🌱 LCA & CO₂ Dashboards for Smart Energy Systems

To empower participants with practical tools and strategies to design, develop, and interpret Life Cycle Assessment (LCA) and carbon dashboards that track environmental impact and CO₂ emissions across smart energy systems, supporting data-backed decisions toward net-zero goals.

• Introduce participants to LCA as a tool for sustainable energy planning

• Enable hands-on creation of carbon dashboards with real or simulated data

• Promote transparency and traceability in emission metrics

• Support green reporting, regulatory alignment, and net-zero initiatives

• Foster a data-driven mindset in smart grid design and energy systems planning

Day 1: Machine Learning for Renewable Integration

• Introduction to Load Forecasting

  • Basics of energy demand and load profiles

  • Challenges in forecasting with renewables

• Machine Learning Models

  • Time-series forecasting techniques (ARIMA, LSTM, etc.)

  • Feature engineering and data preprocessing

• Case Studies & Hands-on

  • Solar and wind integration forecasting projects

  • Python walkthrough: Forecasting electricity demand

Day 2: Reinforcement Learning for Real-Time Demand Response

• Introduction to Reinforcement Learning (RL)

  • Key concepts: Agent, environment, reward, policy

  • RL vs. supervised learning in energy systems

• RL for Demand Response Applications

  • Real-time grid balancing with DR programs

  • Dynamic pricing and energy flexibility

• Simulations & Deployment

  • Hands-on with OpenAI Gym & Grid simulators

  • RL models for household or commercial DR control

Day 3: Life Cycle Assessment (LCA) & CO₂-Impact Dashboards

• Fundamentals of LCA

  • Cradle-to-grave assessment of energy systems

  • Key metrics: GWP, energy payback time

• CO₂ Dashboards for Monitoring Impact

  • Tools & platforms for CO₂ tracking

  • Dashboard design and visualization (Power BI, Streamlit)

• Practical Implementation

  • Create your own carbon impact dashboard

  • Use cases: Smart buildings, EVs, and microgrids

• Understand the lifecycle emissions of energy technologies

• Build interactive dashboards to visualize carbon and environmental data

• Apply LCA and CO₂ modeling tools in real-world projects

• Analyze trade-offs and scenarios for energy decarbonization

• Receive certification and access to open-source templates for future use

• Energy engineers and sustainability managers

• ESG analysts and carbon auditors

• Data scientists working in climate-tech

• Urban planners and green infrastructure consultants

• Students (UG/PG/PhD) in energy, environment, or data analytics