Grid

I will do a little experiment and let ChatGPT also write this blog post. I have made minor edits to ensure it aligns with the screenshots, but this is not me! A few essential items before we dive in: I am using GPT4 with Data Analysis through a paid account I work in the energy space, so I knew basically what I was trying to do with the prompts The Consumers website could have done this analysis in precisely 3 clicks through their portal, so I saved little time Yes, we use a ton of electricity! We have a large geothermal system, 22kw solar array, and 26kw of batteries in the basement. We also have 2 Electric Vehicles and a manufacutring shop on the land. ChatGPT Shortcomings: There is no confidence rating here. You ask the model; it gives answers. Are those answers correct? Sometimes. There is a fallacy that you upload and ask away. In another exercise, I needed to go back and validate the PDF breakout, and the table read needed to be corrected. Verify everything. For a site-by-site analysis, this works great, but scaling this would require API integration. Back to my first point here, you would trust that automation wholeheartedly. As technology advances, the ability to quickly ingest and distil complex tariff documents will be a net positive to the energy industry. We are close, but not there just yet. Steps I used to complete this exercise: I went to GreenButton Connect for Consumers and downloaded my interval and billing data. I tried using some lower-level interval data from my parallel metering, but it was too small of an interval to process correctly. Downloaded the latest tariff book for all Consumers Energy rates. Logged into ChatGPT, selected my GPT4 analysis mode and provided the prompt - How does my utility bill compare to other people in Michigan? before starting to have it evaluate the usage against the tariff specifically. Reviewed the Python code and processing You can see the entire chat minus the actual code here: ChatGPT Chat Prompts ...

In our household, energy is more than just a utility; it’s a way of life. We’ve gone to great lengths to optimize our home, employing a symphony of solar panels, batteries, geothermal systems, and even energy monitoring to keep things in check. But, as they say, the devil is in the details, and I’m on a mission to uncover the hidden secrets that conventional energy monitoring won’t reveal. I often remind my team that energy is a force that doesn’t just vanish into thin air. Whether we’re monitoring temperatures at our EV chargers to predict potential faults or pondering the idea of dissipating excess energy into a vault of oil to tame its fiery temperament, we understand that energy has to go somewhere. ...

I am fortunate to have exposure to work on grid policy and implementation in both the US and European Union. The duality of those two worlds colliding helps look for the best approaches in both spheres. I wanted to talk about the most significant differences for those also looking to understand the differences. It is safe to say that both the US and Europe recognise the critical importance of grid security in maintaining a stable and reliable energy supply. As you compare the two governing bodies, the biggest takeaway is how basic KISS security can be, regardless of the policy framework. One area I do see more considerable differences is in market and program design. The US programs allow for more manual intervention and temporal windows, while the EU leans heavily into automation for quicker network response. You see more technical controls around that. ...

The current landscape of security approaches within Utility and ISO Programs is reminiscent of the early DITSCAP, DIACAP, and Rainbow Series progression of the Department of Defense world from the 80s and 90s. Given the ongoing Russia-Ukrain war and current geopolitical events, the urgency to bolster grid security and protect critical infrastructure in the US cannot be understated. Ageing power distribution systems are vulnerable to cyberattacks that can potentially jeopardise national security and bring the nation to a halt. ...

When you learn new languages, you can often find connections in words and ideas. Sometimes it’s wholesale incorporation of a word into the zeitgeist. Dunkelflaute is one I see more and more used in the energy world. “A Dark Lull” is the exact translation, but it intends to describe what happens when the sun isn’t shining, or the wind is blowing. The German language is beautiful; I don’t care what others say, but it is also incredibly literal. It is less flowery in its descriptors and often combines disparate words to create anew. ...