An AI-powered daily literature mining system for power systems and energy forecasting research. Automatically fetches, scores, and summarizes the latest papers from arXiv and other sources — delivering a daily research brief to your inbox or dashboard.
Keeping up with the energy systems literature is a full-time job. This tool automates it: every day, it scans for new papers in electricity forecasting, microgrids, and energy optimization — then uses AI to extract the key findings.
- Daily arXiv Crawling — automated fetch of latest preprints in power systems
- AI-Powered Summarization — LLM-generated summaries of key contributions
- Relevance Scoring — papers ranked by relevance to your research focus
- Web Dashboard — browse daily papers with an interactive UI
- WeChat / Email Push — daily digest delivered automatically
- SOTA Tracking — track state-of-the-art results over time
# Clone and install
git clone https://github.com/disdorqin/power-papers-daily.git
cd power-papers-daily
npm install
# Configure your research interests
cp .env.example .env
# Edit .env with your API keys and preferences
# Run the daily fetch
npm start
# Or set up auto-run with GitHub Actions (already configured)See the live dashboard for today's papers.
Papers are scored on:
- Time relevance (how recent)
- Journal impact (where published)
- Citation velocity (how fast it's being cited)
- Topic alignment (match with your research)
- Daily arXiv ingestion
- AI summary generation
- Web dashboard
- Integration with DARIS for automated literature review
- Multi-source aggregation (IEEE Xplore, ScienceDirect)
- Personalized recommendation engine
JavaScript · Node.js · Python · OpenAlex API · LLM APIs · HTML/CSS
See CONTRIBUTING.md.
MIT — see LICENSE.