Negative Feedback

Tag: model

  • No free energy: why EROEI matters

    This is a follow-up post on the previous one about energy in SA. After writing it, or more accurately after writing many of the same words in a very long Facebook battle recently, a few links were posted that claimed that EROEI doesn’t matter.

    The Wikipedia article on EROEI gives a pretty good summary. In short, you use energy to collect energy in the future. It has been argued that EROI doesn’t matter when you have a source of energy as bountiful as the sun.  Unfortunately, you actually have to build things like solar panels or windmills to capture the energy coming from the sun and convert it into something that we can use.

    I wrote a quick simulation in Python that shows why it does matter,
    and would like to paste some of the prettier results here for posterity.  The scenario I analysed works as follows:

    Imagine we live in a world where we are using 1 energy unit every month, and we expect to double that usage over the next 100 years in a linear fasion (this is already a little ambitious, as recent energy demand growth has been closer to an exponential).  Further, imagine we have the ability right now to produce 1.2 units of energy every month (20% more than we use), but we want to phase out the dirty old technology linearly over a period of 15 years.  Graphically the situation looks like this, for the next 20 years.

    So, let’s say we see problems ahead and therefore we use some fraction of the surplus energy every month (say 20%) to build new solar panels which will supply clean energy in the future.  For the purposes of this simulation, let’s use a productive lifetime for these panels of 20 years.  The EROEI is the ratio of the energy produced by the panel over its total lifetime to the original energy cost of the panel.  The next figure shows the results of our slightly unnatural situation for values near the balance:

    I’ve shown three values for EROEI for our theoretical solar panels, chosen so that they either fail to satisfy our energy demand, just manage to do so or do so exponentially well.  This illustrates just how important it is to invest in the correct technology, even if it is renewable. In our example, any EROEI less than 10.3 will result in us running out of energy, with no way to build ourselves out of it.  There is no Energy Bank where we can borrow a lot of energy to build the new things we need – the world doesn’t work that way.  The closest we have at the moment is the energy stored as fossil fuels, but that is also not an infinite resource.

    Another way of looking at EROEI is that it determines what fraction of the total energy activity of our society is dedicated to building replacement energy devices. In fact, the calculation is very simple, this fraction just the inverse of the EROEI (1/EROEI).  So when EROEI is 2, half of the energy economy is dedicated to building more energy devices.

    I post the source code for the simulation here in the interest of transparency. Note that these are fictional numbers in fictional units, but the simulation illustrates a point: there is something like a too-low return when it comes to building the new energy capacity that we will need to ween ourselves off fossil fuels.

    from __future__ import division
import matplotlib.pyplot as plt

# Simulation parameters
Nyears = 20
Nmonths = 12*Nyears

# Installed capacity
def installed(i):
    """ Linear decline in installed capacity down to zero"""
    endt = 15*12
    beginE = 1.2
    if i > endt:
        return 0
    else:
        return (endt - i)*(beginE)/endt

# Usage
def usage(i):
    """ linear increase of 0.1 unit per year of 1 unit/month """
    return i*1/100/12 + 1

# New energy stats
life = 20*12
buildfactor = 0.2

# For plotting
months = range(Nmonths)

def simulate(EROEI):

    # Initial energy
    E = 0

    # remember what we have built
    builds = []
    Eovertime = []
    for i in months:
        # add installed capacity
        E += installed(i)

        # add energy from built capacity
        for (b, Ecost) in builds:
            if i - b < life:
                E += Ecost*EROEI/life

        # subtract usage
        E -= usage(i)

        if E < 0:
            E = 0 # can't go into energy debt
        else:
            # spend a fixed fraction of reserves on building new capacity
            Ecost = buildfactor*E
            E -= Ecost
            builds.append((i, Ecost))

        # Save what we have after all that
        Eovertime.append(E)

    return Eovertime


timeaxis = [i/12 for i in months]

plt.plot(timeaxis, map(installed, months),
         timeaxis, map(usage, months))
plt.xlabel('Years in future')
plt.ylabel('Energy')
plt.legend(['Old energy installed capacity', 'Usage'], 'best')
plt.savefig('assumptions.png')
plt.figure()

ratios = [10.5, 10.305, 10.1]
for EROEI in ratios:
    plt.plot(timeaxis, simulate(EROEI), linewidth=2)

plt.ylim([0, 4])
plt.axvline(15, color='black')
plt.axhline(0, color='black')
plt.xlabel('Years in future')
plt.legend(ratios,  'best')
plt.ylabel('Energy stored')
plt.savefig('trajectories.png')
plt.show()

  • Impressions of superiority

    None of my compliments are as often or firmly rebuked as telling someone they have a natural ability for something.

    It is a quirk of our society that our sense of achievement is diminished by aptitude. We praise above all individuals who have overcome adversity in their achievement. Many view being told they have an aptitude or ability as tantamount to saying they didn’t have to overcome as much as other people would have.
    I am aware of my natural aptitudes for some activities. I had no particular difficulty learning to play the guitar and appear to understand music pretty well. My mathematical intuition is sound. I find it easy to learn new programming languages. I also have certain… challenges. I am easily distracted, I find medium-term planning difficult and my learning mode is often highly inefficient as I require a lot of background and overview before things start making sense. It has taken me a lot of time to figure out what the population average abilties in some of these areas are. I am by no means there, but I have learned enough to know which properties are high and which are low.
    The reason for listing my own abilities here is an attempt to defuse the knee-jerk reaction that I have perceived many times when you tell other people they have abilities above the norm. Many people will vehemently deny such abilities because they assume you are implying they didn’t have to work at it. It seems more acceptable to lament the lack of such abilities in others than to claim them for yourself. Many people don’t even do that – they will deny any particular variation in these abilities among people and instead end up lamenting their lack of application. I find this particularly objectionable, as the implication is often that the reason for failure is fundamentally a weak will.
    Here’s how a sample dialogue often plays out:
    Me: I have left off marking my papers again, and will have to put in a late night tonight.
    Them: Oh, I always get my marking out of the way first thing, then I feel much better.
    Me: I wish I had your well-developed work ethic and drive to completion
    Them: I don’t really have any particularly well-developed drive to completion – you can do this too.
    Me: I have tried and failed. Perhaps I am just weak-willed. But more likely I am more easily distracted than you are, or find this task more onerous than you do
    Them: How dare you imply that I don’t need to apply myself to get this stuff done!
    Unequal distribution of abilities sits poorly with the doctrine of equality (or at least equal opportunity). Even worse, it is very difficult to think of oneself as anything other than “normal”. When I lost 25 kg, I honestly did not seem any different to myself in the mirror. I can just remember seeing a lot more fat people around. When I started running, it never felt much different to run at a comfortable pace, even though that has changed radically as I trained. It’s an all-too easy trap to fall into as ones abilities develop: renormalisation. As you become more knowledgable, you just start to see more idiots. As you become less fit, you start wondering how all these people can be so active.
    This post is a bit of an impression rather than a well-though out argument. I wanted to get this down while I was still thinking about it after having discussed it at a party last night. There is much left out here: how much of these abilities are innate and how much are learned? How does practice feature into it and how well can we assess our own abilities, and what is the mechanism of self-control (in fact, what is being controlled). That will have to wait for later.

  • Understanding and intent

    When our ancestors were attacked by animals, they needed a way to predict their behaviour to come up with a counter strategy. An effective way of doing this is to think about the animal’s intent. “It’s trying to catch me, so if I run here, it will run there” etc. Of course, humans who were good at avoiding being eaten were selected and here we are with our brains wired for modelling intent. Unfortunately, many things to not have intent. Rocks, the weather, computers are all examples of things that are not “trying” to do anything. They exist and behave according to deterministic rules. I say unfortunately, because our over-active intent modelling comes up with intent anyay. Children easily think that simple inanimate things are out to get them (or ascribe some kind of autonomy to them), but grown-ups are often caught by the same trap when they try to understand the motivations of the computers or other complex devices that they use.

    I am in two minds about this phenomenon. On the one hand I think that it leads to sloppy thinking, where we are ascribing thought to something that has none, or leveraging a broken model to extrapolate far outside its realm of usefulness. On the other hand, it does make things easier to understand. I think my refusal to use intent when I was teaching programming is one of the reasons my students didn’t understand what I was saying. How many times have you heard things like “So, the rock wants to fall, because it’s being pulled by gravity, but there’s this thing in the way, so it has to go around it” (perhaps only if you listen to the Naked Scientist or are an engineering educator). This is clearly wrong in the particulars: The rock has no intent, it doesn’t “know” anything about what’s in the way — it is experiencing an acceleration proportional to the resultant force acting on it, that’s about as far as it goes — but it is right in allowing someone to understand what will happen.
    So the riddle is this: how do I leverage this mode of thinking in myself and others to increase understanding or make explanations easier but avoid coming up with a new religion to explain the intent of rocks?