Introducing 4PACE: I built an open-source, YAML-driven power grid simulator in Python ⚡

daniel.sakdinun — Tue, 05 May 2026 11:28:55 +0000

Hi DEV community! 👋 I'm Dan, a recent Electrical Engineering graduate. While looking for my first full-time role, I decided to channel my energy into building something that solves a real problem in my field.

Today, I’m excited to share the initial release (v0.1.0a1) of 4PACE (Four-Quadrant Power Analysis & Computational Engine). It’s an open-source, Python-based power system analysis tool.

The Problem with Existing Tools 🤔

In power engineering, we often deal with complex simulations. Many existing tools are either expensive commercial black-boxes or require writing a massive amount of boilerplate code just to set up a simple grid topology.

I wanted an engine where users could define the grid simply and transparently, while the core handles the heavy non-linear physics under the hood.

Enter 4PACE 🚀

4PACE shares a space with great libraries like PyPSA and pandapower, but it brings a few distinct architectural choices to the table:

1. Declarative YAML Topology
Instead of writing Python code to build your network node-by-node, you define the entire grid in a clean YAML file. Once configured, you simply call the analytical functions.

2. Taming the Non-Convex ACOPF
AC Optimal Power Flow (ACOPF) is notoriously non-convex and hard to solve. 4PACE tackles this by applying Convex Relaxation into Cone Programming (SOCP/SDP) using CVXPY. It then uses a Newton-Raphson solver to close the relaxation gap, ensuring the final dispatch is 100% physically rigorous.

3. Built for the Modern Grid
With the rise of renewable energy, 4PACE utilizes Multi-Period Optimal Power Flow (MPOPF) to accurately model the time-series behavior of Inverter-Based Resources (IBR) like Solar and Battery Energy Storage Systems.

Current Features (v0.1.0a1) ⚡

Capacity Expansion Planning (CEP)
Security-Constrained OPF (SCOPF) with Validate_N1()
Fault Analysis
Transient Stability equipped with standard IEEE dynamic control models (SEXS, TGOV1, PSS1A, CSVGN1, STATCOM1, and TCSC1).

The Architecture 🏗️

I prioritized minimal dependencies to keep the library lightweight and easy to audit. The core is an Object-Oriented Differential Algebraic Equation (DAE) engine built on top of NumPy, SciPy, CVXPY, and NetworkX.

I would love your feedback! ❤️

Since this is my very first major open-source project, I would absolutely love any feedback from the experienced developers here. Whether it's about the Pythonic structure, the mathematical implementation, or just general advice!

📦 PyPI: https://pypi.org/project/4pace/
💻 GitHub: https://github.com/daniel-sakdinun/4PACE
📄 Documentation: https://4pace.readthedocs.io/