Estimating the retail price for 100% Australian renewable electricity.
Ted Trainer.
18.4.2017
3314 w
Abstract: The recent simulation by Lenzen et al. (2016) has significantly advanced the exploration of possible costs and implications of 100% renewable power supply for Australia. The analysis arrived at a probable production cost of around 20 c/kWh. This discussion explores the possible implications for the resulting retail price of electricity. A number of factors in addition to those included in the original study are taken into account, especially the uncertainty surrounding the contribution CSP can make to the back-up/storage task in poor conditions. These considerations indicate that the retail price of electricity based on the mix of technologies the study assumed could be in the region of three to four times the present price.
Corresponding Author, Ted Trainer, 5 Dryandra St., Wadalba 2259, Australia. tedtrainertsw@gmail.com 0407011149
Keywords: Renewable energy, 100% renewable electricity.
Highlights:
Funding acknowledgement; No funds were received for this work.
Introduction.
The central issue for the analysis of 100% renewable energy supply is not whether this goal is possible, it is what the cost of the required amount of plant might be when provision has been made for the back up capacity required to enable supply through periods of low renewable energy availability. Numerous analyses have concluded confidently that 100% renewable electricity supply is possible without making any reference to the weather patterns in the regions under discussion and therefore these have been of little or no value.
Two groups have recently carried out the first analyses of the (more or less) total Australian power supply task based on detailed weather information. These find that the production cost of electricity (not total energy) would be c. 10 – 15 c/kWh in one case and c. 20 - 30 c/kWh in the other. However both these pioneering studies of this complex issue inevitably involve a number of assumptions and simplifying omissions. The following discussion attempts to reconsider some of these in order to determine the implications firstly for the production cost of electricity and secondly for the retail price.
Both studies have been interpreted as showing that 100% electricity supply is possible and easily affordable. However little or no attention has been given to the implications of these production costs for retail electricity price. The following examination of the factors operating between production cost and retail price indicate that the difference is likely to be substantial.
The two studies.
Elliston, Diesendorf and MacGill (2012, 2013) deserve much credit for apparently being the first to attempt a national analysis based on actual weather data, recently made available by the Australian Energy Market Opertator. Their general finding is that 100% power supply can be achieved at a cost of around 10 – 15 c/kWh. For coal-fired power the cost per kWh produced for plant plus operations and management (O and M) and fuel is around 3 c. (Cost etc. statistics used here are for the 2014-2016 period.)
However the following discussion is based mainly on the more recent analysis by Lenzen et al., which concludes that the cost might be in the region of 20 c/kWh, and possibly 30.3 c under fairly common conditions. They say the scenario yielding the second figure “…comes close to what would be implemented in the real world”. The both studies seek to determine the pattern of generating units which would minimise the cost of supply capable of meeting demand with high reliability, given the weather patterns for the year 2010. The Lenzen et al. findings are set out in Fig. 3 as a matrix of options that might be selected among, depending on the amount of biomass capacity within the system (…ranging from the present c. 1.7 GW to 15 times that amount) and the price put on carbon. The main plot enables a production cost in cents per kWh to be read off for any combination of these two variables.
The reasons for working here with the Lenzen et al. analysis rather than that by Elliston, Diesendorf and MacGill (and associates) include,
The full real-world production cost?
There are several considerations complicating the drawing of implications from the Lenzen et al. production cost findings for the probable price firms and households would have to pay for electricity. Lovegrove et al. (2012 p. 192) points to the difficulty of predicting costs for future renewable technologies and on p. 109 note that for the (much less difficult) issue of estimating CSP capital costs, ”Large differences between original cost estimates and actual installed costs have been common.” They point to for instance the possibility of significant future price rises for resource inputs to construction.
1. Lenzen et al. only take in capital, O and M, transmission and “fuel” costs. The Prieto and Hall (2013) study of the Spanish PV system attempted to take into account all costs, including usually overlooked factors such as plant security vehicle fuel use. For coal fired power the above four factors add to about 3 c/kWh, but when all other factors are taken into account, including company tax and profit, the wholesale cost rises to about 8 c/kWh (…and then many factors currently multiply this by approximately 3 to yield the retail cost.) We would need similar figures for a complex, multi-form renewable production system. Efforts to tally comprehensive cost inventories do not seem to have been made in EROI studies for renewables, except by Prieto and Hall for PV.
2. The cost assumptions made are commonly quoted estimated 2030 values. These are generally around one-third lower than present costs (and a challengeable 50% lower for CSP, see below.) Although often used the set involves assumptions re expected reductions and “learning curves” that are open to doubt. For instance Wood, Mullerworth and Morrow (2012) and Hinkley et al. (2011) report no fall in CSP plant capital cost as built capacity went from around 90 MW cumulative to around 1200 MW, i.e., despite around a 12-fold increase in plant capacity built. Renewable Energy Focus, (2010) states the same general view and expects no fall to 2025. Fig 9. From Bollinger and Seel (2014) shows an increase in solar thermal cost over time. A report by the Electric Power Research Institute (2010) expects no fall in capital cost for PV, wind or CSP until at least 2025.
For wind, the California Energy Commission (2014) does not necessarily foresee cost falls as this is a relatively mature technology. Continued falls for PV are commonly predicted and likely to occur but Feldman et al., (2014) report several estimates of tapering, indicating around 20% falls to 2040, as distinct from 33% by 2030 as assumed in the AEMO and AETA tables used in this study. There are reports that subsidies for Chinese module production are being phased out. CSP mostly involves relatively simple technology and well established construction engineering suggesting that major cost-reducing breakthroughs here are less likely.
Another cost uncertainty concerns the increasing difficulties and costs associated with providing relevant materials for large scale building of renewable systems. (Dierderen, 2009, Sveredrup and Ragnarsdottir, 2014.)
3. As Lenzen et al. note, the cost figures used assume the exchange rate which held at the time they were made, i.e., the Australian dollar cost of the imported plant would be $1A = $1US. It has since fallen by almost 30%, meaning that the Australian dollar cost of plant, which would be mostly imported, would be over 1.4 times as high as has been assumed.
4. Lovegrove et al. (2012, p. 22) estimate that remote area construction of renewable plant (in his case solar thermal) would cost 10% to 20% more than the commonly quoted figures which assume construction at US and European locations. Most of the sites in Australia would probably be remote. He also says that the initial constructions would involve an additional perhaps 15% cost for technologies that have not previously been built in Australia. In addition regardless of locational issues Australian construction costs seem to be considerably higher than overseas costs, due in part to poor productivity growth. (Freebairn, 2017.)
5. The study did not attempt to take into account the embodied energy costs of generating or transmission systems. This was wise given the uncertainty and disputation in this field, especially for PV. However an ER of 18 - 20 is commonly assumed for the most cost effective sector, wind. This suggests that when all inputs are included for all technologies, along with transmission systems, an overall system cost might be up to 10%.
6. The year 2010 is unlikely to have been the worst ever for renewable generation. My (superficial) examination of Bureau of Meteorology and AEMO data for 3 solar sites and 5 wind sites spread across central to eastern Australia found that the average value over the three sites for the lowest solar radiation on record for each of the twelve months was 17+% below the 2010 figure. For wind the figure was 32% below the 2010 value.
7. The capital cost figures at the beginning of an enthusiastic renewable building program would be present costs, generally one-third higher than those anticipated for 2030. Thus even if costs fall as assumed the average cost of plant built before 2030 would be around15% higher than those assumed.
8. In view of the 2016 South Australian blackout caused by storm damage to the grid, and the subsequent loss of the Victorian interconnector, one wonders how robust the long distance transmission provision assumed by Lenzen et al. is, especially in view of the expectation that in future the greenhouse problem will increase extreme weather events. Would a sufficiently strong grid add significantly to overall system cost?
9. Palmer (2017) has pointed out that an ideal system as indicated by the Lenzen et al. kind of analysis cannot now be built, because much renewable capacity has already been built in locations other than those the study finds to be ideal. Wind farms for instance have been put where grid access is presently favourable, not where a big picture analysis would indicate is best.
10. There are important issues to do with assumptions underlying the role of the solar thermal component which would significantly affect performance and system cost. These will be considered in more detail below.
If only the factors identified in points 3, 4, 5 and 6 above are taken into account the production cost derived from the Lenzen et al. study is likely to be multiplied by 2.3, i.e., to between about 46 and 70 c/kWh. (This assumes Lovegrove’s 1.2 for remote construction but not the 15% first project factor.) If point 7 above is also taken into account the multiple increases by 1.16, to 2.67.
It is difficult to speculate on what the real-world, practical production cost might be for a mix with a much less than maximum use of biomass. (Lenzen et al. do not see the maximum use plotted in Fig. 3 as desirable/achievable.) This would seem to be the case represented in the figure by the fourth column from the left, that is, the one that assumes c. 30% wind, 18% biomass and 18% CSP. This is close to the case Lenzen et al. discuss as “…what would be implemented in the real world”, which has a production cost of 30.3c/kWh. However that figure was generated by assuming a high biomass cost and presumably this cold be avoided simply by capping the system’s biomass use. Nevertheless these considerations indicate that the “real world” production cost this study indicates for a system with low to moderate biomass use might be significantly higher than 20 – 30 c/kWh (before taking into account any of the above 10 factors.).
The resulting retail price?
The important but uncertain issue set by these figures is what retail price for power might a production cost in the range arrived at lead to? The first question here is what wholesale price might these production costs result in. The 2012 - 2014 cost per kWh of coal-fired power associated with the above four factors is c. 3 cents, and this becomes a wholesale price of around 8 cents when all other factors operating within the generating firm exert their influence. The most important of these would seem to be company profit and tax. (Some accounts seem to add insurance but others include this in O and M costs. Interest on borrowed capital seems to be routinely included in the capital cost of plant.)
If the cost of producing power becomes significantly higher than in the past then the cost of the power needed for all the operations and processes involved in building and running power generating plant will be much higher. This includes the cost of the materials needed to build generating and supply equipment, because their production requires energy. In addition costs will compound or pyramid. For instance the higher cost for steel etc. to build turbines will contribute to generating company costs, and the wholesale price of the power the company sells to retailers will be set higher to cover these and make a profit. The retailers will then put their profit margin on top of all their costs, and these costs will include the higher profit amount the wholesaler added on.
What all this will add up to would seem to be impossible to estimate at this stage, but the important point is that if the power production cost at the beginning of the chain of multipliers is at least twice the present amount as the Lenzen et al. analysis indicates then the retail price is likely to be significantly greater than the new production cost plus the present approximately 22c for all steps between production and consumer.
If the Lenzen et al. analysis is accepted along with the multiplying factors in the above four points, and if the present c. 22 c difference between production cost and retail price remains, then the retail price would have to be at least (20c x 2.3) + 22c = 68 c/kWh. For the selected scenario Lenzen et al. discuss the sum would be (30.3c x 2.3) + 22c = 92c/kWh. These figures are respectively about 2.7 and 3.7 times the present Australian retail price, which is already relatively high compared with other OECD countries.
To these figures would have to be added the significant multiplier effects of the other 6 of the 10 factors noted above and these could produce a much higher ratio of retail to production cost. Thus a ratio in excess of 3/1 would seem to be plausible, and this is likely to be significantly economically disruptive. However much depends on issues to do with the contribution from the Concentrating Solar Thermal (CSP) sector, and the following discussion indicates that revised assumptions in this domain would add significantly to system cost and retail price conclusions.
The CSP issue.
Given the complexity of the modeling and computing tasks involved in the Lenzen et al. analysis it made sense to proceed with commonly held assumptions regarding CSP, but following is a summary of the case that some of these assumptions are much too optimistic.
The foregoing derivation of costs is based on the Lenzen et al. findings, which depend significantly on the contribution of CSP in periods when renewable energy is least available. There are three important elements in the Lenzen et al. study which are questionable but could be refined when the approach is further elaborated.
Firstly Lenzen et al. assume the general efficiency of generation to be 30%, based on a table given by Lovegrove et al. (2012, p. 49.) However that text points out that this figure is an estimate of what technical advance might achieve. There is considerable evidence in reports on the CSP systems operating today that current efficiencies are around 14%. (Lovegrove, Zawadsky and Coventy, 2007, Hinkley et al. 2011, Fig. 7, NREL Solar Advisory Model, undated, Kearney Consulting, 2010, Viebahn, Kronschage and Trieb, 2004, Abengoa, 2016, Marin, 2015, De Castro 2017, and Solarstor, 2017.)
The second issue concerns efficiency and net output in poor conditions, especially winter. The Lenzen et al. findings depend considerably on the contribution that CSP can make in periods when the renewable resource is at its lowest. Their Fig. 6 representing five difficult days shows that due to the lack of wind and PV input CSP is called on to provide a lot of electricity, almost always over 15 GW and at times apparently up to 19.4 GW, which is 84% of average demand.
In this initial investigation it was in order to minimize the already complex computational task by assuming that CSP generation efficiency would be the same at all seasons and levels of DNI and times of the year. However this is not the case; the actual efficiency of a plant in winter is in general significantly lower than in summer and varies according to the priorities underlying its design. (Jones et al. 2001, Wood et al., 2013, 4-14, Siangsukone and Lovegrove 2003, Odeh, Bahmia and Morrison, 2003, and Kaneff,1991.)
That the effect is not trivial is evident in data via a personal communication from the Torresol generating company which operates Gemasolar in Spain (Marin, 2015), and from Solarstor, (2017.) The Solarstor device has an average ”Field efficiency” in summer that is twice its winter value i.e., the ratio of heat collected to solar radiation intersected by heliostats. This falls sharply as DNI falls, that is, faster than the fall in DNI. For instance at 400 W/m2 “field efficiency” is 61% below its level when DNI is 1000 W/m2, and heat is being collected at only 15% of the 1000 W/m2 rate.
The data on Gemasolar confirms the indication from Solarstor that the effect is marked. When DNI is 463 W/m2 the efficiency of heat delivery is only c. 20%. If a turbine efficiency of 33% is added the efficiency of solar to electricity generation would appear to be under 7% (…and this does not take into account loss of parasitic energy.) If this reasoning is more or less valid the CSP contribution represented in Fig. 6 in Lenzen et al. would have required more than four times the 61 GW capacity found to be needed (or would have required resort to be made to some other storage strategy.) Note that average Australian demand is 23 GW.
Finally Firstly the capital cost assumption (taken from AETA 2012 and ‘Scenario 1 2030’ in AEMO 2013) represents a large (56%) fall from the present cost given by AEMO, which is almost double that assumed for the other technologies. The 20 MW Gemasolar Plant in Spain was the first to be equipped with15 hour storage, assumed by Lenzen et al., and its capital cost has been reported as $(US)419 million , or a remarkable $21,000/kW (Wilson, 2011) and three to four times the Lenzen et al. cost assumption.
Thus if future applications of the Lenzen et al. approach can incorporate more complex CSP assumptions they are likely to arrive at a significantly higher production cost estimate than that informing the above derivation.
Conclusions.
The quantities arrived at above are not precise or confident but they indicate the kind of analysis needed to derive implications for the likely retail price of electricity from the studies such as that by Lenzen et al. which understandably deal only with a limited set of production cost factors. The assumptions and derivations set out above would seem to support the general conclusion that the retail price resulting from the pattern of generating technologies arrived at by Lenzen et al. would be much higher than the production cost they arrived at. Reasons are given for thinking that it could be more than three to four times the present retail price.
This exploration suggests that on the global scale the quest for 100% renewable electricity supply will involve retail prices that might be tolerable in renewable-rich regions but even there are likely to be at least significantly economically disruptive. If this is so, this strengthens the case for seeking a solution on the demand side involving De-growth to simpler lifestyles and systems. (See Trainer, 2017.)
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