Inspiration
The rise of AI is straining urban energy systems, yet AI can also optimize them. We wanted a solution that balances sustainability and efficiency.
What it does
Synergy 2050 is a plan for an AI-driven system that allocates and even trades energy across zones. It forecasts demand, manages supply, and integrates both renewable and non-renewables for reliable city-wide energy.
How we would build it
Note: Participation is in Ideathon category We can use ML forecasting, Kubernetes for flexible workloads, and cloud/on-prem compute. A pilot campus setup includes IoT sensors, smart meters, and a dashboard to track live metrics and run A/B tests on potential strategies.
Challenges we would likely run into
Forecasting energy accurately is difficult as anomalies can often appear. The ML's training data may not be perfectly accurate for future conditions.
What we learned
AI can stress and stabilize energy systems simultaneously. Pilot projects test the viability of grand ideas. Cloud orchestration with Kubernetes ensures flexibility and cost efficiency.
What's next for SYNERGY 2050 (idea)
We plan to expand to campuses and add renewable and nuclear sources. This would also help us refine ML models and improve accuracy. Eventually, we plan to integrate into urban developments. Public-private partnerships will help with funding and scaling, supporting UN SDGs 7, 9, and 11.
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