New Course: Software for In Front of the Meter Battery Systems

According to the U.S. Energy Information Administration, developers plan to add 24 GW of utility-scale battery storage to the grid in 2026 – on top of the record 15 GW added in 2025 and more than 40 GW over the last five years. The software that runs these systems – the layer that actually decides when batteries charge, when they discharge, and how they bid into energy markets – is where the talent gap is opening up fastest.

That’s why we’re excited to share that Peter Gruenbaum’s new course, Software for In Front of the Meter Battery Systems, is now live on HeatSpring.

What “In Front of the Meter” Actually Means

Let’s talk about the distinction that shapes everything in this course. In front of the meter (IFTM) systems locate batteries on the grid side of the electricity meter – typically near solar or wind farms. Because they’re selling directly into energy markets, the software that runs them is fundamentally different from behind-the-meter systems designed to manage a single facility’s load.

IFTM batteries make money by buying low and selling high – charging during low-price periods, discharging when prices peak. To do that at scale, you need an energy management system (EMS) that gathers market data, generates optimized bids, and dispatches the battery accordingly. Building that kind of system is exactly what this course teaches.

What You’ll Build

In this hands-on course, you’ll build a simulated energy management system from scratch – piece by piece – using AI to generate Python code and then writing unit tests to verify that each component works. The four pieces you’ll construct:

• Market forecaster — predicts energy price windows
• Battery simulator — models charge/discharge behavior
• Bid optimizer — generates optimized offers for the market
• Market simulator — mimics how real energy markets accept or reject bids

Then you put them all together. By the end, you have a simple working simulation of a complete IFTM battery software system.

You don’t need to know Python going in, but you do need some coding experience. If you have zero experience with Python, it is recommended that you watch a short video on Python syntax because it’s different than C-style languages (like Java and C#).  Peter uses Google Colab, but learners are able to use whatever tools and AI that they like.

Why Take This Course

Grid-scale storage projects don’t run themselves. As more utility-scale solar and wind comes online, the systems that optimize when and how batteries charge and discharge are becoming as critical as the hardware itself. There’s a huge need for software engineers who understand how these complex systems work.

This course won’t make you a production EMS engineer overnight, but it gives you a working mental model of the system, hands-on experience building its components, and a foundation for going deeper.

The prerequisite is Peter’s free introductory course, Introduction to Software for Battery Systems, which covers the basics of both IFTM and behind-the-meter systems. If you haven’t taken it, start there.

Meet Your Instructor

Peter Gruenbaum brings an unusual background to this subject. He holds a PhD in applied physics from Stanford, spent years as a commercial software developer at Boeing, Microsoft, and a handful of startups, and has been writing control software for battery systems – both in front of and behind the meter – since 2019. He also teaches Software for Renewable Energy at the University of Washington.

That background shows up in how he structures the course: technically rigorous, but built around doing rather than just watching.

Enroll in Software for In Front of the Meter Battery Systems to get started!