Can plastic solar cells deliver?

The promise of polymer solar cells is that they will be cheap enough and produced on a large enough scale to transform our energy economy, unlocking the sun’s potential to meet all our energy needs in a sustainable way. But there’s a long way to go from a device in a laboratory, or even a company’s demonstrator product, to an economically viable product that can be made at scale. How big is that gap, are there insuperable obstacles standing in the way, and if not, how long might it take us to get there? Some answers to these questions are now beginning to emerge, and I’m cautiously optimistic. Although most attention is focused on efficiency, the biggest outstanding technical issue is to prolong the lifetime of the solar cells. But before plastic solar cells can be introduced on a mass scale, it’s going to be necessary to find a substitute for indium tin oxide as a transparent electrode. But if we can do this, the way is open for a real transformation of our energy system.

The obstacles are both technical and economic – but of course it doesn’t make sense to consider these separately, since it is technical improvements that will make the economics look better. A recent study starts to break down the likely costs and identify where we need to find improvements. The paper – Economic assessment of solar electricity production from organic-based photovoltaic modules in a domestic environment, by Brian Azzopardi, from Manchester University, with coworkers from Imperial College, Cartagena, and Riso (Energy and Environmental Science 4 p3741, 2011) – breaks down an estimate of the cost of power generated by a polymer photovoltaic fabricated on a plastic substrate by a manufacturing process already at the prototype stage. This process uses the most common combination of materials – the polymer P3HT together with the fullerene derivative PCBM. The so-called “levelised power cost” – i.e. the cost per unit of electricity, including all capital costs, averaged over the lifetime of the plant, comes in between €0.19 and €0.50 per kWh for 7% efficient solar cells with a lifetime of 5 years, assuming southern European sunshine. This is, of course, too expensive both compared to alternatives like fossil fuel or nuclear energy, and to conventional solar cells, though the gap with conventional solar isn’t massive. But the technology is still immature, so what improvements in performance and reductions in cost is it reasonable to expect?

The two key technical parameters are efficiency and lifetime. Most research effort so far has concentrated on improving efficiencies – values greater than 4% are now routine for the P3HT/PCBM system; a newer system, involving a different fullerene derivative, PC70BM blended with the polymer PCDTBT (I find even the acronym difficult to remember, but for the record the full name is poly[9’-hepta-decanyl-2,7- carbazole-alt-5,5-(4’,7’-di-2-thienyl-2’,1’,3’-benzothiadiazole)]), achieves efficiencies greater than 6%. These values will improve, through further tweaking of the materials and processes. Azzopardi’s analysis suggests that efficiencies in the range 7-10% may already be looking viable… as long as the cells last long enough. This is potentially a problem – it’s been understood for a while that the lifetime of polymer solar cells may well prove to be their undoing. The active materials in polymer solar cells – conjugated polymer semiconductors – are essentially overgrown dyes, and we all know that dyes tend to bleach in the sun. Five years seems to be a minimum lifetime to make this a viable technology, but up to now many laboratory devices have struggled to last more than a few days. Another recent paper, however, gives grounds for more optimism. This paper – High Efficiency Polymer Solar Cells with Long Operating Lifetimes, Advanced Energy Materials 1 p491, 2011), from the Stanford group of Michael McGehee – demonstrates a PCDTBT/PC70BM solar cell with a lifetime of nearly seven years. This doesn’t mean all our problems are solved, though – this device was encapsulated in glass, rather than printed on a flexible plastic sheet. Glass is much better than plastics at keeping harmful oxygen away from the active materials; to reproduce this lifetime in an all-plastic device will need more work to improve the oxygen barrier properties of the module.

How does the cost of a plastic solar cell break down, and what reductions is it realistic to expect? The analysis by Azzopardi and coworkers shows that the cost of the system is dominated by the cost of the modules, and the cost of the modules is dominated by the cost of the materials. The other elements of the system cost will probably continue to decrease anyway, as much of this is shared in common with other types of solar cells. What we don’t know yet is the extent to which the special advantages of plastic solar cells over conventional ones – their lightness and flexibility – can reduce the installation costs. As we’ve been expecting, the cheapness of processing plastic solar cells means that manufacturing costs – including the capital costs of the equipment to make them – are small compared to the cost of materials. The cost of these materials make up 60-80% of the cost of the modules. Part of this is simply the cost of the semiconducting polymers; these will certainly reduce with time as experience grows at making them at scale. But the surprise for me is the importance of the cost of the substrate, or more accurately the cost of the thin, transparent conducting electrode which coats the substrate – this represents up to half of the total cost of materials. This is going to be a real barrier to the large scale uptake of this technology.

The transparent electrode currently used is a thin layer of indium tin oxide – ITO. This is a very widely used material in touch screens and liquid crystal displays, and it currently represents the major use of the metal indium, which is rare and expensive. So unless a replacement for ITO can be found, it’s the cost and availability of this material that’s going to limit the use of plastic solar cells. Transparency and electrical conductivity don’t usually go together, so it’s not straightforward to find a substitute. Carbon nanotubes, and more recently graphene, have been suggested, but currently they’re neither good enough by themselves, nor is there a process to make them cheaply at scale (a good summary of the current contenders can be found in Rational Design of Hybrid Graphene Films for High-Performance Transparent Electrodes by Zhu et al, ACS Nano 5 p6472, 2011). So, to make this technology work, much more effort needs to be put into finding a substitute for ITO.

Energy, carbon, money – floating rates of exchange

When one starts reading about the future of the world’s energy economy, one needs to get used to making conversions amongst a zoo of energy units – exajoules, millions of tons of oil equivalent, quadrillions of british thermal units and the rest. But these conversions are trivial in comparison to a couple of other rates of exchange – the relationship between energy and carbon emissions (using this term as a shorthand for the effect of energy use on the global climate), and the conversion between energy and money.

On the face of it, it’s easy to see the link between emissions and energy. You burn a tonne of coal, you get 29 GJ of energy out and you emit 2.6 tonnes of carbon dioxide. But, if we step back to the level of a national or global economy, the emissions per unit of energy used depend on the form in which the energy is used (directly burning natural gas vs using electricity, for example) and, for the case of electricity, on the mix of generation being used. But if we want an accurate picture of the impact of our energy use on climate change, we need to look at more than just carbon dioxide emissions. CO2 is not the only greenhouse gas; methane, for example, despite being emitted in much smaller quantities than CO2, is still a significant contributor to climate change as it is a considerably more potent greenhouse gas than CO2. So if you’re considering the total contribution to global warming of electricity derived from a gas power station you need to account, not just for the CO2 produced by direct burning, but of the effect of any methane emitted from leaks in the pipes getting to the power station. Likewise, the effect on climate of the high altitude emissions from aircraft is substantially greater than that from the carbon dioxide alone, for example due to the production of high altitude ozone from NOx emissions. All of these factors can be wrapped up by expressing the effect of emissions on the climate through a measure of “mass of carbon dioxide equivalent”. It’s important to take these additional factors into account, or you end up significantly underestimating the climate impact of much energy use, but this accounting embodies more theory and more assumptions.

For a high accessible and readable account of the complexities of assigning carbon footprints to all sorts of goods and activities, I recommend Mike Berners-Lee’s new book How Bad Are Bananas?: The carbon footprint of everything. This has some interesting conclusions – his insistence on full accounting leads to surprisingly high carbon footprints for rice and cheese, for example (as the title hints, he recommends you eat more bananas). But carbon accounting is in its infancy; what’s arguably most important now is money.

At first sight, the conversion between energy and money is completely straightforward; we have well-functioning markets for common energy carriers like oil and gas, and everyone’s electricity bill makes it clear how much we’re paying individually. The problem is that it isn’t enough to know what the cost of energy is now; if you’re deciding whether to build a nuclear power station or to install photovoltaic panels on your roof, to make a rational economic decision you need to know what the price of energy is going to be over a twenty to thirty year timescale, at least (the oldest running nuclear power reactor in the UK was opened in 1968).

The record of forecasting energy prices and demand is frankly dismal. Vaclav Smil devotes a whole chapter of his book Energy at the Crossroads: Global Perspectives and Uncertainties to this problem – the chapter is called, simply, “Against Forecasting”. Here are a few graphs of my own to make the point – these are taken from the US Energy Information Administration‘s predictions of future oil prices.

In 2000 the USA’s Energy Information Agency produced this forecast for oil prices (from the International Energy Outlook 2000):

Historical oil prices up to 2000 in 2008 US dollars, with high, low and reference predictions made by the EIA in 2000

After a decade of relatively stable oil prices (solid black line), the EIA has relatively tight bounds between its high (blue line), low (red line) and reference (green line) predictions. Let’s see how this compared with what happened as the decade unfolded:

High, low and reference predictions for oil prices made by the EIA in 2000, compared with the actual outcome from 2000-2010

The EIA, having been mugged by reality in its 2000 forecasts, seems to have learnt from its experience, if the range of the predictions made in 2010 is anything to go by:

2000 and 2010 oIl price predictions
Successive predictions for future oil prices made by the USA's EIA in 2000 and 2010, compared to the actual outcome up to 2010

This forecast may be more prudent than the 2000 forecast, but with a variation of nearly of factor of four between high and low scenarios, it’s also pretty much completely useless. Conventional wisdom in recent years argues that we should arrange our energy needs through a deregulated market. It’s difficult to see how this can work when the information on the timescale needed to make sensible investment decisions is so poor.