Ferroni and Hopkirk revisited
Ferroni and Hopkirk published a paper last year titled ‘Energy Return on Energy Invested (ERoEI) for photovoltaic solar systems in regions of moderate insolation’. They concluded that the EROI of solar PV in Switzerland was below 1:1, or a net energy loss. Not surprisingly, the paper raised a few eyebrows, and a rebuttal has been published from Raugei et al. This follows on from a previously published rebuttal of a paper by Weißbach et al. in 2014, also with a low solar EROI.
<update 21 May 2017 – Ferroni, Guekos and Hopkirk have published a rebuttal to Raugei et al’s critique here>
The critique from Raugei et al. identifies a number of methodological flaws and inconsistencies in Ferroni and Hopkirk, but the main criticism relates to the use of non-conventional methodology –
Net energy analyses may be conducted using a variety of boundaries and assumptions, all of which, in principle at least, may be considered valid … but that … extending the EROI boundaries … shifts the goal of the analysis from the (comparative) assessment … to the assessment of the ability of the analysed system to support the entire societal demand for the type of energy carrier it produces, or sometimes even for all forms of net energy.
I agree with much of Raugei’s critique regarding PV system price, the problem of ascribing energy consumption to labour, the use of outdated data, assumptions around performance and others. Raugei (and others) have made an important contribution. The only way in which EROI can be taken seriously is be adhering to a consistent methodology. But the critique also reflects a broader problem – the IEA-PVPS guidelines are not providing a comprehensive examination of the value of PV. It’s worth looking at how these studies are conducted.
Solar PV life-cycle assessments (LCA’s) are nearly always conducted with a process-based life cycle inventory using an attributional framework. This requires drawing a boundary around the manufacturing processes of PV and measuring the direct energy into those processes. Depending on time and effort, the researcher steps back up the value-adding chain and cumulatively adds up the embodied energy. Since there are a only few energy intensive processes, identifying those processes is said to provide a reasonably comprehensive stocktake of embodied energy. The main benefit of this method is that the researcher can apply the clearly defined guidelines and boundaries from the IEA-PVPS. This is useful for comparing similar products. LCA practitioners declare the scope, utilise standard methods, and these work well within the LCA community.
The main point of contention is that many EROI practitioners are more interested in a ‘bigger picture perspective’ than a comparative assessment of different PV types. High EROI generally correlates with low energy cost and contributes to productivity and economic growth. The EROI of oil, coal, and hydro has conformed to this principle. High EROI oil drove earlier 20th century economic growth, while lowering EROI from the 1970s contributed to recessions. We want to know whether an energy source is a net-source or net-sink and how much it contributes to human welfare. Where is our energy going to come from as we rely less on fossil fuels? What is the new energy source substituting for?
The problem is that the pre-defined and narrow boundaries defined by the IEA-PVPS are not really telling us much about the impact of solar PV on overall energy costs or economic growth.
As a starting point, solar PV has three important strengths –
1. it’s modularity makes it highly scalable
2. the photoelectric effect lends itself to progressively lower manufacturing costs and easy installation
3. its social acceptance ensures a low regulatory hurdle.
Yet despite improving EROI and lower costs, solar is not leading to lower overall energy costs or transforming industry in the way that previous energy transitions have. In European countries, there is a strong correlation between installed RE per capita and electricity costs. The conventional idea of EROI as it applies to oil, coal, and hydro does not seem to apply.
There seems to be three main issues.
1. Solar is highly seasonal and in many parts of the world, it’s availability does not correlate well with demand.
2. Although predictable, solar power is of course variable.
3. Unlike conventional electricity generation, nearly all of the energy investment of solar is an upfront energy debt, but the EROI is calculated on an energy return over a 25 or 30 year life.
Ferroni and Hopkirk’s solution for intermittency is to add storage to the analysis. But Raugei et al. note that –
For example, they add an unreasonably extended storage requirement to PV but not to nuclear, ignoring that PV primarily serves peak loads while nuclear only serves base loads and both of them (not only PV) would require storage in order to satisfy total demand loads. This is problematic because the way in which the analyses are presented to the reader implies that any differences in the reported EROIs are due to data inputs – i.e., something inherent to the technologies or resources under investigation – and not an artefact emerging from methodological inconsistencies between the studies being compared. The latter is actually the case here.
I agree that there is a problem of adding an arbitrary amount of storage without providing supporting evidence for why this quantity has been selected. But Raugei et al. also seem to mistake the reason for buffering of solar. Conventional generation does not need buffering to ensure a low outage rate – each generator contributes to overall system reliability. The reason for adding storage to intermittent power is to increase its availability, whether that is used during peak or off-peak periods. There is certainly a case to made for thinking about whether the cumulative energy demand (CED) of peak-load generation should be added to baseload in order to arrive at a total picture, but this is quite different to arguing that there is an equivalence between variable renewable energy and baseload. Electrical systems are built according to system capacity, not system annual energy.
In summary, the second last paragraph in the conclusion perhaps reflects the divergence between the aims of different EROI researchers –
Also, extending the boundaries of the EROI calculations in order to estimate the ability of a certain technology to support the present civilization tends to stretch the value of this measurement beyond its initial intended purpose, and the vast uncertainties involved in doing so make it a risky enterprise that might easily lead to wrong policy choices.
Yet understanding how the ‘present civilization’ can transition from fossil fuels is precisely the motivation for many EROI researchers. If EROI researchers are not going to undertake this task, who will?