Navigating the energy transition landscape: summary findings from a dynamic systems view

I’ve been asked a few times now to provide an account of the energy transition modelling featured on Beyond this Brief Anomaly over the past year or so, that goes beyond the very brief article for The Conversation in May, but that is more accessible than the detailed documentation provided in earlier posts here, here and here. The article presented here is intended to fill that gap. It’s based on the presentation I gave in July at a University of Melbourne Carlton Connect Initiative event on energy transitions, discussed in the introduction to this earlier post. The presentation abstract will serve for orientation:

Energy transition discourse in both the public and academic spheres can be characterised by strong and often fixed views about the prospects for particular pathways. Given the unprecedented scale and complexity of the transition task facing humanity, greater circumspection may help ensure collective efforts are effective. While significant attention has been given to the question of how to satisfy future energy demand with renewable sources, dynamic effects during the transition period have received far less attention. Net energy considerations have particular relevance here. Exploratory modelling indicates that such considerations are relevant for more comprehensive feasibility assessment of renewable energy transition pathways. Moreover, this suggests there may be value in asking broader questions about how to ensure energy transition learning and praxis is sufficiently ‘fit for purpose’. Continue reading

The energy costs of energy transition: model refinements and further learning

In this post I’ll discuss further developments relating to the energy transition modelling exercise covered in detail in the previous two posts (here and here). Consistent with Beyond this Brief Anomaly‘s inquiry ethos, I view the exercise as effectively open-ended. The findings at any point in time can be considered provisional and subject to refinement or revision as learning unfolds, as new ways for making sense of the modeled situation come to light, and as the ways in which the situation itself is understood change. This particular modelling effort should not be treated as the “last word” on the subject. Indeed, the best outcome from the work would be an increased public concern for the dynamics of energy transition — leading to new initiatives that explore the implications independently, going beyond what is possible with this relatively modest foray.

Nonetheless, the findings to date from this work demand close consideration from anyone seriously committed to renewable energy transition. The essential insight is this: in the rapid build-out required for a major transition in primary energy sources, effective aggregate energy return on investment (EROI) for a replacement source’s total stock of generators is lower than for an individual generator considered in isolation. The overall EROI ramps up from zero at the commencement of the transition, only reaching the nominal value for an individual generator over its full life-cycle when the transition is effectively complete i.e. when the generator stock reaches a steady state. All of the other key findings flow from this fundamental feature of any rapid transition in primary energy source. If a replacement energy source has lower nominal EROI than incumbent sources, then this becomes a critically important feasibility consideration.

The specific model developments introduced here are summarised as follows (I’ll discuss each in more detail below):

  1. The conversion of power outputs to energy service outputs in the form of heat and work for each supply source has been thoroughly overhauled, resulting in a far more refined implementation of this feature of the model.
  2. Conversion of self-power demand to emplacement and operating & maintenance (O&M) energy service demand in the form of heat and work has also been modified for each supply source.
  3. The maximum autonomy period that determines the amount of energy storage for wind and PV electricity can now be increased gradually as the intermittent supply penetration increases as a proportion of total electricity supply.
  4. For the default parameter set (now called the “reference scenario”, previously “standard run”), the maximum autonomy periods for wind and PV supply are arbitrarily reduced to 48 and 72 hours respectively, simply for the sake of heading off any knee-jerk response along the lines that “the amount of storage assumed to be necessary is unrealistic, therefore the entire model is suspect”.
  5. Detailed calculation is now included for levelised capital cost and O&M cost  for wind and PV supply plant, and levelised capital cost for batteries (making the discussion of this in the previous post now redundant).

The updated version of the model to which this post relates is available here.

The full parameter set for the updated model’s “reference scenario” (equivalent to the “standard run” in previous posts) is available as a PDF here. Continue reading

EROI and the limits of conventional feasibility assessment—Part 3: Intermittency & seasonal variation

In the previous post in this sequence, I developed the concept of power return on investment as a complementary indicator to energy return on investment (EROI) for assessing the viability of wind and solar PV as alternatives to thermal electricity generation. I used as my departure point for this an article in which Ioannis Kessides and David Wade introduce a dynamic approach to EROI analysis.[1] Specifically, I drew on an illustrative example that they present, based on IEA data for coal-fired thermal and wind electricity generation in Japan, showing how the time required for coal and wind installations to provide sufficient energy to emplace additional generating capacity equal to their own can differ by an order of magnitude even where the EROI for coal and wind is identical. Given that the data on which this example was based was from prior to 2002, both the doubling time in Kessides & Wade’s example and the power return on investment in the extended analysis would likely be improved if up-to-date figures for emplacement energy and capacity factor were substituted for those from the IEA study. Unfortunately, this goes only a limited way to mitigating the central issue in terms of “real world” considerations. Continue reading

EROI and the limits of conventional feasibility assessment—Part 2: Stocks, flows and power return on investment

Update, 24 July 2015: while doing some background work for a forthcoming post that draws on data presented here, I reconsidered the best basis to use for the PV comparison. The post has now been revised to reflect my updated thinking, specifically using a higher EROI for PV of 4.17:1, rather than the original of 2.45:1, by considering only a subset of Prieto and Hall’s energy costs. In the course of making this change, I also discovered an error in the original calculation, in the ratio of emplacement energy to operating & maintenance energy for PV (relatively minor impact only, from 0.59 to 0.55). This is also corrected here.


An important principle to bear in mind for inquiring into the ways that energy-related considerations influence human societies is that, by and large, economies are dependent for their present functioning not on the total stocks of energy sources they might have at their disposal, but on the current rate at which energy sources are supplied and utilised. This is a key distinction in understanding the phenomenon of peak oil. “Peak oil” for a given field or territory is taken to have occurred at the point in time for which the production rate for petroleum—appropriately defined, i.e. by grade or composition—reaches a maximum, and thereafter declines. But at such a time, as much as half of the ultimate resource may still be available. Peak oil doesn’t imply that we’re on the brink of “running out of oil”. What it means is that the production rate is at the highest level that will ever be achieved. It is the change in rate that is central for understanding the implications of the phenomenon for future social prospects, as a declining aggregate oil production rate (i.e. where a shortfall from one region cannot be compensated by increased production from others) implies greatly foreshortened prospects for further growth in the non-energy related economic activity enabled by that production, and in fact very likely implies commensurate economic contraction. The same principle applies to any resource that is ultimately stock-limited, but for which it is the supply rate upon which the present nature of the economic activity enabled by that resource depends. Continue reading

EROI and the limits of conventional feasibility assessment—Part 1: The technical potential for renewables

A fundamental requirement that any energy supply system must satisfy for economic viability is a sufficiently high energy return on energy investment (EROI) for manufacturing, installing, operating and maintaining the system over its operating life. The question of what constitutes a sufficient return depends on the nature of the economy and society that the energy supply system is intended to support—while an EROI <1 implies a net energy sink, an EROI >1 does not automatically entail viability. Consider the limiting case in which net energy supply is zero, i.e. EROI =1. This would entail an economy consisting entirely of an energy supply sector that supported itself, but allowed for no economic activity beyond this. It’s certainly possible to imagine a functional economy along such lines, but it implies that every person living in such a society must dedicate their life to and focus all of their attention and effort on providing for the subsistence energy needs of their economic system. Such an economic system would serve no purpose beyond its own perpetuation; citizens of such a society might very well consider their lives to constitute a form of slavery to their economy. Continue reading

A rough guide to visualising energy density

In concluding the previous post, I pointed out the problem with comparing stock-based energy sources—such as fossil fuels and uranium—with flow-based sources—such as wind and solar radiation—on the basis of their associated energy densities. [Update: strictly speaking, we’re dealing here with the distinction between energy density and power density. While energy density is a straightforward and very useful way to characterise and compare energy storage media such as fuels and batteries, the infrastructure for producing fuels and electricity is often better characterised in terms of power density—the rate of energy transformation or supply per spatial unit. This reflects the more immediate dependence of a particular set of socio-economic arrangements, if it’s to be maintained, on its associated energy supply rates, rather than its energy reserves. For now though, I’ll continue the inquiry based on the concept of energy density, as it is arguably the more accessible concept given the nature of our direct experience with fuels—including our own fuels, the food that we eat!] Just to recap on the previous post, establishing a characteristic energy density for a given source requires that we first nominate an appropriate spatial dimension associated with that source. This is straightforward for stock-based sources involving a given quantity of material such as coal, oil or gas, and we can readily compare the energy densities between different sources. The characteristic spatial dimension is the volume occupied by the source material. Continue reading

Energy density and the prospects for renewably-powered societies

In the post prior to last week’s, I looked in some detail at the energy densities associated with each of the conventional fossil fuels that together account for over 80 percent of global primary energy supply. As I pointed out, the highly concentrated nature of these energy sources is a fundamental enabling factor in relation to the forms of social and economic organisation that have evolved over the course of the industrial age. The norms, expectations habits and tendencies with which we live together today—and that for most of us, most of the time, remain largely below our thresholds of awareness—are intertwined in various ways with the characteristics of our energy sources. Different energy sources necessarily entail differences in these characteristics. In transitioning between energy source regimes, if key characteristics associated with an emerging regime differ sufficiently from those with which our major techno-economic infrastructure and socio-cultural institutions have developed, then at some point the infrastructure and institutions will themselves need to change for the process of transition to proceed. When such transition points are reached, the connections between energy resources and cultural expectations can no longer remain submerged from view: we’re required to confront the changing situation, and in many cases, we too must undergo our own transformations, individually and collectively. Continue reading