Newton-Raphson Power Flow
Understand the mismatch equations, Jacobian structure, iteration logic, convergence, and the checks behind a credible power-flow result.
Five-part video collection
Power Systems Readiness on YouTube
Start with the topic you need or follow the sequence from power flow through operational decision-making.
Five readiness topics
Each briefing introduces the engineering idea, shows where errors enter, and identifies the checks needed before the result is accepted.
Per-Unit System
Use coherent bases, transformer relationships, and base conversion to simplify networks without losing physical meaning.
Symmetrical Components
Interpret zero-, positive-, and negative-sequence quantities and connect the transformation to physical network behavior.
Fault Analysis
Build sequence networks, apply the physical fault boundary, reconstruct phase quantities, and verify the result independently.
Economic Dispatch and Unit Commitment
Separate continuous dispatch from discrete commitment decisions and understand lambda, operating constraints, and system cost.
What the Readiness Kits add
Diagnose
Find the real gap
Begin with a diagnostic that separates familiarity with terminology from the ability to apply the method independently.
Practice
Work beyond the example
Use challenges, debugging cases, and transfer tasks that require decisions rather than imitation of a worked solution.
Verify
Defend the result
Use checks, oral-defense prompts, evidence tracking, and guided coaching to make reasoning visible.
Fault analysis in greater depth
MRK-004 is the first topic supported by two public engineering articles. One develops the analytical foundation. The other examines why large, sensitive data-center loads raise the standard for validated grid fault studies.
Foundation
The Formula Was Right. The Fault Study Was Wrong.
Why power-system fault analysis begins with the network, its grounding paths, and its physical boundaries.
Large-load application
Data Center Growth Raises the Standard for Grid Fault Studies
Why precise models and validated protection assumptions matter as large AI data centers connect to the grid.