Quantum-AI-for-Climate

Womanium Quantum+AI 2024 Projects

Please review the participation guidelines here before starting the project.

Do NOT delete/ edit the format of this read.me file.

Include all necessary information only as per the given format.

Project Information:

Team Size:

• Maximum team size = 4
• While individual participation is also welcome, we highly recommend team participation :)

Eligibility:

• All nationalities, genders, and age groups are welcome to participate in the projects.
• All team participants must be enrolled in Womanium Quantum+AI 2024.
• Everyone is eligible to participate in this project and win Womanium grants.
• All successful project submissions earn the Womanium Project Certificate.
• Best participants win Womanium QSL fellowships with NNL. Please review the eligibility criteria for QSL fellowships in the project description below.

Project Description:

• Click here to view the project description.
• YouTube recording of project description - link

Project Submission:

All information in this section will be considered for project submission and judging.

Ensure your repository is public and submitted by August 9, 2024, 23:59pm US ET.

Ensure your repository does not contain any personal or team tokens/access information to access backends. Ensure your repository does not contain any third-party intellectual property (logos, company names, copied literature, or code). Any resources used must be open source or appropriately referenced.

Team Information:

Team Member 1:

• Full Name: Benjamin Kroul
• Womanium Program Enrollment ID: WQ24-x7CcgxUOPWpvHVd

Team Member 2:

• Full Name: Xin Lan Zheng
• Womanium Program Enrollment ID: WQ24-BUulB1qoioS2BsJ

Team Member 3:

• Full Name:
• Womanium Program Enrollment ID: WQ24-

Team Member 4:

• Full Name:
• Womanium Program Enrollment ID: WQ24-

Project Solution:

In this project we demonstrate the potential of quantum computing in optimizing modern electrical grid systems. The overarching goal was twofold: first, to implement state-of-the-art quantum optimization methods that show significant promise in accelerating electrical grid operations in the near future, even on noisy intermediate-scale quantum computers (NISQ), and second, to make a platform that demystifies both electrical grid management and its optimization and allows everyone the access to interact with and learn from these optimizations.

We want to make an accessible portal to show others this potential and pave a pathway for current grid providers to consider quantum computing solutions when planning grid modernization.

1. Translate from open-source data to a pandapower network for classical electrical grid modelling
   1. translating from transnet-models has been implemented
   2. TODO: translate from PSS/E power modelling format
   3. TODO: translate directly from OSM data by inferring electrical circuits in real-time, like transnet/app
2. Run various optimization algorithms on the network classically
3. Use D-Wave quantum annealing to accelerate the optimizations with quantum computing

We solve the following optimization problems with quantum methods:

1. Self-sufficient microgrid formation with predicted loads
2. TODO: Optimal AC power flow equation solving

Project Presentation Deck:

Link a 5min. presentation recording or deck here.