Dynamic Energy Optimization and CO2 Emission Reduction Using Explainable AI – Amitec’s Contribution to AVEVA Partner Games 2024
At Amitec, we work a lot with today’s energy and environmental challenges. As participants in the AVEVA Partner Games 2024, our team, exAItd – Explainable AI in Time-Series Data, competed in the Power District, presenting a solution titled Dynamic Energy Optimization and CO2 Emission Reduction Using Explainable AI.
This blog post outlines the technical details and benefits of our solution, which leverages AVEVA tools, explainable AI (XAI), and real-time data integration to optimize energy use and reduce environmental impact.
The Challenge: Tackling Energy Costs and CO2 Emissions
Modern industries face growing pressures to achieve net-zero targets while maintaining operational efficiency and reducing costs. The Power District challenge in the AVEVA Partner Games required participants to address these issues with innovative solutions that utilize AVEVA’s extensive technology ecosystem.
Our solution combines dynamic data integration, predictive analytics, and user-friendly interfaces to offer actionable insights for optimizing energy consumption and minimizing CO2 emissions.
Solution Overview: Explainable AI for Energy Optimization
Our system integrates data from multiple sources, including real-time energy prices, grid data, and weather influences. Key components of our solution include:
- Data Integration via ENTSO-E Transparency Connector
- Using a custom connector, we access day-ahead price forecasts, energy generation by resource type, and cross-border energy flows. This data provides a comprehensive view of energy market dynamics.
- Additionally, dynamic energy pricing data from Tibber refines our cost predictions, ensuring accurate recommendations for users.
- CO2 Emissions Calculation
- By analyzing the energy mix, we calculate the associated CO2 emissions in real-time. This allows users to make environmentally conscious decisions by identifying optimal low-emission periods.
- User Interaction Through LLM
- We integrated a Large Language Model (LLM) to enhance user interaction. Users can query the system with natural language questions, such as:
- “When is the cheapest time to use energy?”
Leveraging AVEVA Tools for Seamless Integration
Our solution was built upon key AVEVA technologies, ensuring scalability and robust data management:
- AVEVA PI System, PI Vision, and PI Asset Framework (AF)
- These tools provide a solid foundation for data collection, visualization, and contextualization. The visualization was further enhanced with some advanced symbols like Heatmaps, Sankey diagrams, and Event Frame Editors, enabling intuitive data exploration.
- AVEVA CONNECT (formerly AVEVA Data Hub)
- AVEVA CONNECT enables secure, cloud-based data sharing and analysis across multiple sites. This integration simplifies collaboration and ensures seamless access to real-time and historical data for enhanced analytics.
- Explainable AI (XAI)
- Our use of XAI ensures that the system’s recommendations are fully transparent, building user trust and facilitating informed decision-making.
Advantages of enhancing PI Vision
The additional symbols and tools, enhancing visualization and interactivity, helped us to make the monitoring easier to understand and more valuable. Here we used a mix of these:
- Heatmaps and Sankey Diagrams for visualizing energy flows and identifying inefficiencies.
- Event Frame Editors for precise tracking of operational events.
- High-Availability Add-Ons to ensure critical displays remain operational at all times.
- Seeq Integration for seamless advanced analytics within PI Vision.
These enhancements empower users to gain deeper insights, streamline workflows, and improve decision-making processes.
Practical Application: Smarter Energy Decisions
A typical use case involves a user asking, “When should I run my washing machine?” The system evaluates real-time energy prices and CO2 emissions, providing recommendations that align with either cost-saving or environmental goals.
This capability extends to industrial applications, where optimizing energy-intensive processes can result in substantial cost and emission reductions.
Benefits of the Solution
Our approach offers clear benefits to technical and operational teams:
- Cost Savings: Reducing energy expenses by aligning consumption with low-price periods.
- Environmental Sustainability: Lowering carbon footprints through data-driven emission analysis.
- Operational Efficiency: Advanced analytics provide actionable insights into energy patterns, enabling smarter resource management.
- User Empowerment: The LLM interface allows non-technical users to interact effortlessly with complex datasets.
Let’s Collaborate
We’d love to hear your thoughts or discuss potential collaborations. For a deeper dive into our solution, feel free to reach out or schedule a demo. Let’s work together to drive smarter, greener energy solutions!
