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⚡ "Predicting Energy Markets"

Carbotnic

Photo by Joshua Sortino / Unsplash

Table of Contents

Host: James McWalter
Guest: Lauren Kuntz | CEO and Co-Founder | Gaiascope
Category: ⚡ Renewable Energy | Energy Forecasting

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Podcast’s Essential Bites:

[0:12] “We're really focused on trying to help the assets that we need for a carbon free grid. So things like storage, renewables, demand response, maximize their returns, so that those projects that are more financeable in the future [...] and we can help accelerate our transition to a carbon free grid.”

[2:05] “The early product […] [was] a SaaS company and we're going to sell price forecasts on the electric grid. The idea being if you know what price expectations are, you immediately know how to make decisions. […] Really early on, we learned we had to pivot away from that, because almost everybody we spoke to was like, if you're amazing at forecasting prices, why don't you go trade? There was a huge skepticism.”

[2:42] “We pivoted kind of within that first three months of formation, just from trying to be a software platform to actually running a very small trading platform. So we spent about two and a half years then trading ourselves, building up our models, having an amazing feedback loop […] and now are really launching a product that's focused on giving bid decisions and optimization around dispatch to decarbonize assets on the grid. So kind of taking that price forecasting a step further for them as well [and say], this is how you should trade. This is how you should dispatch your asset to maximize your returns.”

[3:54] “I think today, so many renewables have been under PPAs (Power Purchase Agreements), for so long, that they haven't had to worry about trading and wholesale markets. They've basically had zero exposure to this. So they haven't had to build out trading teams in house like. […] And now you're seeing the PPA value start to fall. So it's not quite as valuable to do as it was before. You're starting to see assets that were on PPAs, now that contract has ended and they're not exposed to this wholesale market risk. And they […] don't know, necessarily how [to] manage that risk. […] So we really are trying to come in and help with that specific problem.”

[6:48] “If you have no idea what tomorrow is going to look like, [it’s difficult to] make decisions around what plants are going to be turning on at what time. And will I have enough generation from those plants? And there are some plants that take a very long time to spin up and be ready to produce power. And probably if you have no idea what's gonna happen, […] [you’ll be] ready all the time to produce power.

[7:38] “Because we have different return expectations than say, the wind farm, or the coal plant, we’re able to bid more aggressively and get the market to look more accurate than they otherwise would. They probably are going to be more conservative. […] So we're able to really help the market operate more efficiently through our trading. And efficiency also is really strongly correlated with lower carbon.

[17:18] “The one area that still really frustrates me […] is around demand response. I feel like the way right now demand response markets are set up as you get rewarded for peak shaving. So at times, when there's a lot of load on the grid, if you are able to reduce your load, you can get paid for this. But you can't get paid for filling troughs. So if you have too much renewable generation, and prices are negative, most demand rockets are set up where you can't take advantage of that. So you're really limiting how that resource can interact and what benefit they can provide from the grid, because you haven't incentivized them properly.”

[26:24] “There's a good amount of data on the grid collected that we have access to as a market participant, which has been phenomenal. […] My biggest pain is […] I wish this data was cleaner and less of a pain to work with. Name matching between datasets is just so hard. There's no consistency. It'll even sporadically change over time.”

Rating: ⚡⚡⚡

🎙️ Full Episode: Apple | Spotify | Google
🕰️ 38 min | 🗓️ 06/07/2022
✅ Time saved: 36 min

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