Inspiration We were inspired by NYC's growing solar infrastructure (6 gigawatts and counting) and a critical problem: 10-15% of peak solar energy is lost due to grid limitations. With ConEd's Smart Share already providing data access but no trading capabilities, we saw an opportunity to create a solution that would empower communities to take control of their energy future.
What We Built Grid Energy DAO is a community-powered microgrid platform that enables:
- Peer-to-peer energy trading through email-based wallets (Verbwire)
- IoT-powered energy monitoring and automation
- AI-driven optimization using real-time USEIA data
- Blockchain-based energy credits (GED tokens)
How We Built It
- Frontend: React-based dashboard for energy monitoring and trading
- Blockchain: Polygon L2 for efficient token transactions
- Integration:
- Verbwire API for seamless wallet creation
- IoT system for real-time energy monitoring
- AI prediction engine for optimal energy distribution
Technical Innovation
- Used Verbwire's WaaS for email-based crypto wallets
- Implemented IoT monitoring for automated energy tracking
- Integrated AI for predictive energy distribution
- Built on Polygon L2 for scalability and efficiency
Challenges
Making blockchain accessible to non-crypto users
- Solution: Email-based wallets through Verbwire
Real-time energy monitoring
- Solution: IoT integration with smart meters
Optimal energy distribution
- Solution: AI-powered prediction engine
What We Learned
- Blockchain can solve real-world problems when made accessible
- IoT and AI can work together for better energy management
- Community-focused solutions need simple user experiences
What's Next
- Expand to more NYC neighborhoods
- Enhance AI predictions with more data
- Develop mobile app for easier access
- Partner with more solar providers
Our project demonstrates how emerging technologies can work together to solve real community problems while keeping the user experience simple and accessible.
Built With
- flask
- groq
- javascript
- mongodb
- randomforestregressor
- react
- render
- scikit-learn
- vercel
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