jaykomarraju/Quantum-Optimization-for-Solar-Farm

This repo hosts code for optimizing solar farm energy storage using Qiskit and quantum algorithms. It includes data preprocessing, QUBO formulation, quantum optimization, and results analysis to improve efficiency, minimize costs, and reduce CO2 emissions.

Quantum Solar Farm Energy Storage Optimization

This project aims to optimize solar farm energy storage management using Qiskit and quantum optimization algorithms. The goal is to improve efficiency, minimize costs, and reduce CO2 emissions while considering constraints such as storage capacity, maximum charge/discharge power, and grid interconnection constraints.

Table of Contents

• Installation
• Usage
• Data
• Contributing
• License

Installation

1. Install Qiskit by following the official documentation.

2. Clone the repository: https://github.com/jaykomarraju/Quantum-Optimization-for-Solar-Farm.git

3. Install additional dependencies (if any) from the requirements.txt file: pip install -r requirements.txt

Usage

• The paper and relevant code is in the format of a notebook and can be found at: Notebook

Data

Place the input data files (solar irradiance, weather data, energy demand data, electricity market prices, and CO2 emissions factors) in the data folder. The code assumes CSV format, but you can adjust the data loading functions if needed.

Contributing

• Fork the repository on GitHub.
• Create a new branch with a descriptive name.
• Commit your changes to the new branch.
• Submit a pull request with a clear description of the changes.