February 1st

I’m now testing the variations made possible in the basic game by the tax and subsidy controls. Alas, there are some nasty problems. I raised the carbon tax to its maximum value and it generated $2.9 trillion in annual revenue. That money is distributed among five beneficiaries, one of which is subsidies for solar energy. The subsidies amount to $600 billion. This is not intrinsically crazy: the global economy spends about $15 trillion on energy each year. However, total annual spending on solar amounts to a mere $4 billion; the subsidy increases this by two orders of magnitude! That’s simply too big a shock for any normal simulation to handle without special provisions to address it. 

Obviously I need a relaxation algorithm that allows the system some time to respond. This is certainly realistic: if the world suddenly bestowed $600 billion on the solar industry, it simply would not be able to expand quickly enough to handle all that money. I already have a general-purpose relaxation algorithm in place that I use for a few factors. However, its use is tricky, because it can produce anomalies the history graphs.

There are two obvious places to apply the relaxation: at the taxation level and at the spending level. In the taxation level, the tax would not apply in full force; it would be ramped in over some period of time. This reasonably reflects the desire to give industry some time to respond to the tax. It also gives the entire system time to respond smoothly.

The other place to apply relaxation is on the spending side. This is also reasonable in that it takes into account the time it takes to build up manufacturing capacity. However, it suffers from an implementation problem: my algorithm for calculating energy supplies is already quite complex and I am wary of increasing its complexity.

Ergo, it seems best to apply the relaxation to the tax; I believe that I shall use a relaxation rate of 10%. This means that the relaxed value will change by, each year, only 10% of the difference between the actual value and the intended value. That means that it will take about 10 years to get within 90% of the final value. I’ll try that and see how it comes out.


Well, it worked, but required two further changes. First, I had to put a ceiling on growth rate of renewables: no more than doubling each year. That’s still a very aggressive growth rate, but it is necessary if solar is to show much of a dent in energy supply. Solar starts off with just one BgOge of energy production (Billion gallons Of gasoline equivalent), when the rest of the world is using about 4000 BgOges. Thus, solar would need a minimum of nine years just to come up to something significant even at the most aggressive growth rates. I am tempted to slow it down a bit, because there’s a second problem:

Sometimes solar and wind overshoot the mark and end up decreasing once. This then raises prices, causing nonrenewables to spike upward, which raises the price, which starts an oscillation. The oscillation is damped, but it still looks all wrong in the history graphs, so I put a floor underneath renewables: they can never decrease. That makes sense because renewables have no fuel costs: it’s all capital costs, so once the facility is built, you might as well run it at full output all the time.

Maybe I should drop the maximum growth rate to 1.8 or so…