Blockchain-Based Energy Trading Architecture

This project is a prototype implementation of the paper “A Blockchain-Based Architecture for Energy Trading to Enhance Power Grid Stability.”

📚 Project Summary

• 📜 Smart Contracts:contracts/
• 📄 Processed Data:data/
  • Data Format (📦 Source-Sundance):
    1. Consumer:[time(1-based, 24),demand(kW)]
    2. Prosumer:[time(1-based, 24),demand(kW),supply(kW)]
  • Original consumption data: data/consumer(prosumer)/historicaldata
  • Predicted consumption data:data/consumer(prosumer)/predictiondata
  • Real consumption data:data/consumer(prosumer)/realdata
• 📂 Simulation Output:output/
• 🧠 Main Simulation Logic:src/
  • configuration:src/sg_config.py
  • contract compilation & deployment:src/SmDeployments
  • Blockchain interaction:src/Blockchain
  • EMS models:src/Model
  • simulation entry point:src/server.py

⚡ Quickstart

1️⃣ create a virtual environment (recommended)

python -m venv .BTA
source .BTA/bin/activate  
python -m pip install -U pip
pip install -e .

2️⃣ train models for each endpoint

python src/Model/trainModel.py

3️⃣ start a local Ethereum node

# use hardhat
npm install --save-dev hardhat    # install Hardhat (if not installed)
npx hardhat                       # create a project (if not created)
npx hardhat node                  # start local blockchain

# use ganache
# install ganache
ganache -p 7545 -i 1337

# revise RPC_URL, PRIVATE_KEY and CHAIN_ID in 'src/sg_config.py' according to your node

4️⃣ compile and deploy smart contracts

python src/SmDeployments/compile.py
python src/SmDeployments/deploy.py
python src/SmDeployments/getOnChainInfo.py

5️⃣ run the simulation

python src/server.py

6️⃣ get results visualization
(You can run these directly, as example data is already provided for the simulation window [91, 105))

python src/Analysis/plot1.py
python src/Analysis/plot2-1.py
python src/Analysis/plot2-2.py
python src/Analysis/plot3.py
python src/Analysis/plot4.py

7️⃣ modify configuration and re-run

# in src/sg_config.py
CONSUMER_NUMBER = 5
PROSUMER_NUMBER = 10
TIME_WINDOW_START = 91
TIME_WINDOW_END = 105

If you change the number of consumers/prosumers:

# import sundance dataset in dir 'data/rawdata'
python src/DataBean/data_bean.py

re-run above steps again

License

This project is licensed under the MIT License - see the LICENSE file for details.