Скачать или смотреть Day 2: Fitting a Straight Line in Python – Optimal-Start Math Crash Course

Welcome to Day 2 of the Optimal-Start Math with Python Crash Course!

In this video, we take the next step beyond DeltaT and rate. Today we learn how to fit a simple straight line using two warm-up events. This introduces the core ideas behind regression: the slope (m) and intercept (b) that describe how many minutes it takes to warm up the building for any DeltaT.

This same math shows up inside real optimal-start logic, including how systems estimate “minutes needed” from setback to setpoint. We break it down step-by-step and build your first predictive formula using Python.

What You’ll Learn

How to compute slope (m) from two warm-up events
How to compute the intercept (b), also known as “dead time”
How to build the formula Minutes = m * DeltaT + b
How to predict warm-up time for any DeltaT
How to run the Day 2 assignment in Python

These concepts build the foundation for more advanced models we’ll explore later, including EMA learning, quadratic models, and the full PNNL approach.

Resources
hvac-optimal-start-math-playground repo day 2.

https://github.com/bbartling/hvac-opt...

Who This Video Helps

BAS technicians wanting to grow into analytics and optimization
HVAC engineers learning Python
Controls programmers practicing optimal-start math
Anyone interested in regression, EMA, and self-tuning HVAC algorithms

Assignment Covered

1. Compute slope m using two warm-up events
2. Compute intercept b
3. Predict warm-up time using Minutes = m * DeltaT + b

Like and subscribe if you want more walkthroughs for Day 3, Day 4, and all the advanced models later in the course.

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Hashtags
#hvac #hvacoptimization #buildingautomation #bas #hvaccontrols #mathematics #python #ai #selfstudy #engineering #niagara4 #optimization #smartbuildings #learningisfun