Relevant to some recent discussion on this website, here is a new paper comparing the emissions estimates that you would get from different estimation methods. It is a topic close to my heart, so here are a few links/explainers on why you might care.
Second, a thread from yesterday with lots of branches showing why these questions are not just of academic interest. In short, policy and some markets want to know what happens to emissions if we add/remove X, but that it a harder question than it seems.
Finally, this related result we had in a paper last year showing that using marginal versus average emissions factors can sway your estimates of energy efficiency by a factor of 2 in either direction - that is a big difference!
Finally, this related result we had in a paper last year showing that using marginal versus average emissions factors can sway your estimates of energy efficiency by a factor of 2 in either direction - that is a big difference!
In which @BrianTarrojaPhD and I look at the value of controlled charging or vehicle-to-grid in a different way: How much less energy storage would you need and what is that worth?
Brian gave a good summary of the work overall in this thread (below), but I want to focus on just one part (where I think we did a clever thing): How should we estimate the value of smart charging or V2G?
To do this, people mostly look at current or future prices/costs of electricity/services to calculate the value of smart charging/V2G. They mostly find that it isn't worth much today (fair enough).
Ex: here's Elon downplaying the value of V2G: utilitydive.com/news/tesla-unv…
That is: it doesn't seem like we're seriously thinking about how to get the vaccination rate up and we ought to be trying out low-cost experiments like this to see what works.
Currently reviewing a paper for a French-language journal and I just learned that the French call a "pie chart" a "camembert". Now I want to know what pie charts are called in other languages so we can make a delicious chart of the results.
I made a chart of the responses so far. I can edit this, so corrections or additions are welcome.
Pie charts are generally bad, but I think a pie chart of names for pie charts is one good use. Here is another:
New technologies like solar + batteries are getting cheaper. And certainly lower cost drives greater adoption. But does adoption go up gradually or are there "tipping points" where new tech is suddenly preferred? We wanted to dig into this question with a microgrid case study.
This was all driven by some results in a previous microgrid paper, where a student noticed in sensitivity analysis that solar price declines didn't much affect how much solar to put in your microgrid until, suddenly, the model said to greatly increase solar. What's up with that?
Joining the professional class today basically requires that you continually make amazing close friends and then leave them forever (or they leave you). You have to do it again and again and it sucks every time.
Why don't we ever talk about this? It seems to be the #1 downside.
This is obviously a real "first world problem" type of complaint and I imagine most people who manage to get into the highly-educated professional group are happy with their choices (I am), but the inability to hold onto the amazing people that have changed your life is hard.
I've *only* lived in 6 places in my life, but can think of ten different really great friends I've made - friends that would be life-long super-close friends if we lived in the same place. But I left them for college or a job (or they left for one of these reasons).
If you are looking for a solid semi-academic read on how governments behave in a crisis, Essence of Decision has a lot to say about today's situation. It is about US and USSR actions in the Cuban Missile Crisis, and I'll describe a few lessons below. en.wikipedia.org/wiki/Essence_o…
The book shows that many of the actions taken by either side in the Cuban Missile Crisis (CMC) weren't really rational and attempts to explain them through other means: organizational behavior or political negotiation. This is because organizations don't "think" rationally.
A rational model of decision uses a "logic of consequences:" relating actions to outcomes and choosing actions that have the best outcomes. Organizations don't work like that - they have a "logic of appropriateness", responding to each situation in a way that seems "by the book".