THE LIMITS TO SOLAR THERMAL ELECTRICITY.

14.5.12

Ted Trainer

Conjoint Lecturer, Social Sciences and International Studies, University of New South Wales, Kensington, 2052. F.Trainer@unsw.edu.au Tel. 61 02 93851871.

Abstract: Accessible evidence on the likely output and costs of trough, central receiver and dish technologies is analysed with a view to assessing the capacity of solar thermal systems to meet electrical demand in mid-winter. In view of the need for storage most attention is given to Big Dishes and central receivers. It is concluded that for solar thermal systems to meet a large fraction of anticipated global electricity demand in winter would involve prohibitive costs. Problems of variability and storage are discussed and are found to add significant difficulties despite the capacity for heat storage, indicating that it is not likely that solar thermal systems could enable the meeting of electricity demand through protracted periods of low solar radiation. This study adds to the case that energy and greenhouse problems cannot be solved by renewable energy.

Keywords: Renewable Energy. Solar Thermal Power. Limits to Growth.

The prospects for a high proportion or all of world energy demand to be met by renewable energy sources is likely to depend primarily on the limits to solar thermal supply in winter. Although solar thermal systems are likely to be among the most significant renewable energy contributors they are best suited to the hottest regions and previous studies do not make clear how effective they can be in winter, even in the most favourable locations. The purpose of the following discussion is to consider the capacity of solar thermal systems to meet demand in winter, the variability and storage issues involved, and the probable investment costs.

Unfortunately the data required for confident conclusions on these questions is not readily available. This is partly due to the lack of critical studies in this area, but mainly to the fact that solar thermal developers rarely make publicly available the key data on the performance of commercially operating plants. (Heller, 2010, Blanco, 2010, Mancini, 2010.) However there are theoretical studies and models enabling a useful indicative examination of the issue. At least the following analysis offers an approach which can be reapplied as more satisfactory data becomes available.

Troughs.

The ratio of winter to summer output for troughs is considerable, in the region of 1/4 or 1/5, and much greater than for dishes or central receivers.

(Odeh, Behnia and

Morrison, 2003, Fig. 2, Kearney, 1989, Fig. 2, Bockamp et al., 2003, IEEE, 1989 1989, Mills, Morrison and LeLeivre, 2003, Czisch, 2001, Booras, 2010, NREL, 2010, 2011.) This is due to the geometry determining that the angle between sun, reflecting surface and absorber is relatively large much of the time. Thus troughs are not likely to be able to make a major contribution to electricity supply in winter.

Dishes.

Lovegrove, Zawedsky and Coventry (2006) claim dishes are in general 50% more efficient than troughs or central receivers. The advantages of dishes are firstly that they can be pointed directly at the sun all through the day and thus avoid the cosine problem which affects trough and central receiver or tower systems and for the former are especially serious in winter. Secondly the high concentration ratios enable higher temperatures than troughs, which make possible more efficient generation of electricity via Stirling engines at the focus of each dish. Thus the heat losses and pumping energy losses involved in transferring heat long distances to a generator are avoided. However as dish-Stirling systems do not involve storage they cannot be major contributors in winter.

The main non-Stirling dish initiative is the Australian National University 400 square metre “Big Dish”. (Lovegrove, Zawedsky and Coventy, 2006.) Its annual average solar to electricity efficiency has been estimated at just under 14%, but it is anticipated that this can be raised to 19% in future. (Uncertainties surrounding this figure are considered below.).The figure is net of operating energy costs and takes into account transient cloud. However it is not clear what the winter solar to electricity efficiencyperformance would be. It is an experimental device and has not been used to provide electricity to the grid over extended periods.

The possibility of using such dishes to collect and store heat is uncertain, and does not appear to be being explored. Kaneff (1991, 1992) sees this as viable, and believes losses can be kept to c. 4 – 5 %. However some European dish developers regard the problems of heat transfer through large numbers of moveable joints and for long distances as too great. (Heller, 2010.) (Troughs involve long distances but fewer moveable joints and most of the piping length is heated absorber.)

The information given by Lovegrove, and by Kaneff show that the high future solar to electricity efficiency claimed for the Big Dish is due to the assumption of a large scale turbine, and therefore would involve large collection fields and long piping distances and heat losses. Both assumed that the turbine will operate at .35 efficiency, which is 36% greater than the figure for the efficiency of the turbine used in the present Big Dish. If the heat losses and insulation costs, for very large fields are greater than those assumed in the figure for a single Big Dish, as seems likely, then the .19 solar to electricity figure used below will be an over-estimate, or the system capital cost estimate used will be an underestimate.

As DNI falls the solar-to-electricity efficiency of dish-Stirling systems falls. (Davenport, undated.) The figures suggest that at the typical maximum winter DNI in Central Australia, c. 730 W/m², i.e., 27% below peak, output that would be 40% below peak, a decrease in solar-electricity efficiency of 13% below the level at peak insolation.

The Big Dish exhibits this effect. Figures 3, 4, 10 and 11 from Siangsukone and Lovegrove (2003) show that on day when DNI is c.1000 W/m² power output averaged about 38-40 kW/m2, but on a day when DNI was around 800 W/m² output averaged about 20 kW, (reaching 26 kW late in the reported period.) In other words a 20% fall in DNI from the peak value resulted in a 49% fall in electricity generated. This is somewhat puzzling as it, which is consider ably greater than the fall evident in the dish-Stirling evidence above. Extrapolation indicates that at 730 W/m² output would have been 16 kW, 41% lower than at peak insolation.

No evidence has been found on the possible effect of lower DNI on the efficiency of the ammonia dissociation process. In general thermal energy systems are most efficient when temperatures are at their highest. It is likely that an ammonia dissociation system designed to operate best with ideal DNI levels would be significantly less than .7 energy-efficienct at 700 W/m². In Central Australia in winter DNI rises above 700 W/m² for only about 4 hours a day. This will be disregarded in the following discussion.

The ANU solar thermal group is exploring the use of the high temperature achieved by dishes to transform ammonia into nitrogen and hydrogen which can be stored without insulation via processes common in the fertilizer industry, and recombined later to release heat. (Lovegrove, et al., 2004, Kreetz and Lovegrove, 2002, Lovegrove, and .) They estimate and that the storage in-and-out energy efficiency would be .7. (This seems to be given as the upper end of a possible range under ideal conditions. Kaneff, 1992, p.143 states the efficiency at .6.) These figures indicate that in winter with insolation of 5.7 kWh/m²/d and a .19 solar to electricity efficiency, electricity corresponding to a 24 hour flow of 31.6 W/m² would be generated from an ammonia storage system.

However more recently Dunn, Lovegrove and Burgess state that to store the output of a 10 MW big dish plant for 28 hours via Ammonia would require 162 km of 30 cm diameter pipe of 12.7 mm thickness, capable of taking the high pressure. These figures were confirmed by personal communications, which also revealed that it would be more appropriate to assume 24 hour storage and thicker pipe in view of the likely corrosion caused by the gases. The embodied energy cost of such a large amount of steel pipe would seem to clearly disqualify this approach. It would amount to around 40% of total lifetime plant energy output.

Central receivers.

UnfortunatelyBecause little or no evidence is publicly available on the actual performance of the few central receiver systems in commercial operation little space can be given to them in this discussion as t(he operators will not release performance information. However some iidea of their probablempressions regarding their likely performance can be based on the figures given in Sargent and Lundy (2003), and the NREL (2010, 2011) Solar Advisor Model. The latter source 9’s report.

The anticipated long term future model is a (nominal) 220 MW peak system with a 280 m high tower and 2.65 million square metres of collection surface, set out over a 2+ km radius. The anticipated average annual solar to electricity efficiency is .165 (although also given as .173 in some tables.) This means that peak generating rate would be around 437 MW but its 24 hour average output at a site where DNI is 7.5 kWh/m2/day would be 137 MW. Gross wWinter output in Central Australia would be 40 W/m2 (before taking into account the thirteen reducing factors discussed below .)

This is a significantly higher estimate than that of Vvan Voorthuysen, (2006), (an optimist regarding solar thermal systems, arguing that they can supply total world electricity demand.) He concludes that if 7.5 kWh/m2/day DNI is assumed output would average 32 W/m2. b

provides three example cases for a Southern Californian site, where the NASA radiation source indicates a mid-monthly average DNI of 5.2 kWh/m²day. The estimated average winter monthly output from the c. 1 million square metre collection area, is given as million kWh. When transformed to a 5.7 kWh/m² site, typical of Central Australia, this output correspond to a continuous 24 hour flow of just over 28 W/m², a little lower than for the Big Dish plus ammonia storage system.

This approximate value indicates that the above evidence of a significant fall in trough solar – electricity efficiency at low DNI is also characteristic of central receivers. If efficiency in winter had been the overall annual average .16 stated for the NREL central receiver examples, output in winter would have corresponded to 38 W/m², rather than 28 W/m². In one of the other NREL example the winter solar – electricity efficiency is only 11.4%, which is around 67% of the annual average and 49% of the summer figure. This is of considerable importance below where the effect of winter minimum DNI levels has to be taken into account.

Another uncertain reducing factor concerns the difference between summer and winter average angle between sun, reflectors and absorber. In winter troughs suffer marked effects due the geometry of their alignment with the sun throughout the day, causing the quite low performance of troughs in winter. As the sun travels across the sky in summer its angle with the (N-S) axis of the trough is close to 90 degrees all day, at a good location, but in winter it is around 60 degrees, meaning that a square metre of collector receives half as much (cos 60) solar energy as the DNI value per square metre. Dishes can be pointed directly at the sun all day in summer and winter, and they have only slight curvature, meaning that this “cosine loss” is much less and only due to the low average angle between sun, reflector and absorber.

With central receivers the situation is more subtle and difficult to estimate. Radesovich (1988) states the average cosine loss for a central receiver as 21%. A central receiver field resembles a fresnel arrangement of a dish but a inefficiency is created by the fact that when the sun is at a low angle to the horizon the high absorber is not at a point analogous to the focal point of a parabolic dish. The angle between it, reflector and absorber is low to very low for all the mirrors on the sun’s side of the tower, and at Mildura at midday in winter one would have to go almost a kilometre south of the tower to find a reflector normal to the sun. For almost all the reflectors north of this one the angle between sun, reflector and absorber would be low to very low. The result is that the average angle between sun, reflector and absorber in summer when the sun is higher in the sky all day is somewhat greater than in winter when it is lower all day. Note that this is for midday and in winter mornings and afternoons the sun is even lower above the horizon. (NASA tables show that for Algeria the average hourly angle of the sun above the horizon in summer is 46 degrees and in winter only 27 degrees.) Tables 3 – 6 from Alpert and Kolb (19889) sets out the differences and it is evident that when the angle goes from 90 degrees to 15 degrees the efficiency of the field can fall by one-third. An attempt to estimate the effect graphically indicates that Aat Mildura, ,35 degrees south in South Eastern Australia, the angle averages 26 degrees over the best 6 hours of the day, and at n attempt to estimate the effect graphically indicates that mid day in winter the difference in energy received at the absorber would be c.15% lower than in summer, (and it would be lower still in mornings and afternoons as the average angle over the remaining 4 hours of sunlight is under 10 degrees.).

This cosine factor is probably the main contributor to the considerable obsedrved difference between solar-electricity efficiency for central receivers in summer and winter. (The reference here is to the proportion of daily radiation represented by daily electricity production, not to the conversion efficiency at a point in time or for a level of DNI at a point in time.) Radosevich (Table 4 - 3) shows that daily solar – electricity conversion in summer was a surprising 4 to 9 times as great as in winter. Alpert and Kolb report marked reduction in efficiency with low DNI (c. p. 21.) Over the three years in which NREL experimented with a 10 MW pilot plant the ratio of mid-summer to mid-winter monthly gross output was 4.2, 7.6 and 7.2. The ratios for net output were up to 25% lower (i.e., 10/1 in one year). Alpert and Kolb, (Table 5 - 1, p. 59.)

Some light can be thrown on these ratios by Fig. 4 –1, p. 43 from Alpert and Kkolb showing daily output in relation to DNI. For the Solar 1 devicer, DNI must reach almost 8.75 kW/m2 before any power is generated, indicating that output is not proportional to DNI but increases rapidly only after a relatively high value is achieved. In other words, in winter the lower DNI results in disproportionately lower electrical output.

If reduced to take into account the loss in transmission to the eastern Australian population centres, or from North Africa to northern Europe the delivered winter rate would be around 34 W/m2, somewhat better than for delivery from dish-ammonia systems.

The ZCA report (2010) claimsed that it would be preferable to avoid the long distance transmission problem costs and losses by locating central receivers closer to population but in less favourable DNI. The location they choose closest to Australian population centres is Mildura but winter DNI there is given by NASA as 3.9 kWh/m2/day (i.e., below the 4.25 kWh/m2/day ZCA assumes.) NASA tables also state variation around the average and list the minimum as 3.45 kWh/m2/d. When other effects are added, such as the limits to do with threshold, warm-up and reduced solar-electricity efficiency, it is unlikely that a significant amount of net power could be produced at such a site in winter.

The solar to electricity efficiency of the two systems NREL investigated was in the region of 6%. These were early experimental and pioneering early projects and Sargent and Lundy and the NEEDS report (2008, ( and Trieb, undated200) anticipate achievement of 16 -18% in future. However it is not likely that the summer/winter output ratios will alter as these are primarily due to the rather intractableinsic geometry of the central receiver layout. As with troughs a configuration that increased winter output could be designed, (e.g., by locating the tower on the sun’s side of all reflectors) but this would reduce annual output, and not raise winter output markedly compared with winter output from a normal layout.

Thus the best central receiver strategy for Australia would seem to be to locate in Central Australia where DNI is around 5.7 kWh/m2/day and incur the possibly 15% loss in transmission to the demand centres. However in view of the summer/winter output ratios reported above, central receivers would seem to be significantly poorer performers in winter than troughs. Applying a 6/1 ratio to the average 40 W/m2 derived above suggests a winter average output in the region of 13 W/m2, before taking into account the effect of the 13 factors listed in the next section. If this (uncertain) figure is more or less valid then the most promising option for in winter supply would seem to be the dish-ammonia strategy.

Factors reducing net solar thermal output.

A full energy accounting would have to include the following factors which reduce the net energy that could be delivered. There are three major factors.

The embodied energy cost of plant. The available evidence on the life cycle embodied energy cost of solar thermal systems is unsettled and unsatisfactory, especially regarding the absence of estimates which take into account all “upstream” costs, e.g., the energy needed to produce the steel works that produced the steel used in solar thermal plant construction. These factors can double cost conclusions for steel, and treble those for PV modules. (Lenzen 2009, Lenzen,1999, p. 359, Lenzen and Dey, 2000, Lenzen and Treloar 2003, Lenzen and Munksgaard, 2002, and especially Lenzen et al., 2006, Crawford et al., 2006 and Crawford 2011.)

The studies reported roughly indicate that embodied energy costs not taking into account upstream factors can be 5 – 11+% of lifetime energy produced. (Dey and Lenzen, 1999, p. 359, Weinriebe, Bonhke and Trieb, 2008, Norton, 1999, and Vant-Hull,1992-3, 2006, Kaneff, 1991, Herendeen,1988, Lechon, de la Rua and Saezes, 2006, Lenzen, 2009, p. 117.) Dey and Lenzen state 10.7% for a central receiver. A 10% figure will be assumed here for solar thermal plant cost. although it is likely that a full accounting of upstream factors would yield a considerably higher figure. The embodied energy cost of the long distance transmission lines and substations should also be included. These would be substantial; Czisch estimates their dollar cost at approximately one-third of plant cost.

Loss in long distance transmission. For transmission via High Voltage DC lines from North Africa or the Middle East to Europe, or from the South West of the US to the North Eastern cities, a considerable loss of energy would occur. Mackay (2008) and Czisch (2004) say this could be 15%. (For similar estimates see also Breyer and Knies, 2009, the NEEDS report, 2009, Ummel and Wheeler, 2008, Jacobson and Delucci, 2011, pp.1183-4.) Losses in local substations and distribution, i.e., after the long distance high voltage lines reach urban centres, which might be 7% of energy received, must also be included, suggesting a total loss of 22%. However the total loss figure for combined long distance transmission plus local distribution assumed below will be 15%.

Cooling turbines in the desert regions where solar thermal generation would take place access to sufficient water is a significant problem. Cooling via air avoids this problem but is less efficient, requiring 7% of energy output according to the IEA (2010) and Harvey (2010), and imposes a 10% dollar cost increase. Discussions tend not to make clear whether these costs have been included but it will be assumed below that they have been built into the NREL figures used.

It will be assumed that the NREL SAM figures take into account plant operating and management energy costs, the effect of passing clouds (“transients”), down time for repairs, the morning start-up delay, storage loses, and loss in heat transfer to the power block. It is not clear whether they take into account supplying water to desert regions for reflector washing or cooling of absorbers by the wind.

Taking into account the two main factors above, i.e., losses in transmission and local distribution, and embodied energy costs, indicates that the net 24 hour continuous rate of electricity delivered at long distance in winter from central receivers around 22 W/m². Therefore a central receiver plant capable of delivering 1 GW would need a collection area of 45 million square metres.

Dollar costs.

The NREL theoretical example central receivers assume about 1 million square metres in collection area and cost around $658 million, i.e., the average cost per square metre is about $660. If in winter electricity could be delivered at distance at the rate of 22 W/m² net of energy losses due to embodied energy and transmission losses, than a plant capable of delivering 1 GW at distance under average winter DNI would cost in the region of 45 million m² x $650/m² = $29 billion.

What reduction in cost is likely in the long term future? Predictions tend to assume cost “learning curves” observed in other (selected) engineering fields. However, but that term might best be confined to improvements in an established technology brought about by increased production scale, plant size, and technical advance, whereas dish and central receiver CR technologies (unlike troughs) aremight best be regarded as no not yet established on a clearly preferable path. For instance or at the anticipated scales. (Eg., central receivers in use are a small fraction of the greatly increased 220 MW scale anticipated for central receivers and this will set engineering challenges that have not been encountered to date.so far

It is often assumed that technical advance and scaling up to mass production will have a large marked reducing effect on unit price, but the NEEDS report (2009, Fig. 3.8) and the review studies reported by Hearps and McConnell, (2011, p. 31), expect costs to only approximately halve by 2050. Jacobson and Delucci (2011) expect a 39% fall. ABARE (2010) and AEMO (2010) predict only a c. 35% fall in Australian solar thermal capital costs between 2015 and 2030. Solar Paces (undated) does not expect a significant fall between 2010 and 2030. According to Wood et al., (2012, levelled out, and will not fall further even with considerably increased cumulative production..

A significant concern problem for those assuming cost reductions is set by recent trends for wind turbines as some of these have run sharply against the conventional wisdom. In the eEarly 2000s the commonly stated cost for wind was c. $1,500 per kW of capacity. Wind might be regarded as a “”mature” technology now enjoying the “learning curve” benefits of a rapidly increasing production scale. However in recent years turbine costs have risen not fallen. ABARE (2010) reports the average cost or units built in Australia as a remarkable $2,900/kW, including a 30% increase in onethe last year. Jacobson and Delucci (2011) report a 37% rise in the seven years to 2009, but expect costs to fall in future. EPRI (2009) reports a rise in solar thermal electricity cost from $175/MW to $225/MW in the year to 2009, a 30% increase.

Confusing the issue is the recent rapid increase in supply of wind turbines and PV panels from China, lowering costs considerably. However the associated labour costs can be regarded as extremely low, unlikely to endure in the long run, and not indicative of technical advance in production systems.

This evidence prohibits confident cost expectations for the more distant future.

Easily overlooked is the fact that all these future cost estimates assume present materials, construction and energy costs, and in future materials and energy inputs are likely to be considerably more expensive than they are now. Clugston (2012) for instance reports remarkably steep rising cost curves for energy and materials since the early 2000s, e.g., 14 -20% p.a. However the working assumption made below is a 50% fall in capital costs.

The following discussion deals only with capital costs and does not include operations and management costs, which are significant additions to total lifetime cost. Lenzen (1999) says for large solar thermal plants these costs could add to almost 20% of plant capital cost. Hearps and McConnell (2011) indicate c. 16%. The IPCC (2011, p. 8) says the two ways of deriving O and M costs yield a lifetime cost 25% and 33% of capital cost respectively. The solar thermal lifetime O and M figure given by Booras (2010, Ch. 8 p. 2) corresponds to 20% of capital cost, for an estimated 25 year plant lifetime. (ABARE, 2010.)

Solar thermal systems are typically located in deserts a long way from demand and the costs of long distance transmission lines should be added. One line might cater for only three 1000 MW solar thermal power stations, so if solar thermal is to be a major contribution to European electricity supply hundreds of lines would be required. According to Czisch (2004) transmission lines from the Sahara to southern Europe under the Mediterranean Sea would probably add one-third to plant cost. DESERTEC proposals refer only to supply over relatively short distances, such as from Morocco to Spain and from Egypt to Turkey. Supply to Sweden or the UK from the best North African regions, towards the East of the Sahara, would be considerably more costly.

A factor confusing cost estimation is that capital costs are stated in terms of dollars to produce 1kW of electricity at peak output, i.e., in 1000 W/m² radiation. The NREL SAM example quoted above costs $658 million and has a nominal peak capacity of 100 MW, thus is rated at $6,580/kW(e)(peak). However the average annual production rate given is only 55 MW. This means the cost of building a plant of this kind would be $12,000 for each 1 kW produced. (These are figures for gross output, not output net of the above mentioned losses, and are not for winter output.)

Trough costs.

According to Sargent and Lundy (2003) the “near term future” cost of solar thermal trough systems will be $(US2003)4,589/kW, or $(A2003)6,556 (using the early 2000s exchange rate.) According to Sargent and Lundy (2003) the “near term future” cost of solar thermal trough systems is $(US)4,589/kW, or $(A)6,556 (taking the early 2000s exchange rate.) This figure includes heat storage, which reduces required generator capacity and cost. Their long term future, (2020) cost prediction is $(US)3,220/kw.

However, NREL (2005) states that the 2003 cost for the SEGS systems wais $(US2003)7,700/kW which would have corresponded to $(A2003)11,000/kW. Viebahn, Kronshage and Trieb, (2004, p. 20, Table 2 – 3, p. 12) state e5300/kW. They expect costs to halve by 2050. (Fig 3 – 7.) The example case given in the NREL, (2010) SAM modelling package states $(US2010)8,243/kW. These sources indicate a trough cost at least 25% higher than for central receivers; (see below.) ACIL Tasman (2010) estimates the average 2015 Australian capital cost for troughs (with 6 hour storage) at $7,876/kW, and the associated LCOE at about 50% higher than for central receivers. Booras (2010) states trough capital costs at $8,751, 1.35 times the figure for central receivers, and trough LCOE at 1.5 times that of troughs.

When this relatively higher cost range for troughs compared with central receivers (below) is considered along with the above low winter output figure for troughs, central receivers seem to be clearly preferable. (This is the conclusion arrived at by Hinkley, et al., 2010, and the Wyld Group, 2012, p. 23.)

ABARE predicts only a 34% fall in solar thermal cost between 2015 and 2030. EPRI (2009) actually reports a rise in solar thermal electricity cost from $175/MW to $225/MW, a 30% increase in the year to 2009. It is noteworthy that the recent NEEDS (2008) estimate is in the region of $(A)17,000 per kW.

A coal plant plus fuel (early 2000s price) over plant lifetime would cost approximately $(A)3,700 million, although more recently costs of electricity generating plant in general appear to have risen significantly. The above solar thermal plant cost figures are for peak outputs but the average output from a coal plant is c. .8 of peak whereas for a solar thermal plant it is around .2 of peak capacity. Thus taking the above coal power figure and the Sargent and Lundy estimate, the “near future” capital cost per gross kW delivered on average (as distinct from peak) from a solar thermal plant would be about 12 times as great as for coal including fuel, (indicating so possibly 6 times as great as in 2010now.)

In addition solar thermal systems are typically located in deserts a long way from demand and the costs of long distance transmission lines should be added. Transmission lines from the Sahara to Europe under the Mediterranean Sea would probably add one-third to plant cost, according to Czisch (2004).

Thus it is not at all clear what should be assumed regarding future costs for solar thermal systems. Indeed there is evidence from recent trends for wind and solar thermal construction which suggest that costs will not be lower. Note that the figures discussed are for the annual average output, and thus do not indicate plant sizes and costs that would be required to enable solar thermal plant to produce as much power as a coal-fired plant in winter.

Easily overlooked is the fact that all these cost figures refer to present materials, construction and energy costs, and in future materials and energy inputs are likely to be considerably more expensive than they are now. Given the way all inputs into production involve energy it would not be possible to estimate the total effect on solar thermal plant cost that might be brought about by significant increase in energy costs.

c

Dish costs.

It is not possible to estimate Big Dish costs confidently. Sargent and Lundy do not discuss dishes. Luzzi (2000) estimates that the cost of a Big Dish would be $440,000 but in future could fall to one-third of this figure. Luzzi does not provide derivation or support for the prediction, which is at variance with the 50% fall anticipated for overseas-built solar thermal plant in more recent estimates, and the 35% fall for Australian-built plant. (Hearps and McConnell, 2010). This suggests that even ignoring inflation between 2000 and 2012, the future cost of a 50kW(p) Big Dish might be in the region of $277,000, or $5,500/kW.

To this the cost of the ammonia system would have to be added. It would seem that on cost as well as output grounds central receivers will be preferable to Big Dishes.

Central receiver costs.

Unfortunately estimates of present and future central receiver costs vary and do not enable confident conclusions. Often it is not made clear what amount of storage is assumed, whether dry cooling costs are assumed, whether embodied energy costs have been deducted, or to what future date the estimate applies.

Following are varied cost estimates indicating the complexity of the issue, before focusing on the JNREL estimates to be used below.

Sargent and Lundy (2003) state a cost of around $(US2003)9,090/kW(p) for central receivers but expect this to fall to $3,220/kW(p)3,591 by 2020, in $(US2003), which corresponds to $(A2010)6,0726/kW(p),162, taking into account the 2003 exchange rate and inflation since then. Jacobson and Delucci (2011) quote an IEA estimate of $(US)3,082/kW(p) for 2030 costs. Considerably higher current cost figures are given by Viebahn, Kronshage and Trieb, (2004), the NEEDS study (2008),

Nicholson and Lang (2010), and Hinkley et al. (2010). Solar Paces (undated) does not expect a fall in capital cost between 2010 and 2030. The NREL (2010, 2011) SAM package states a theoretically derived $(US2010)6,578/kW(p), for a plant constructed today. The ACIL Tasman (2010) estimate for near term future Australian cost is $5,827, although it does not seem that this includes the dollar cost and energy losses associated with dry cooling. The review of cost estimates by Hearps and McConnell (2011) shows that the average fall between 2010 and 2030 anticipated for US and European systems is about 50%, and 35% for Australia. Hinkley at al. (2010) state present estimates for Australia of $6,494/kW for 3 hour storage, and of $8,066 for 9 hour storage, assuming wet cooling in both cases. The significantly higher cost for the longer storage is a concern, given that a major future contribution by solar thermal will have to assume c. 17 hour storage ( and much more if lengthy cloudy periods are to be coped with; see below.) Their relatively near term future cost figure is $5,675/kW.

The approach to be taken here will be based on the figures for the three example central receiver cases given in the NREL SAM package (2010,2011), i.e., an approximate $6,580/kW. Because the collection fields are approximately 1 million square metres plant cost per square metre is c. $658. A 50% fall will be assumed for future capital costs and therefore $325/m² will be taken for plant constructed in the US and Europe. Given the net winter flow of 22 W/m² derived above, this corresponds to $14,773/kW delivered at distance and net of embodied and transmission energy costs. Following Hearps and McConnell, (2010) the Australian cost would be 30% higher, i.e., $19,200/kW.

????you should take S and L 3220 for troughs long term??

Cost. S nand L $9,090 to $3591 in 2020.

Cr conclusions

Some other issues.

The above figure is for a central receiver with only 6 hour storage and in future 17-18 hour storage will have to become standard if solar thermal sources are to play a major role in maintaining 24 hour supply. The NREL cost breakdown figures indicate that this would increase the plant cost by 16%, i.e., from $658/m² to $757/m², but a smaller and therefore cheaper power block would be required, because the captured energy could be delivered at a lower rate over the longer period. These factors have not been taken into account in the budget worked out below.

However if solar thermal plants are to play a major balancing role in an electricity supply system containingwith much solar and wind capacity, then advantage could not be taken of a major cost saving enabled for solar thermal systems. The ability to store heat from peak mid day collection and to use it to generate at a much lower constant rate, perhaps 20% of peak capacity, means that much smaller and cheaper generators can be used. However if at times the solar thermal component of a renewable supply system is to be called upon to plug gaps left by intermittent wind and sun, then there will be times when it must generate at closer to its peak collection rate and therefore turbines would have to be large and more costly.

Another issue is the need to wash reflectors frequently and the resulting water, vehicle and energy demand, given that solar thermal plant is intended for use in desert areas. Hayden (2004, p. 189) reports that SEGS reflectors are washed every five days, and subject to high pressure washing every 21 days. A dish system capable of delivering 1000 MW in winter might involve washing some 40+6 million square metres of collection area. This might involve 470,000 km of travel p.a. for special purpose vehicles carrying water tanks. Washing 400 square metre big dishes would seem to be more problematic than washing 5 to 10 metre wide troughs.

A related issue concerns the amount of water needed for cooling the turbines. Solar thermal systems are most likely to be located in desert regions. According to one estimate (Solar Paces, undated, 5-43) the turbines of the equivalent of a 1000 MW solar thermal plant would use 18.5 billion litres p.a. The USGS (2010) states that electricity generation actually accounts for half of total US water use, more than agriculture. The most efficient cooling is by evaporation, meaning that the water cannot be condensed and reused. In some situations sea water can be used but not in Central Australia, nor in North Africa because cloud occurrence increases with proximity to the sea. Air cooling is feasible, but at an energy penalty variously stated as 7 – 10% of output for troughs.

A supply system in the form of troughs capable of meeting demand in winter would produce far more energy in summer than was needed, probably four times as much in view of the above summer/winter ratios noted above, and would have to dump much of it. Some of the excess would go into compensating for the lower wind capacity in summer, and some functions such as cement and fertilizer production might be carried out only in summer but the scope for activities of this kind would be limited, and capital costs of plant idle except in summer would be high. Some processes, such as electric furnace production, are not suited to operating intermitten

Exploring a global renewable energy budget.

Trainer (2010am, 2012) explores an approach to the estimation of the potential of renewable energy sources to meet future world energy demand. The following derivation is a simplified application of that approach. The assumptions and derivation are transparent enabling reworking with different values if that is thought appropriate.

By 2050 world primary energy demand is likely to be in the region of 1000 EJ/y, and final energy demand in 2050 is likely to be 700 EJ/y (Moriarty and Honnery, 2009, p. 31, IPCC, 2011.) Let us assume that electricity remains at the rich world c. 25% of final demand, transport remains 33%, but that 60% of transport energy (i.e., 20% of final energy) can be provided via electricity. This would mean that 45% of all final energy would be electricity and thus 315 EJ/y of electricity would be required. (For simplicity possible reductions in demand achieved by conservation and efficiency gains will be ignored here.)

Lenzen’s review of renewable energy technologies (2009, p. 19) reported that due to the problems set by intermittency wind is not likely to be able to provide much more than 20% of electricity demand. The figure for PV is probably somewhat higher and 25% will be assumed here. Let us assume for the sake of simplicity that solar thermal systems are to provide the remaining 55% of the 315 EJ/y electricity demand, i.e., 173 EJ/y. Their supply task over a mid-winter month would be 14.4 EJ.

To meet this demand in winter via central receivers delivering at distance 22 W/m², i.e., 59 M1.8J/m²/month, 244 billion square metres of collection field would be needed, and at a future cost of $325/m² the cost would be $79.3 trillion, or $3.2 trillion p.a. (This is assuming a 25 year plant lifetime. ACIL Tasman, 2010, assume a 30 year lifetime. A lifetime of 20 years is assumed by the IEA, 2010.) This investment sum

is over 5% of global GDP, which is around 10 times the ratio for all energy investment (as distinct from expenditure, incl. purchases) to world GDP in the early 2000s. (Birol, 2003, IEA, 2010, 3Pfuger, 2004.)

Pfuger states that the energy investment/GDP ratio in rich countries is c. 40% higher than the world figure. AEMO concludes that Australian solar thermal capital costs will fall 35% by 2030, not 50%. Combining these figures indicates that the investment required to provide the foregoing proportion of electricity from solar thermal sources through a winter month in Australia would be more than 18 times the early 2000s ratio of energy investment to GDP in developed countries. (Australia’s energy investment is higher than .7% of GDP but most of this goes into maintaining export industry infrastructure. When this is separated out, the proportion going into meeting domestic demand is around the rich country average. ABS, 2010.)

Note that these are estimates of the capital cost of providing via solar thermal plant providing only 55% of the 45% of total energy required in electrical form, i.e., 25% of total energy required. Also to be included in a thorough budget for a total renewable supply system would be a) the capital costs of the wind and PV components capable of supplying the other 30% of total energy (which would be needed in electrical form, i.e., 210 EJ/y, which is 3.5 times the quantity of electricity presently generated in the world), b) the capital cost of providing the 55% of total energy not in electrical form, c) the cost of 17 hour storage, whereas only 6 hour storage is assumed in the figures in the NREL example cases, d) the cost of the long distance transmission lines and e) the redundant plant needed for backup when wind and solar resources are low (see below.)

Why is the multiple so large? Several factors multiply their effects. The anticipated future capital cost per peak kW of central receivers is about 3 times that of coal-fired power stations, but on average the delivery rate of a central receiver is about half its nominal or peak rate, winter output would on average be around .7 of annual average output, and in general central receivers must be located at long distance from consumers and therefore would involve significantly higher transmission costs in energy and dollars. These three factors multiply to 10+.

A thorough analysis would include assumptions regarding the reduction in demand that energy conservation and saving effort might make in coming decades, and probable future contributions from hydroelectricity and other minor renewable sources. However the magnitude of the values derived above indicates that plausible assumptions would not significantly alter the general picture sketched. Also to be taken into account would be O and M costs, approximately 25 – 33% of lifetime capital cost according to Harvey, 2011 and IPCC, 2011.

It seems clear that unless the assumptions and derivations involved in this exercise are grossly mistaken then in terms of quantity and capital cost considerations based on average demand a system meeting world energy demand in winter from renewable sources in which solar thermal played the major role would impose impossibly high capital investment requirements. Yet when variability and intermittency are taken into account even higher costs become evident.

If the efficiency of the ammonia path is not affected by the reduced DNI in winter as trough, dish-Stirling and dish-steam systems are, then the task for solar thermal above would require 350 million dishes, not 494 and their cost would be 5 times present world annual total energy investment, not 7 times.

The magnitude of the task might be reduced by assuming maximum conversion of the economy to electricity, thereby minimising the use of hydrogen. The lack of detailed data on the uses, temperatures and forms of energy (noted by Ayres, 2009, p. 96) makes it difficult to estimate how many functions could be converted.

The intermittency and redundancy problems.

For simplicity the above exercise assumed that both winter demand and the available level of DNI are both at constant average levels. These are not valid assumptions. Firstly DNI varies significantly around the winter monthly average. At the best Australian sites the long term average DNI in winter is around 5.7 kWh/m²/d but in particular months it can average 40% below this value, i.e., 3.42 kWh/m²/d. (ASRDHB 2006, RREDC undated, Hagen and Kaneff 1991, NASA 2010.) This means that on many particular days in such a month DNI would be considerably lower than this figure.

Secondly provision must be made for peak demand, which can be 30% above average demand. Australia’s electricity consumption averages 29 GW but the capacity of the plant that has been built to ensure that peaks etc., can be coped with is 51 GW, some 75% greater. (ABS, 2011.) Therefore the fundamental question for solar thermal systems is what capacity would be needed to enable demand to be met when it peaks and the solar resource is at a minimum. The above figures suggest that the answer could be more than twice as much capacity as would be needed to meet average winter demand. (In addition this multiple does not take into account the markedly lower solar to electricity efficiency that would be associated with minimum winter DNI, noted above.)

However the biggest problem set by intermittency concerns protracted periods of calm and cloudy weather, which can set in over a continent for a week or more. (

There is considerable documentation of the occurrence of long periods of negligible wind and sun across the whole European continent, lasting for several days. For instance graphs from Oswald et al., (2008) show the magnitude of the problem experienced in February 2006 regarding wind energy availability over the whole of Ireland, UK and Germany for the first 300 hours of 2006. This was mid-winter, the best time of the year for wind energy. For half of this time there was almost no wind input in any of these countries, with capacity factors averaging around 6%. For about 120 continuous hours UK capacity averaged about 3%. During this period UK electricity demand reached its peak high for the year, at a point in time when wind input was zero. Note the tendency for periods of minimal renewable energy availability to coincide with periods of peak demand. (For similar documentation see Coelingh, 1999, Soder et al., 2007, Sharman, 2005, Eon Netz, 2004, Davenport, undated, ASRDHB Table 7, Kaneff, 1991, Ttable XV-A, Mackay, 2008, p. 189, and for Australia, Lawson, 2011, Davey and Coppin, 2003, and Elliston, Kay, Diesendorf and MacGill, 2012. NASA climate data for North Africa similarly indicate considerable cloud cover in winter.)

In such periods a wholly renewable electricity supply system would need to have sufficient back up solar thermal, hydroelectric or biomass plant to substitute possibly entirely for wind and PV input. Clearly this would involve the very large scale provision of redundant plant. In regions such as Australia hydroelectric sources could only make a minor contribution. In many regions biomass might be the best back up option, given that it will probably be available in significant quantity for ethanol production and it is storable.

Reference to the magnitude of these intermittency and redundancy problems for solar thermal systems is appropriate here. For instance, data from the US dish site at Daggett (Davenport, undated) shows that the 10 lowest days in a December of the reported year averaged only 2.45 kWh/m²/d with a total of only 5 hours over 700 W/m². For February the average for the 9 lowest days was 2.1 kWh/m²/d with only 4 hours over 700 W/m² in these 9 days. In December there was one sequence of 5 days of very low DNI and in January there was one of 4 days and another of 5 days, separated by 2 days. In February there was a 4 day run in which there was a total of only 4 hours over 700 W/m². Note again that at 700 W/m² dish-Stirling output falls to 50% of peak output.

The DNI data reported by Davenport for a year at Phoenix Arizona are even less favourable than for Daggett. In January the 13 lowest days had an average 2.35 kWh/m² radiation and these days included only 5 hours over 700 W/m². At the Mod 2 site over a 19 day period there was dish output on only 2 days, totalling 25 kWh, less than 2% of the level that peak output would have been for that period.

Australian climate data aligns with the above data from the U.S. NASA radiation data shows 21% cloud cover for central Australia in July. At Alice Springs each of the three winter months averages 5 to 8 “cloudy” days and only 17.1 “clear” days. The ASRDHB (2006) provides tables on the probability of sequences of cloudy days at Australian sites. (Table 7, for each location.) At Alice Springs the probability of a 5, 7 or 9 day run in which average daily global radiation in winter is under 4.86 kWh/m²/d is 100% in all cases. (DNI data is not given but other tables show that DNI is around 15% lower than global.) There is a 90% chance of a 4 day run averaging under 3.75 kWh/m², and in each of the 4 winter months there is a 25% chance of a 4 day run averaging under 3.75 kWh/m²/d. Even on a 4.86 kWh/m² (global) day DNI would rarely reach 700 W/m². There is a 50% chance in June that there will be a 5 day run under 4.1 kWh/m²/day of global radiation; i.e., one will occur every two years, and there is a 50% chance that there will be a 7 day run under 4.1 kWh/m²/day. There is a 100% chance that in June there will be a sequence of 14 days in which global radiation is under 5.5 kWh/m² day. This means DNI would be under 4.8 kWh/m²/d, i.e., under 85% of the 5.7 kWh/m²/d winter average for central Australia.

To summarise, in a typical winter in the best solar thermal regions in Australia it is virtually certain that there will be one 4 day period and several shorter periods in which it is highly likely that there would be negligible or no generation of electricity. On almost half of these days DNI would barely reach 700 W/m². Thus a solar thermal system capable of maintaining supply with high reliability would seem to need at least four day storage capacity.

At present this is not a serious concern for solar thermal researchers and developers given that summer and annual average output reaches commercially viable levels. However it is crucial for the discussion of the viability of a totally renewable energy supply, which must be able to meet demand in winter and which would have to depend heavily on solar thermal sources.

The storage issue.

The seriousness of these variability and intermittency problems depends on the potential of solar thermal heat energy storage. Some enthusiasts have claimed that this can maintain supply though lengthy calm and cloudy periods, not only keeping output from solar thermal systems up to normal/average levels, but also filling the gaps left by wind and PV systems.

Some solar thermal systems currently operating have the capacity to store for up to 7.5 hours. The standard provision in future is expected to be 17 hour storage. However if electricity from a solar thermal plant was to be despatched from stored heat for 4 cloudy days, i.e.,.96 hours, the storage capacity would have to be some 133 times the maximum presently being built. The NREL SAM figures indicate that 6 hour storage constitutes about 8% of plant cost or $50 million, suggesting that a 96 hour storage capacity would add the cost of another solar thermal plant.

These implications to do with the problem of maintaining output from a single solar thermal plant would seem to clearly rule out the possibility of the solar thermal sector’s combined storage capacity meeting total electricity system demand through several days when there is little input from wind and PV sectors. That would require sufficient solar thermal plant to meet c. 100% of demand, all equipped with at least 4 day storage capacity.

Thus levelised cost is misleading.

Discussions of the viability of renewable energy technologies typically focus on their levelised costs. These can be highly misleading because they fail to take into account the above implications of variability and intermittency for required redundant plant. Consider for instance a global 2050 scenario in which wind is to provide 25% of 120 EJ/y of electricity, i.e., 920 GW, or 201 million GWh over 25 years. At the commonly assumed wind energy levelised cost of c. 2 cents/kWh (Booras, 2010) the turbines would cost $4 trillion. However this overlooks the fact that sometimes demand will peak at 1.3+ times average demand, and, far more importantly, the fact that sometimes there will be negligible or no wind within the system’s boundaries. If solar thermal plant was to back up wind, and the capital cost per kW of solar thermal electricity produced was $12,000/kW delivered, then the wind back up plant required to cope with a peak in demand would cost {(920 GW x 1.3)x($12,000/kW} = $14.4 trillion, i.e., almost 5 times as much as a cost based on wind LCOE would suggest. If as Lenzen (2009) argues the cost of back up capacity should be accounted to the technology in question then the wind sector in this example would cost far more than 2 cents/kWh.

This is only a crude indicative calculation and the figure arrived at would be higher if it included the energy losses due to more distant transmission for solar thermal, embodied energy and the storage costs to enable constant supply, all of which would be significantly higher for solar thermal than wind. Biomass electricity generation would be a cheaper back up, but the average estimate for potential global biomass primary energy is 250 EJ/y (IPCC, 2011) and most of this (challengeable) amount would be required as a major source for transport fuel.

This exercise shows that the appropriate approach to whole system cost analysis is that detailed in Trainer 2010a and 2012 whereby the focus is on the capital cost of the quantities of redundant plant required to maintain supply in view of the fact that at times some components will not be able to meet their quota and must be backed up by extra capacity of some other components.

Conclusions.

Because of the inaccessiunavailability of basic performance data this analysis has not been able to come to precise or confident conclusions. However the evidence accessed suggests that although solar thermal systems will be valuable contributors they will not be able to make a large contribution in winter to meeting predicted demand levels in winter, let alone to solve the total system problem set by the variability of other renewable sources.

The most promising option would seem to be using Big Dishes with an ammonia storage capacity. The cost of sufficient collection and generation capacity to deliver 1000 MW at distance, ignoring many relevant factors including the cost of the ammonia processing plant, would seem to be around $(A)18 billion. The few and uncertain figures available indicate that providing storage capacity to maintain output over four cloudy days might add e1 – 3 billion per plant.

This discussion aligns with previous attempts to assess the potential and the limits of renewable energy sources. (Trainer, 2007, 2010c, 2012.) These have not been arguments against transition to full dependence on renewable energy sources. They have been contributions to the general case that energy-intensive societies cannot be run on these sources. The only options left would seem to be to seek to enable continued pursuit of affluence and growth via nuclear energy, or to embrace some kind of ”Simpler Way” involving dramatic reductions in rich world per capita resource and energy demand, and a zero-growth economy in which there is a high level of localism, and the acceptance of non-affluent lifestyles. Such a transition would be of unprecedented proportions, it is not being considered in current policy discussions, and it is quite unlikely to be made. That this Simpler Way vision is workable and attractive is argued in Trainer 2010b, and Trainer 2011.at At present the failure to consider such a path derives largely from the common belief that renewable energy sources will eliminate any need to take it seriously.

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Governments. Sandringham.

The cosine problem.

Another uncertain reducing factor concerns the difference between summer and winter average angle between sun, reflectors and absorber. In winter troughs suffer marked effects due the geometry of their alignment with the sun throughout the day, causing the quite low performance of troughs in winter. As the sun travels across the sky in summer its angle with the (N-S) axis of the trough is close to 90 degrees all day, at a good location, but in winter it is around 60 degrees, meaning that a square metre of collector receives half as much (cos 60) solar energy as the DNI value per square metre. Dishes can be pointed directly at the sun all day in summer and winter, and they have only slight curvature, meaning that this “cosine loss” is much less.

With central receivers the situation is more subtle and difficult to estimate. Radesovich (1988) states the average cosine loss for a central receiver as 21%. A central receiver field resembles a fresnel arrangement of a dish but an inefficiency is created by the fact that when the sun is at a low angle to the horizon the high absorber is not at a point analogous to the focal point of a parabolic dish. All central receivers built to data have been small compared with the standard 220 MW unit assumed for the future, and this cosine problem is considerably more acute when the field is large and the height of the tower is low relative to its radius. For a 2+ km radius field and a 280 metre high tower in winter the angle between the sun, reflector and absorber is low to very low for all the mirrors on the sun’s side of the tower. At Mildura in winter one would have to go almost a kilometre south of the tower to find a reflector normal to the sun, even at midday. For almost all the reflectors north of this one the angle between sun, reflector and absorber would be low to very low. The result is that the average angle between sun, reflector and absorber in summer when the sun is higher in the sky all day is somewhat greater than in winter when it is lower all day. Note again that this is true of midday and in winter mornings and afternoons the sun is even lower above the horizon and most angles are bigger. (NASA tables show that for Algeria the average hourly angle of the sun above the horizon in summer is 46 degrees but in winter only 27 degrees.) Tables 3 – 6 from Alpert and Kolb (1988) sets out the differences and it is evident that when the angle goes from 90 degrees to 15 degrees the output of the field can fall by one-third.

My crude graphical estimation of reflector angles, weighted by numbers of reflectors at various positions in the field, indicates that given winter angles the energy received at the absorber would be 73% of the value for the summer angles (i.e., assuming the same DNI in each case.) This roughly corresponds to the above figure from Radosevich, i.e., a 21% average loss due to the cosine effect. But note that this is for mid day and at other times of the day the sun is lower and the average angle would be worse.

The little evidence to hand on the winter/summer ratio for Central Receivers reports some surprisingly large and confusing differences, and it is disappointing that a clear and confident conclusion is not possible on this crucial issue. The cosine factor is probably the main contributor to the difference. Radosevich (Table 4 - 3) shows that daily solar – electricity conversion in summer was a surprising 4 to 9 times as great as in winter. Over the three years in which NREL experimented with a 10 MW pilot plant the ratio of mid-summer to mid-winter monthly gross output was 4.2/1, 7.6/1 and 7.2/1. The ratios for net output were up to 25% lower (i.e., 10/1 in one year). (Alpert and Kolb, 1988,Table 5 - 1, p. 59.) (Attempts to determine by personal correspondence whether these ratios were misleading or generally valid indicators, have not been successful. Similarly it has not been possible to get confirmation that the SAM data has taken this factor into account or assumes the same cosine effect in summer and winter.)

Some light can be thrown on these ratios by Fig. 4 –1, p. 43 from Alpert and Kolb showing daily output in relation to DNI. For the Solar 1 device, DNI had to reach almost 875 W/m2 before any power was generated, indicating that output is not proportional to DNI but increases rapidly only after a relatively high value is achieved. In other words, in winter the lower DNI results in disproportionately lower electrical output. Alpert and Kolb report marked reduction in efficiency with low DNI (c. p. 21.)

It is noteworthy that in one of these receiver cases given in NREL’s SAM package (2010) a 36% fall in DNI is accompanied by a 58% fall in net energy produced, again testifying to a significantly falling solar-to electricity efficiency with falling DNI, and supporting the conclusion that the above simple derivation of a 40 W/m2 winter flow from the basic 220 MW central receiver characteristics could be too high.

Other Central Receiver issues.