GRIDD
Forecasting solar photovoltaic (PV) power production is hard: As clouds move over PV panels, the power output moves up and down rapidly. To keep the energy grid in balance, operators need to have read
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描述
### ⚡ Project Title: Gridd — AI-Powered Demand Forecasting & Dispatch Optimizer
### 🌍 Problem
Power grids must perfectly balance supply and demand at every second. Overgeneration wastes energy and burns unnecessary fuel. Undergeneration causes outages. Solar/wind variability makes this harder, and grid operators rely on fossil-fuel "spinning reserves" to stay safe — defeating the point of clean energy.
### 🤖 Solution
We use machine learning to forecast energy demand using public smart meter data and weather inputs, enabling:
• Smarter scheduling of generators (esp. renewables)
• Load-shifting recommendations
• Reduced backup fuel reliance
### 🧱 Stack
• ML: XG Boost and Gradient Boost
• Data: Hugging Face and Open Weather Map
• Backend: Python (Fast API) APIs for model inference
• Frontend: Web dashboard (React
### 🔥 Why It Wins
• Tackles a real, high-impact climate+AI problem
• Works with real public data — extensible across countries
• Bridges consumers, grid ops, and policy needs
• Pitchable to startups, governments, and climate NGOs