33-, 119-, and 136-bus system data for reinforcement learning-based distribution network reconfiguration

The 33-, 119-, and 136-bus datasets are important resources for training AI algorithms in improving electrical distribution networks. These datasets help create smart programs that learn how to change power grids for the better. In the 33-bus dataset, there are 33 points connected by lines and switches. It helps researchers make programs that reduce power loss, improve voltage, and work more efficiently. The 119-bus dataset is a bit harder. It has more parts like transformers and capacitors. This helps researchers make smarter programs that can handle more complicated situations. The 136-bus dataset is the most challenging. It's like a big puzzle with 136 points and many complicated pieces. Researchers use it to see if their programs can handle really complex situations. All these datasets give a fair way to test how well AI programs can make electricity distribution better. The programs made using these datasets could help make electricity networks work smoother and save energy. So, the 33-, 119-, and 136-bus datasets are like training tools that could help make our power systems smarter and more efficient.