, and their practical application in this important application area. Congratulations to Jaidev on this second-place submission!
3rd Place
Mohamed Khaled, Karim El-lethy, Hazem Hossam, Nourhan Abd Elzaher, Salma Abdelbaset, Mayar Sayed, Aya Hesham
Ain Shams University, Egypt
Challenge Project completed: Techno-Economic Assessment of Green Hydrogen Production
This team of students submitted a comprehensive assessment of green hydrogen production. This solution leverages a first-principles based Simscape™ model of electrolyzer chemistry, solar-powered generation, energy storage, and grid connectivity. A MATLAB® script is developed for automated optimization analysis of hydrogen production costs and reduction on grid energy dependency. Their case study identified Putre, Chile, as an ideal location for a 150KW electrolyzer capacity, selected from 242 potential sites for its high solar irradiance and low grid electricity costs.
As new clean alternative fuels such as green hydrogen emerge as potential solutions, their economic assessment is key for studying viability of adoption at scale. The team's work demonstrates an understanding of how engineering innovation and economic analysis together will enable decarbonization pathways. Congratulations to the team on their third-place solution!
