You’ll get free Google Cloud access during the event—no credit card needed.
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Make sure you’re signed into a Gmail/Google account.
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Open our event’s unique link: https://trygcp.dev/claim/gdg-other-ai-accelerate-hack
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Follow the prompts to activate your account and access the Google Cloud Console.
Google Cloud Platform offers all the tools of the google cloud development environment to build your applications. It also offers free Gemini API Keys so you can leverage the full potential of generative AI during today's hacking!
These are some of the services the GCP offers ranging from backend & storage to scheduling and ML workloads. Some of them might be interesting to leverage during this case, especially the services enablign AI services!
- Vertex AI : Train/host custom models, embeddings, batch prediction, Model Garden.
- Vision API : Labels, OCR, object detection.
- Speech-to-Text / Text-to-Speech : Voice features.
- Translation API : Multilingual apps fast.
- Vertex AI Workbench : Managed notebooks; GPUs/TPUs if available.
GCP offers a broad range of other services to allow for cloud deployment of applications. Feel free to check out the possibilities of GCP for your hacking today or future projects!
Welcome to the NOX Energy Hackathon! This repository contains everything you need to participate in the challenge.
This hackathon challenges you to work with real Belgian energy market data to build solutions that demonstrate your understanding of energy systems, data analysis, and innovative thinking.
Read the full challenge details in docs/NOX_Energy_tech_guidelines.pdf
You have access to three datasets containing Belgian energy market information:
File: data/dam_prices.csv
Contains electricity prices traded one day in advance:
- Frequency: 15-minute intervals
- Period: 2024-2025
- Unit: EUR/MWh
- Columns:
datetime_utc,date,hour,minute,price_eur_mwh
File: data/imbalance_forecast.csv
Forecasted prices for grid balancing:
- Frequency: 1-minute intervals
- Period: May 2024 - 2025
- Unit: EUR/MWh
- Columns:
datetime_utc,date,hour,minute,second,price_eur_mwh
File: data/imbalance_actual.csv
Real imbalance prices from the grid:
- Frequency: 15-minute intervals
- Period: July 2024 to 2025
- Unit: EUR/MWh
- Columns:
datetime_utc,date,hour,minute,price_eur_mwh
Start here: Open docs/NOX_Energy_tech_guidelines.pdf for:
- Complete challenge description
- Technical requirements
- Evaluation criteria
- Submission guidelines
- API access information (if needed)
Quick exploration script:
# View first few rows
head -20 data/dam_prices.csv
head -20 data/imbalance_forecast.csv
head -20 data/imbalance_actual.csv# Create virtual environment
python3 -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
# Install common dependencies (adjust as needed)
pip install pandas numpy matplotlibDevelop your solution based on the requirements in the technical guidelines.
nox-energy-hackathon/
├── README.md # This file
├── docs/
│ └── NOX_Energy_tech_guidelines.pdf # FULL CHALLENGE DETAILS - READ THIS!
│ └── NOX KULeuven Hackaton Presentation.pdf # NOX & Case presentation
└── data/ # Energy market data
├── dam_prices.csv # Day-Ahead Market prices
├── imbalance_forecast.csv # Imbalance forecasts
└── imbalance_actual.csv # Actual imbalance prices
Day-Ahead Market (DAM)
- Electricity prices set for the next day
- Traders buy/sell energy 24 hours in advance
- More stable and predictable
Imbalance Prices
- Real-time grid balancing costs
- Occur when actual consumption ≠ planned consumption
- More volatile than DAM prices
Negative Prices
- Yes, electricity prices can be negative!
- Happens during excess renewable generation
- Producers pay consumers to use electricity
import pandas as pd
# Load data
dam = pd.read_csv('data/dam_prices.csv')
dam['datetime_utc'] = pd.to_datetime(dam['datetime_utc'])
# Basic analysis
print(f"Average price: {dam['price_eur_mwh'].mean():.2f} EUR/MWh")
print(f"Min price: {dam['price_eur_mwh'].min():.2f} EUR/MWh")
print(f"Max price: {dam['price_eur_mwh'].max():.2f} EUR/MWh")You can also query live data from:
- ENTSOE Transparency Platform: Day-Ahead Market Prices
- Elia Open Data: Imbalance Prices
See the technical guidelines PDF for API details.
As described in the technical guideline, you will need to send in a total of 4 predictions from 18:29 to 19:29.
Your solution must produce a CSV file with predictions in the following format:
Columns:
datetime_utc- Timestamp in UTC (e.g.,2024-01-01 00:00:00)price_eur_mwh- Predicted price in EUR/MWh (numeric)
Example output file:
What to submit by email at 18:29:
datetime_utc,price_eur_mwh
2025-10-29 18:30:00,45.50- Use UTC timezone for all timestamps
- Match the time interval specified in the guidelines
- Ensure no missing values
- Sort by datetime ascending
Detailed submission instructions are in the technical guidelines PDF.
General checklist to provide at:
- ✅ Follow the deadline specified in guidelines for the submissions of the predictions by email
- ✅ At 19:30, provide the source code and solution documentation
- ✅ Include any required visualizations or reports
Technical & Logistics: Martin Michaux
Technical: Adrien Debray
- ENTSOE Transparency Platform
- Elia Open Data Portal
- Open-Meteo Weather API (for renewable correlation)
NOX Energy is pioneering smart energy management solutions, combining AI, IoT, and energy expertise to optimize energy consumption, reduce costs, and accelerate the renewable energy transition.
Good luck! ⚡
For complete challenge details, evaluation criteria, and requirements, please refer to the technical guidelines PDF in the docs folder.