The Heat Production Optimization project, developed by Group 5 at the University of Southern Denmark (SDU), focuses on optimizing district heating in Heatington. The system supplies heat to 1,600 buildings using a district heating network powered by heat-only boilers and Combined Heat and Power (CHP) units. The goal is to reduce costs, improve efficiency, and maximize profits by optimizing heat schedules and electricity production.
- Automated Heat Scheduling: Intelligent automation for cost-effective heat distribution.
- Economic Optimization: Minimizes fuel consumption and maximizes electricity market profits.
- Data-Driven Insights: Uses real-time heat demand and electricity pricing for smart decision-making.
- User-Friendly Interface: Intuitive controls and graphical visualizations for operators.
- Environmental Benefits: Reduces CO₂ emissions through optimized energy usage.
- Asset Manager (AM) – Manages production unit data.
- Source Data Manager (SDM) – Stores heat demand & electricity prices.
- Result Data Manager (RDM) – Saves optimized heat production schedules.
- Optimizer (OPT) – Core module calculating cost-effective heat schedules.
- Data Visualization (DV) – Provides graphical insights into energy usage and costs.
- Agile Methodology: The project was structured into multiple sprints with iterative improvements.
- Technologies Used: .NET, Avalonia UI, ScottPlot (for data visualization), and Jira for project management.
- Testing: Implemented unit tests, manual testing, and user feedback cycles to improve functionality.
- Optimized heat production schedules for different scenarios.
- Graphical UI for monitoring and controlling heat distribution.
- Reports & Data Logs for analysis and decision-making.
- Integration with real-time electricity pricing APIs.
- More advanced optimization algorithms for dynamic scheduling.
- Enhanced alerts & notifications for better system monitoring.