We all know this accounts a fake. It’s relentlessly anti renewables. It’s misinformation. But who is it? Read on. 🧵

https://twitter.com/JohnLeePettim13/status/1622810848824631296

Let’s look at the name. John Lee Pettimore. Who’s he? A real person? Nope. A fictitious character in a song. Not just any song, a song about copper!

Short thread 🧵 on electric motorcycles in Indonesia. 👇 Tl;dr, the market is about to explode and my prediction is that there will some serious disruption. 1/n First terminology. I’m going to use the term “electric scooters” in this thread. This is specifically referring to the city commuter market segment. Step through motorbikes that have 50-100 km of range and a top speed of 80 km/h. In Indonesia these are called “motor listrik”. 2/n

There is a lot of discussion on energy Twitter about how 100% RE manages dunkelflaute, or periods with low wind and sun resource. Turns out AEMO modelled one in the 2022 ISP. Short thread 👇 My answer has always been that we will use clean liquid fuels like H2 or NH3. This graphic gave me the opportunity to undertake an order-of-magnitude calculation of what that might look like for this event in the NEM.

/2

Thread on H2 as “storage” coming up. Declaration. Initial thoughts and the numbers definitely need firming up.

There has been discussion in Twitter that H2 isn’t suitable as a storage medium for VRE because the round trip efficiency isn’t high enough. 1/n This is apparently based on the logic that by the time you make the H2 with RE, store it, transport it and turn it back to electricity the round trip efficiency is too low.

I’ll calling this out as BS. I don’t care what the efficiency is, I care how much the product costs. 2/n

@dmichie66 @ThatcherUlrich @GrantChalmers @VibrantCE OK, here goes. One of the great things about science is that if you have the right hypothesis, or more accurately, the right framework for thinking about the problem, then as the future reveals itself, the data points that it delivers line up with your framework. @dmichie66 @ThatcherUlrich @GrantChalmers @VibrantCE This is how climate models (as an example), work. Past data is used to build a model which is judged by how well it backcasts (ie predicts known data), then, as the future reveals itself, you see how well it has predicted the observed data.

@dmichie66 @simonahac OK, I've watched the whole thing and I've been following Jesse on twitter for a while, so I feel I understand where he is heading. Let's start with a couple of framing remarks.

1. He makes a point about "mental models". Here I am in complete agreement with him. 1/n @dmichie66 @simonahac People's mental models (ie, their framework to tackle a problem) are significantly influenced by their education/training/upbringing. My own early career in biotech, particularly genome sequencing influences how I think about problems in the energy space. 2/n

Tweet thread with my thoughts on 100% renewable vs 100% zero carbon modeling. 1. All models are wrong. Some are useful (Box).

@BieglerTom @factchekka @mcannonbrookes @simonahac Tom! I'm so glad you asked. To lay it out for you will be a bit of a thread, so please bear with me. Reference for numbers are Lazard 12.0 and the new study by ITP on dispatchable renewables by Keith Lovegrove available on the ARENA website. 1/n @BieglerTom @factchekka @mcannonbrookes @simonahac Old power generation system was baseload, intermediates and peakers. Intermediates provided baseload backup when required & met increased demand. Peakers only came into play at times of extremely high demand. Peakers has low capital costs and high fuel costs. 2/n