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tags:
- stable-baselines3
- power-grid
- ppo
- lstm
- electricity
- reinforcement-learning
- forecasting
- tensorflow
- gym
license: mit
---
# ⚡ Power Grid Optimization with LSTM + PPO
This repository showcases a hybrid deep learning + reinforcement learning system for power grid optimization in Lauderdale County, AL. The system forecasts demand using a weather-informed LSTM model and trains a PPO-based agent to maintain stability and minimize blackout risk under stress.
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## 📈 Models
- **LSTM Demand Predictor**
A deep bidirectional LSTM with attention, trained on 4 years of TVA and weather data.
- **PPO Grid Policy**
Trained in a custom `PowerGridEnv` with generator output, transformer tap, and load shedding control.
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## 🧠 Dataset Overview
- **Demand Data:**
Sourced from the U.S. EIA (TVA region, 2021–2024)
- Demand, Net Generation, Day-Ahead Forecasts, Interchange
- **Weather Data:**
Daily min/max temperatures + precipitation
- From 5 major TVA-region airports via NOAA
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## 🧮 LSTM Model
- **Architecture:**
2-layer bidirectional LSTM + attention, followed by global pooling and dense layers.
- **Key Features:**
- Rolling temperature windows, demand lags
- Weekly mean demand, change rate
- Temp volatility, extreme flags
- **Metrics:**
| Metric | Value |
|---------------|--------------------|
| R² | 0.911 |
| RMSE | 19,565 MWh |
| Mean Error | 713 MWh (overbias) |
| Beats TVA Forecast | 70.08% of days |
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## 🤖 PPO DRL Agent
- **Environment:**
PyPSA-based Lauderdale County grid
- 6 generators (Nuclear, Hydro, CCGT)
- Load centers with realistic demand shares
- Thermal constraints, ramp limits, marginal costs
- **Action Space:**
- Generator control
- Transformer tap shift
- Load shedding (up to 20%)
- **Reward Design:**
✅ Balance demand/supply, low thermal overload
❌ Penalize instability, overloads, excessive cost
- **Training:**
- Algorithm: PPO (SB3)
- Timesteps: 400,000
- VecNormalize, 5 eval episodes per 2048 steps
- **Metrics:**
| Metric | Value |
|--------------------|-----------|
| Mean Reward | ~1480 |
| Explained Variance | Up to 0.85 |
| Blackout Risk | < 5% |
| Load Shedding | < 3% avg |
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