As my brief pause from posting may have suggested, I'm struggling with how to best tackle the next step in this series. To recap, so far I've been discussing the "true" EROEI of renewable energy sources--meaning the measurement with no artificial boundary for accounting--and the need and challenges for calculating this figure. My plan was: 1) work through a few price-estimated EROEI calculations (at least one recent solar and one recent wind project); 2) show that these price-estimated EROEI figures are too low to support envisioned transitions to renewable energy sources; and then 3) argue that, while this method of calculating EROEI is itself suspect, until we come up with a better method for calculating boundaryless "true" EROEI, we must seriously scrutinize the viability of the predominant transition vision.
I've been having a difficult time figuring out how to best make this into a solid argument. My initial desire was to use a very numbers-driven approach. I never intended price-estimated-EROEI to provide some verifiable, "true" EROEI figure, however (it is intended more as a reality-check backstop), so I've been concerned with proceeding on such a numbers-driven approach with price-estimated EROEI as the foundation. To be honest, I was hoping that, in writing this series, I would arrive at some far more accurate and transparent means of calculating "true" EROEI. Unfortunately, the result has been the opposite--while I am still convinced of the value of price-estimated-EROEI as a reality check, its inherent flaws have been well highlighted by my own efforts to refine it, and especially by the very thoughtful comments that I've received.
Therefore, I now think it's best to embrace this fuzziness--to use the price-estimated-EROEI in its originally intended role of reality check. While I'm concerned that my critique of the "renewables transition" will now be more logic-driven and less hard numbers-driven, I am increasingly OK with this shift (a decision process which, in part, explains my lack of recent posting). I've arrived at this conclusion because a logic-driven approach actually seems more true to form: I've been arguing for some time that "true" EROEI is fundamentally impossible from a nuts-and-bolts accounting perspective. Instead, we must use proxies to measure emergent phenomena--such as market price--to estimate its value.
That said, here's my current plan: Below I'll outline my calculations of the price-estimated-EROEI of one recent solar project and one (less) recent wind project. Next week, I'll argue the impacts--and uncertainties--of these numbers on the viability of the "renewables transition." Following that, I'll address a number of ancillary issues: an analysis of the minimum EROEI for society (drawing on, but to some extent disagreeing with Hall's work on the same topic), a discussion of the carbon-impact of the "renewables transition," and I'll conclude with, hopefully, some general guidelines for going forward amidst this uncertainty.
Solar Example: Downtown LA Solar PV Installation: This 2009 installation is my example for price-estimated EROEI calculation. I think it's a good example (no example is perfect) for several reasons: at 1.2 MW, it's modest in size, but large enough to reap economies of scale; because it is installed on an existing roof space, there is no land cost associated with the installation (that, in some circumstances, could present acquisition costs or environmental compliance/impact statment costs not truly representative of net energy issues); because it is in California, where the average cost of electricity (and especially peaking "sunny day" electricity that solar provides) is higher, it will provide a more conservative estimate; because it is located in the downtown of a major metropolitan area it will not require significant transmission investment to provide a true measure, and is therefore also more conservative. Finally, there are good cost and output numbers available for the site.Basic data: 1.2 MW array installed 2009 in Los Angeles, cost $16.5 million up front (ignoring rebates/tax credits/incentives), projected financial return of $550,000 per year. At the rough California rate of $.15 per KWh, that's about 4 GWh per year (conservative).
Price-Estimated-EROEI Calculation: The $16.5 million up-front is, at $0.09/KWh (here using national average, as there's no reason to think that manufacturers would use primarily California peaking power to build this system), an input of 183 GWh through installation (I'm ignoring the realtively small maintenance costs here, which will also make the figure more conservative). If we assume a life-span of 40 years, then the energy output of this system is 160 GWh. That's a price-estimated EROEI of 0.87:1.
Wind Example: I've had a more difficult time finding a recent wind project where good data (on both cost and actual, as opposed to nameplate, output) is available. As a result, I've chosen a 2000 Danish offshore wind project at Middelgrunden. While up-front expenses may be higher off-shore (making the resulting EROEI more accurate for offshore projects than on-shore), I think this is a relatively modern installation (2MW turbines). If readers have more current projects with full data, please provide in the comments--another point for investigation is whether the price-estimated-EROEI of solar and wind have been improving or if they are holding relatively stead.
Basic data: Cost of $60 million, annual energy ouput 85 GWh.
Price-Estimated-EROEI Calculation: At the US national average rate for electricity ($0.09/KWh), the $60 million up-front energy investment works out to 666 GWh. Using a life-span of 25 years (and assuming zero maintenance, grid, or storage investment, making the result artificially high), the energy output comes to 2125 GWH. That's a price-estimated-EROEI of 3.2:1.
I'll let everyone chew on these numbers--and the various issues surrounding how they were derived--for the week. If you have access to similar numbers for other solar or wind projects (or numbers for tidal or geothermal), please provide them in the comments and we'll see if we can generate more figures. Next week I'll discuss the impact--and uncertainty--of these calculations.