What is the potential for renewable energy?

In the most recent posts last year, I looked in some detail at what the energy costs of energy supply imply for global-scale transition from fossil fuels to (mostly) renewable energy (RE) sources. The modelling presented there highlighted the importance of taking a dynamic view of transition – rather than just looking at the start and end states. If we’re serious about identifying feasible transition pathways, this type of approach has an important role to play. It’s reassuring to see that more significant effort is starting to be made in this area.

One reason this has been slow to gain traction is the idea that renewable energy sources are so abundant as to be without practical limits. It’s a popular and compelling story, but unfortunately, also one that obscures as much as it reveals. Here, I’ll explain why, and set out the detailed case for why we are much better served by thinking in terms of the practically realisable potential for renewable energy, rather than the raw physical flows. At the heart of this is a basic insight, expressed in a simple aphorism: ‘each joule of energy is not equal’. 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

An integrated view of energy transition: what can we learn?

In this post I take a detailed look at the simulation results for the energy transition model introduced in the previous post, when it is run with the default parameter values—what I referred to last time as the “standard run”.

Before getting started though, this is a good place to reiterate the motivation for undertaking this work. I’m prompted here by a post on John Quiggin’s blog that he provided a link to as a comment on the previous post. The post is a 300 word dismissal of the relevance of energy return on investment in assessing PV electricity supply performance.  It was—I assume inadvertently—a timely demonstration of the central point I was making: to have a productive conversation about these issues, we need to take a comprehensive, integrated view. But looking beyond the technical superficiality of John’s argument, he also made the misleading inference that a concern with the energetics of energy transition is the exclusive preserve of “renewable energy critics”.

With this in mind, I’ll state my position as clearly as I can here: an interest in critically assessing the capacity for renewable energy systems to directly substitute for incumbent energy systems should not be conflated with “being opposed to renewable energy”. I myself am a long-time proponent for and supporter of a transition to renewably-powered societies. Having taken the time to be fairly broadly and deeply informed in this area, it is apparent that there are significant uncertainties relating to the forms that such societies might take, especially given the tight coupling between current globally-dominant societal forms, and the characteristics of their primary energy sources. It’s apparent to me that humanity stands a better chance of developing future societies supportive of high life quality if these uncertainties are taken seriously, rather than being discounted or ignored. The question that most interests me here is:

What forms might future renewably-powered societies take, if they are to enable humans and other life forms to live well together?

And following from this, how might we best pursue the process of transition towards such future societies?

Developing a more integrated view of the relationship between societal forms and their enabling energy systems would seem to be of benefit here. I do work in this area primarily because a widespread interest in this is not apparent amongst the communities that currently dominate renewable energy transition discourse and practice. Furthermore, my own inquiry suggests that failing to take a more integrated approach as early as possible could have increasingly adverse consequences as such a transition proceeds.

And with that, it’s back to the primary task of considering what our energy transition model might have to tell us about such matters.

Continue reading

Energy transition, renewables and batteries: a systems view

In the concluding section of the report made available here last month, I hinted at a view on the role of batteries in global energy supply that, in the wake of the announcement from Tesla CEO Elon Musk on 30 April this year, may seem rather at odds with prevailing popular sentiment. I suggested there that, while significant numbers of electricity consumers will likely be motivated to go “off grid” as battery costs reduce, this will entail feedback effects with implications that can reasonably be expected to make for a change trajectory far less linear and predictable than many commentators envisage. Such a view is, of course, entirely consistent with the systemic approach to thinking about energy transitions for which Beyond this Brief Anomaly advocates.

In this post, I introduce the energy transition model I’ve been developing over the past few months, to help make better sense of the physical economic implications of a global energy shift in which wind and PV generation with battery buffering dominate electricity supply. Continue reading

Economic Trend Report: Energy Descent, Transition and Alternatives to 2050

For the past few months, I’ve focused the time available for Beyond this Brief Anomaly on background research and modelling aimed at testing more rigorously some of the conclusions towards which the inquiry has pointed so far. This has come at the cost of keeping things active here though. I’m planning to share some of the results of this work shortly. In the meantime, I was recently looking back over a piece of work on energy transition as a key economic trend that I did last year for a client. It occurred to me that it provides a remarkably good summary of the inquiry’s findings to date, and sets out many of the conclusions that I’ve been stress testing behind the scenes. The report below is a version of the original briefing paper revised slightly for a more general audience than the original. It was last updated in November 2014, but for the most part— save perhaps for updated global oil production data and the post-price plunge tight oil situation in the USA—it continues to be relevant today. Also, the brief comments in relation to battery storage may, to some readers at least, seem rather at odds with the popular view that has gained such a significant boost in recent months. More on that when I report on the background work I’ve been up to.

Download the report pdf.

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

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