This repository contains code for a comparative study of traditional and reinforcement-learning-based energy storage control methods. The project evaluates the performance of classical optimal control techniques, such as Pontryagin’s Minimum Principle and Dynamic Programming, against reinforcement learning approaches like PPO, SAC, and TD3.
active 2025-02-20 → 2025-03-13 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 22 days from 2025-02-20 to 2025-03-13. Pushes: 5 total, peak 3 in a day. Pull requests: 0 total, peak 0 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 1 total, peak 1 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| ElinorG11 | 5 | 5 | 0 | 0 |
Recent activity
Latest issues, pull requests and releases
No issue or PR events — this repo's activity is pushes only.
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 1 stars here means stars gained during the window, not the repo's star count.