Decision Intelligence Lab
  • Home
  • Constante bio
  • Publications
  • Research
ESC

Searching...

No results found

↑↓ Navigate ↵ Select
Powered by Hugo Blox
  • Research
  • Courses
    • Hugo Blox
      • Getting Started
      • Guide
        • Project Structure
        • Configuration
        • Formatting
          • Embed Media
          • Buttons
          • Callouts
          • Cards
          • Spoilers
          • Steps
      • Reference
        • Customization
        • Internationalization (i18n)
  • Publications
    • A Quadratically-Constrained Convex Approximation for the AC Optimal Power Flow
    • AC-network-informed DC optimal power flow for electricity markets
    • Physics-informed neural networks with hard linear equality constraints
    • Diagnosing infeasible optimization problems using large language models
    • Daily scheduling of generating units with natural-gas market constraints
    • An effective hybrid decomposition approach to solve the network-constrained stochastic unit commitment problem in large-scale power systems
    • Distributed manufacturing for electrified chemical processes in a microgrid
    • Stochastic Unit Commitment: Model Reduction via Learning
    • Security-constrained unit commitment: A decomposition approach embodying Kron reduction
    • Stochastic scheduling of generating units with weekly energy storage: A hybrid decomposition approach
    • Solving certain complementarity problems in power markets via convex programming
    • AC Network-Constrained Unit Commitment via Relaxation and Decomposition
    • Stealthy monitoring-control attacks to disrupt power system operations
    • AC network-constrained unit commitment via conic relaxation and convex programming
    • Sensitivity-based Vulnerability Assessment of State Estimation
    • Sensitivity-based Vulnerability Assessment of State Estimation
    • Operations and Long-Term Expansion Planning of Natural-Gas and Power Systems: A Market Perspective
    • Conservation voltage reduction of networked microgrids
    • Data-Driven Probabilistic Power Flow Analysis for a Distribution System With Renewable Energy Sources Using Monte Carlo Simulation
  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
  • Slides
    • Example Talk: Recent Work
  • Constante bio
  • Blog
  • Recent & Upcoming Talks

Physics-informed neural networks with hard linear equality constraints

Oct 1, 2024·
Hao Chen
,
Gonzalo E. Constante-Flores
,
Can Li
· 0 min read
DOI
Type
Journal article
Publication
Computers & Chemical Engineering
publications
Last updated on Oct 1, 2024
Authors
Hao Chen
Authors
Gonzalo E. Constante-Flores
Authors
Can Li
← AC-network-informed DC optimal power flow for electricity markets Jan 1, 2025
Diagnosing infeasible optimization problems using large language models Aug 1, 2024 →

© 2026 Decision Intelligence Lab. This work is licensed under CC BY NC ND 4.0

Made with Hugo Blox — Open Source. Create your site →