Online Learning Module

Lesson 1: PV Data Basics

12:43

Learn how inverter telemetry is structured, common issues (gaps, outliers), and how to prepare it for analysis.

Learning objectives

Understand PV telemetry fields and sampling intervals.
Identify common data quality issues and quick fixes.
Prepare a clean dataset for time-series analysis.

Tip: pair this with PV Monitoring with Python notebooks.

Instructor

Elena Rossi

Climate Analytics

00:02
Welcome! In this lesson we’ll look at how inverter data is structured…
02:18
Here are the most common fields: timestamp, pac, e_total, temp…
05:40
To handle gaps, we first resample to a fixed interval and mark missing values…
10:12
Outliers often appear during sunrise/sunset. Let’s cap by quantiles as a quick win…

Use F to toggle full-screen, J/L to seek ±10s.

Downloads

References

Hana

2h ago

What’s a good baseline for daily yield normalization?

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Quick Check · 3 questions

Score ≥ 70% to mark this lesson as complete.

Your Notes

[03:12]

“Resample to 1-min, forward fill, then cap outliers at P95.”

[08:40]

“Sunrise/sunset artifacts — handle separately.”

Bookmarks

00:45 · “Telemetry fields”

05:39 · “Resampling”

10:15 · “Outliers”

Course progress40%

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Syllabus

1. PV Data Basics

2. Cleaning & Resampling

3. Dashboards 101

4. Optimization Basics

Certificate

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