Energy Return and Economic Planning

  • Date: 22/02/17
  • Dr John Constable: GWPF Energy Editor

A recent academic paper suggested that the Energy Return on Energy Invested (EROEI) of Solar Photovoltaic in northern latitudes was actually less than unity, in other words that the technology was a net energy consumer. In response, another paper argued that it was probably in the region of 7 to 10. Read together the papers in fact tend to strengthen the conclusion that there is so much uncertainty in such calculations that no administrative decision can be safely based upon them, and that it would be better to leave the matter to the neural network of a liberal market which will gravitate spontaneously to high energy return sources because they are cheaper.

In 2016 Ferruccio Ferroni and Robert J. Hopkirk published a striking article (“Energy Return on Energy Invested (ERoEI) for photovoltaic solar systems in regions of moderate insolation”, Energy Policy 94 (2016), 336–344) claiming that the energy return for Solar PV sites in Switzerland might be as low as 0.8, implying that the technology was not a net energy producer but a consumer. Unsurprisingly, this paper has been the subject of intense criticism, and a detailed and in many points persuasive rebuttal has recently been published by Marco Raugei et al. (“Energy Return on Energy Invested (ERoEI) for photovoltaic solar systems in regions of moderate insolation: A comprehensive response” Energy Policy 102 (2017), 377–384). Raugei and his colleagues make a number of methodological criticisms of Ferroni and Hopkirk and using alternative methods, calculate that the energy return is in the region of 7 to 10. While Raugei et al’s figure is positive it is not particularly high, as compared for example to figures in the literature for electricity from coal and gas (EROEI = 28–30), and nuclear (EROEI = 75–105) (see D. Weissbach et al. “Energy intensities, EROIs (energy returned on invested), and energy payback times of electricity generating power”, Energy 52 (2013), 210–221).

Exciting though these disputes are, and it cannot be denied that the entire EROEI literature has a deep academic fascination, it is obvious that even at their best the methods are extremely sensitive to premises that may well prove to be mistaken. In other words, it is impossible to avoid the conclusion that EROEI is not a robust calculation and is barely in the realms of intersubjective science.

Interestingly, these uncertainties are almost entirely in the Energy Invested side of the equation (on Energy Return, in fact, Ferroni and Hopkirk and Raugei et al. in substantial agreement). This suggests that the analysis has some key weaknesses not entirely dissimilar to those of the Levelised Cost of Electricity (LCOE) method as it applies to renewables. As is well known, the system effects of uncontrollably variable renewables are not adequately addressed by LCOE, since adding uncontrollably variable renewables to a system increases overall costs (new grid and operating procedures, and suboptimal operation of the conventional fleet), all of which tends to reduce system productivity thus increasing costs. LCOE doesn’t capture this, so a Total System Cost analysis is required to discover what the probable effect would be on the consumer.

The situation with EROEI is rather similar. Rather than just asking whether a technology has a high or low EROEI in an isolated or laboratory sense, we should be asking what the presence of a particular solar PV or wind turbine fleet, for example, does to the EROEI of the overall system of which it is a part. No one would deny that such an analysis is even more difficult than the narrower estimates attempted by Ferroni and Hopkirk and Raugei et al. Perhaps it is impractically difficult, but that  brings us to the broader point. – It seems that however gifted and scrupulous the researchers attempting a comprehensive EROEI calculation, whether at a site or system level, neither the reasoning nor the information can be sufficiently robust to inform an administrative decision on a crucial economy-wide investment with a lifetime measured in decades and far reaching economic consequences.

Of course, it is precisely because of such epistemological limits that economic planning in general is so unwise, and that with any major complex decision there is no alternative to allowing the neural network of free contractual markets to react to the full conspectus of data available, as represented in the price. This is as true in energy policy as it is elsewhere. In fact, and for obvious reasons, price will be strongly correlated with EROEI, a high energy return yielding cheaper energy. Consequently, competitive energy markets will always gravitate towards the highest EROEI systems available because they are cheaper for the consumer. Would solar and wind survive that experiment? The need for both income support subsidies and market coercions compelling consumers to purchase the electricity suggests not, but it would only be fair to give them a chance and put them to the test in an undistorted market. This would be academically very valuable, as well as good for the consumer.



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