Explaining  Negative Electricity Prices 

Posted by

0

When my colleagues and I developed the theory of real time electricity prices back in the dark ages (1982), we were amused to see that our equations allowed for the optimal price to be negative. Power companies would pay consumers to use more electricity! At the time, we thought it was a paradoxical case that was unlikely in practice, except possibly in the middle of the night in systems with lots of nuclear units.

Fast forward 30 years, and negative prices are a regular occurrence in real systems, including in Texas and California. And now they are even happing in the middle of the day. But there is still a puzzle: why don’t generators stop generating the moment the price goes negative?

Several blog posts from Berkeley’s great Energy Institute, and my response to one of them, show that real power systems can have a lot of unanticipated phenomena. Take together, these probably explain these apparently strange behaviors.

Source: Is Solar Really the Reason for Negative Electricity Prices? – Energy Institute Blog.   and from Catherine Wolfram, Is the Duck Sinking?
Continue reading →

Photovoltaics in Mission Bay neighborhood = 30% wasted

Posted by

0

TL;DR In Southern California should put PV on houses and buildings that are far from the coast, because coastal areas are cloudy much of the summer. But the actual pattern is the opposite. I estimate a 30% magnitude of loss. Even my employer, UCSD, has engaged in this foolishness in order to appear trendy.

The bumpiness of this graph shows the effects of coastal weather in August.

Continue reading →

Science policy fellowships @ UCSD

Posted by

0

For STEM doctoral students at UCSD who have policy interests but are not in social science fields. I have advised several students in this program, and it has been useful for all of them.

Drawing applicants from UC San Diego’s STEM related programs, each year the School of Global Policy and Strategy (GPS) selects three doctoral students from across campus and pairs them with a GPS faculty advisor to explore the policy implications of their dissertation research.

Continue reading →

When Am I Committed to Collision? A case of art going toward science, but only very slowly.

Posted by

0

According to the author, naval ship handling still relies heavily on craft expertise. His article writes down some formulas and procedures to reduce collision risk.  Source: When Am I Committed to Collision? | U.S. Naval Institute  My own reaction is in a brief comment at the end of the article.

Here is another article in the same issue of US Naval Institute Proceedings that does a great job of explaining how collisions can happen, and why the captain of a USN ship is always responsible, and never completely safe.

This is the burden of command. A captain puts the lives of several hundred sailors into the hands of a young officer, typically 25 years old and typically green. So what does a captain count on to prevent disaster? The captain has “standing orders.” These are the rules in his or her ship that everyone (especially the OOD) lives by. …”

Showing linear regression coefficients

Posted by

2

I have just finished my Big Data course for 2017, and noted some concepts that I want to teach better next year. One of them is how to interpret and use the coefficient estimates from linear regression. All economists are familiar with dense tables of coefficients and standard errors, but they require experience to read, and are not at all intuitive. Here is a more intuitive and useful way to display the same information. The blue dots show the coefficient estimates, while the lines show +/- 2 standard errors on the coefficients. It’s easy to see that the first two coefficients are “statistically significant at the 5% level”, the third one is not, and so on. More important, the figure gives a clear view

Coef plot from strengejacke Bof the relative importance of different variables in determining the final outcomes.

The heavy lifting for this plot is done by the function sjp.lm from the sjPlot library. The main argument linreg is the standard results of a linear regression model, which is a complex list with all kinds of information buried in it.  Continue reading →

Can Elon Musk Get SolarCity’s Gigafactory Back On Track?

Posted by

Elon Musk clearly has a blind spot about manufacturing. Building a giant factory for the first use of a new process does not work, and theoretically it cannot work. Even if it did work, it would be non-competitive. Once a factory is built and machines installed, subsequent new discoveries/knowledge cannot be incorporated, except at the margins.

To reach the 100-megawatt goal, sources indicate that the pilot production line in Fremont would eventually need to yield between 800 to 1,000 high-efficiency Whitney panels per day. But the team was not able to automate the process consistently enough to produce more than dozens of Whitney panels per day, according to people familiar with the matter. Most of the production resulted in “scrap,” they say. “The big problem was simply that they couldn’t scale up the technology to the point where you could run it in a factory,” a source familiar with the development explains.

Source: Can Elon Musk Get SolarCity’s Gigafactory Back On Track?

Continue reading →