Understanding China’s involvement in South Africa’s Renewable Energy Sector

China is Africa’s largest trading partner, providing demand for the continent’s energy and minerals, and its direct investments in the continent are also on the rise. When Chinese Premier Li Keqiang visited the African Union in 2014, he announced that China would raise its direct investment in the continent to $100 billion by 2020, mostly in infrastructure development.

Solar panels and telephones in Qunu in the Eastern Cape. South Africa. Creative Commons photo: Trevor Samson / World Bank.

Solar panels and telephones in Qunu in the Eastern Cape. South Africa. Creative Commons photo: Trevor Samson / World Bank.

While Chinese companies have been involved in Africa’s energy industry for years, particularly in hydro-electricity and fossil fuel extraction, the rise of China’s involvement in the continent’s renewable energy sector is relatively recent and an area ripe for further research.

New research, which aims to better understand China’s investment in South Africa’s renewable energy sector, will help provide some answers. Lucy Baker, from the Science Policy Research Unit at the University of Sussex and Wei Shen, from the Institute of Development Studies, have received a fellowship to better understand the drivers and obstacles to the expansion of Chinese renewable energy activities in South Africa.

There has been growing Chinese involvement in the wind and solar PV industries under South Africa’s renewable energy independent power producers’ procurement programme (RE IPPPP), a competitive bidding system for renewable energy generation by independent power producers. The research will focus on how Chinese companies and investors are involved in South Africa’s renewable energy, including their engagement in project development, investment, technology supply and manufacturing.

The research will also consider implications for Chinese involvement in emerging renewable energy development elsewhere in the region and for other middle-income economies with a significant renewable energy programme under development, such as Argentina, India and Brazil.

Their findings will be shared as a policy brief to be published by SAIS-CARI. The SAIS-CARI Fellowship they have been awarded allows researchers, policy-makers, or journalists to do field research on an under-explored policy issue related to China’s African engagement.

 

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Financing Innovation in Renewable Energy

Global new investment in green energy technologies hit $329 billion in 2015 say Bloomberg New Energy Finance. That’s a good thing right? Well, not necessarily. Knowledge is always partial, and despite impressive breadth of data gathering, some fundamentals remain unclear. That’s where Mariana Mazzucato and Gregor Semieniuk came in, organising a special workshop on Financing Innovation in Renewable Energy hosted by Bloomberg NEF which asked, who is doing what, where and when?

The answers offered at the workshop, or occasionally the lack of them, pose serious research and policy challenges.

Gregor Semieniuk leading a discussion on who is financing renewable energy at the conference hosted by BloombergNEF.

Gregor Semieniuk from the University of Sussex,  leads a discussion on who is financing renewable energy at the workshop. Image by Pelin Demirel.

First, with regard to the data itself: what goes into the data, what does not, and who are the data collectors? As researchers and analysts we cannot always get the numbers and stakes that underlie investment deals. Sometimes this is cultural, as some countries are reluctant to disclose data. This means trends in the categories of investment, especially with organisations like the China Development Bank, are very hard to get at.

Second, what does the data already collated tell us about the financing of green energy in 2016? We know we have an issue following on from Basel III, a set of banking regulations which aimed to bring about more stability within the banking sector. Long-term, patient capital is now more difficult to raise. We see this in other sectors, such as green technology. The venture capitalists too have shorter exit windows.

So what does this do for the renewable energy industry? And do these two factors mean the development banks have to take a bigger role? If so, how is the public market creation agenda going to emerge to let this happen?

In terms of finance, renewable technologies have two important characteristics. They are highly sensitive to the cost of capital and are highly sensitive to policy. The former suggests that the European interest rate regime of the last few years was a perfect opportunity to deliver growth. The latter tells us it’s a “perfectly missed opportunity”.

The UK is an exemplar here. The coalition government most definitely did not fix the renewables roof while the sun was shining. Not only has this situation regressed under the current incumbents, it looks like they’ve knocked down the walls of the house to boot. Furthermore, despite the headline figures, it would seem from some of the discussion at the workshop, green energy finance is in less than robust health. According to a senior executive at one large financial player, utilities are walking wounded, commercial banks are in trouble, public funding is locked within the vault of austerity, and markets are our only hope. In other words, the pension funds and ‘yield-cos’, companies formed to own operating assets that produce a predictable cash flow, and other institutional investors looking for long-term yields are key potential investors in renewable energy.

Yet, these funds are significantly under-invested in green energy. Only 1-3% of pension fund assets are invested directly in infrastructure, and here lies an opportunity. But these investors are not motivated, and it’s up to renewables boosters to transform their assets into a suitably attractive product.

Here then is the substantive issue of the day. How is the direction of development in the green energy sector set, and what role does finance have in this? This issue was addressed by Gregor Semieniuk at the workshop who reminded us that:

  1. A) Finance is not neutral. Who finances what may impact direction and pace of renewable scale-up.
  2. B) But we don’t know much about sources or destination of finance, and
  3. C) The biggest part, asset finance, is just a “green bar” and we never know about who is financing it.

Much emphasis has been on how public policies effect finance flows, but the actors are not distinguished between public and private, or institutional types. We’re simply unsure about what their motivations for investing are. This brings us to directionality, and à la Andy Stirling’s 2007 contribution, the appropriate question follows: why do some energy infrastructures get funded and some do not?

To date, both investors and civil society advocates of renewables have explicitly privileged speed of scale-up over alternative considerations, such as distribution of benefits. Yet as lead renewable technologies such as onshore wind and solar PV gain cost of production parity with fossil production, we have some serious choices to make about whether there is a role for public market creation, how it is financed and how costs and benefits are distributed.

In other words, it may be time to reframe the policy prescriptions to move beyond addressing merely urgency and scale. The alternative course of action discussed in the previous paragraph sees the promotion of renewables as a type of game playing, wrapping assets up in attractive packages for institutional investors. And we have evidence from the great crash of 2008 that the financialisation of fixed assets – in that case people’s homes – does not always end well.

Bring together a large enough cohort of researchers, and a workshop will always produce more questions than answers. This was no different and a number of future challenges were substantiated. There is a significant challenge of governance levels. Can we afford to apply only national policy to global issues? Solar PV and wind in particular are now global industries with global value chains. So, how should a country like the UK identify where to make interventions? For example, if you are ‘UK PLC’, should interventions be made only at home, or also abroad? This is both a policy and research challenge.

We might also usefully ask what the mechanisms are by which flows of finance enter countries, particular developing countries. For example India’s Prime Minister Narendra Modi’s alliance of industry and 120 nations investing in solar energy made waves at COP21. It was a big deal, but how will the finance on this work? Conversely, we might ask, who benefits from a feed-in tariff introduced in Germany, the UK or Ireland, and where are they? This question gets to the heart of directionality issues. Who makes the decisions, where are they located, and what is the distribution of costs and benefits?

Cian O’Donovan is a Research Fellow and co-ordinator of the Nexus Network at the Science Policy Research Unit (SPRU). He tweets at twitter.com/cian

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Storm Imogen reminds us that there are winners and losers with climate change

AFTER Storm Imogen, is it not time more people faced up to the reality that man-made climate change is causing huge changes to weather patterns which are affecting us?

One storm does not equal climate change, neither does one hot summer. The point is that unusual weather events are becoming more frequent – THAT’S climate change. Imogen was the ninth named storm to hit the UK this winter. Before Imogen, we had the likes of Frank and Gertrude battering the country. 2015 was the hottest year since records began – the average surface temperature of the planet was 0.87°C warmer than the official baseline.

Waves crashing against the breakwater at Brighton Marina.

Waves crashing against the breakwater at Brighton Marina. Photo credit: Hehaden/flickr Creative commons.

This isn’t just a blip; global temperatures have been on an upward trend for years and 2011-2015 was the hottest five-year period on record. The weather is getting weird compared to what we’re used to. This isn’t happening by chance, it’s not ‘Nature’s way’. There’s a lot of folk working on climate science around the world and the vast majority agree that climate change is caused by human activity.

This unusual weather – increasing temperatures, storms, droughts – is down to us. The knock on effects of this weird weather – melting ice caps, flooding, damage to health and property – that’s down to us as well. Why? Because we’re changing the planet’s atmosphere. Over the last century, a by-product of various human activities has been the release of carbon dioxide and other so-called greenhouse gases. These gases block energy from leaving the atmosphere, warming the planet.

The main culprit is fossil fuels. When we burn them, we release carbon dioxide. Deforestation is important too because trees store carbon. When we chop them down we lose this storage capacity, releasing carbon dioxide into the atmosphere. There are other greenhouse gases too such as methane. This is released from the livestock we keep as part of their digestion process.

It’s not all bad, however. The impacts of climate change are many and diverse. Whilst some people lose out, others may benefit from lower heating bills in winter for example. Carbon dioxide helps plants grow which brings opportunities to harvest more crops in some parts of the world. But the more this carries on – the more greenhouse gases we pump into the atmosphere – the more these impacts become increasingly negative. The bad outweighs the good.

It’s difficult to be precise about exactly how bad things might get in monetary terms. Climate science and climate economics are not the same thing. There are fewer people working on the economics of climate change and they often don’t look at all possible climate impacts. Current best guesses suggest that we will lose out on between 1 – 10 years of economic growth in the 21st Century because of climate change.

Although much of this is difficult to predict, we do know that there will be both winners and losers. People in less developed countries are and will continue to suffer most because of climate change and have the least means to do anything about it.

Like any sentient species, humans are intrinsically motivated to try and make themselves comfortable, to acquire food, to keep warm. And so we should. We need to survive and, if possible, we’d like to thrive. But we’ll need to increasingly meet our needs in ways that don’t backfire and end up hurting us.

There’s increasing public and political will behind tackling greenhouse gas emissions. One way of achieving this is through renewable energy like wind and solar. But large-scale technical and social changes aren’t easy. We’re locked in to a fossil fuel based economy, which is protected by powerful interests that hold back the growth of renewables.

Another way to cut emissions is to increase energy efficiency. But this isn’t as straightforward as it first appears. For example, if your new car is cheaper to run because it uses fuel more efficiently, you might decide to use it more. This is called the rebound effect and it’s the focus of my current work.

But, there are always challenges with any major change and we need to remember that progress is being made. We now get around a quarter of our electricity from renewables in the UK and best-guess estimates for the rebound effect do not suggest it is large enough to warrant abandoning energy efficiency efforts.

Overall, the weather really is changing and the more it changes as time goes on, the more we can expect the impacts it causes to be increasingly bad for more and more people. Further moves towards carbon-neutral renewable energy sources has the potential to re-engage communities by involving them in the production of energy. And energy efficiency improvements save people money. More of an emphasis on these and other benefits of change is a good way forward.

This was first published in The Argus on February 13th.

Find out more about the ‘direct rebound effect’ associated with personal car travel in Great Britain – read this blog for an overview or read the full research paper in Energy Economics.

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Why we need to rethink the financial future of oil

Andreas Goldthau, Central European University and Benjamin Sovacool, University of Sussex

The price of oil keeps moving in one direction – down. Even political tension between Iran and Saudi Arabia (historically a cause of price rises) has not stopped the drop. It may come as a surprise to some, but it drives home the point that it is not politics but market fundamentals that set prices.

The global marketplace is awash with crude, thanks in part to US shale, Russia pumping at its limits, OPEC countries incapable of agreeing to a cap on production, Saudi Arabia remaining in a fierce price war with US shale producers, and Iranian stocks entering the market. Industry stocks are as high as almost ever before.

Demand also remains sluggish in emerging regions such as Asia. Wall Street augurs even see additional downward potential, suggesting US$20 as a likely floor price – which is remarkable given that from 2010-14 US$100 oil was the “new normal”. In short, the market environment is soft, which is why oil futures traders are not paying heed to the hostilities between Iran and Saudi Arabia.

Oil giant BP reacted by shedding 4,000 jobs, while globally some US$1.5 trillion of energy investment has been put into question. Clearly, oil assets are on the losing side and the future does not bode well for global oil. This, however, is for reasons related to climate change, not because of tumbling prices. Two actors are key: the US government and financial investors.

Oil prices 2011-2015.

Shale squeeze

In the US, it is particularly the “independents” that have become squeezed. These are small to mid-sized companies which form the backbone of the recent shale gas revolution. So far, they have shown a remarkable ability to cope with an oil price spiralling downward, thanks to their innovative nature and their ability to cut costs and streamline production processes. Now, they have hit their limits. While some unconventional oil wells on the Barnett, Eagle Ford or Bakken formations still break even at US$30 a barrel, many no longer do, leaving the independents in the red.

The US government’s decarbonisation strategy, meanwhile, has a strong incentive to keep these independents alive and well. By and large it relies on replacing coal with gas, in addition to tougher power plant regulation. This strategy so far has worked thanks to lots of additional gas coming online as a byproduct of oil production, keeping the market oversupplied and gas cheap. A faltering shale oil industry therefore also questions whether a US climate policy that relies on “market signals” remains sustainable.

One of many shale oilfields in the US.
Reuters/Lucy Nicholson

If the events of 1998, when low oil prices brought the US oil industry to its knees (and Russia went bust), are any good predictor, Washington will keep the industry from collapsing – so long as the independents are needed to help bridge America’s pathway into an unfolding low-carbon energy economy.

Tipping point

The finance industry, in turn, shows signs of a serious rethink in its fossil fuel investment strategy. To be sure, Wall Street and the City of London have valued oil – the world’s most actively traded commodity – as an investment opportunity. It is not only bankers who put their money into oil assets, but also managers of more conservative outfits such as pension funds, Ivy League university endowments and insurance companies.

Yet, doubts are emerging over whether oil remains as attractive as it has been in the past. Already in 2013, Citibank, a global financial firm, declared that global oil demand was “approaching a tipping point” and that “the end is nigh” for growth. It cited the trends of substituting natural gas for oil, coupled with improvements in the fuel economy of vehicles, as the reasons.

Moreover, as the Paris climate deal of December 2015 underlines, there are significant social and environmental costs stemming from unabated climate change. The 196 world parties to COP21 acknowledged that humanity must therefore manage its remaining “carbon budget”. This means that it needs to limit, and eventually end, the use of fossil fuels, including oil.

Fossil fuels are reaching their limits.
Reuters/Stephane Mahe

As a consequence, many barrels of oil will need to stay in the ground as “stranded assets”. The volumes of oil that “cannot be used” by 2035 due to carbon restraints are projected at 500 billion to 600 billion barrels – roughly a third of today’s proven reserves. Some studies suggest that up to 80% of coal, oil and gas reserves held by stock market listed companies cannot be burnt and should be written off.

Reacting on this, the global insurance companies Allianz and Axa already announced an end to investing in coal. Oil is likely to follow. With the global divestment movement gaining further traction, there will be additional impetus from civil society to abandon oil. This is why some observers have already called on established international oil companies “to sell their existing oil reserves as quickly as possible”.

Ultimately, the future politics of oil present a fundamental and inescapable paradox. As ironic as it is, it is the very same climate change imperatives that are helping to stabilise America’s oil industry in the short run while sounding its death knell in the long term. Going short on oil therefore makes both climatic and financial sense.

The Conversation

Andreas Goldthau, Professor, CEU School of Public Policy, Central European University and Benjamin Sovacool, Professor of Energy Policy, University of Sussex

This article was originally published on The Conversation. Read the original article.

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How good is your model? Quantifying quality research

Lee STapleton

a photograph of Lee StapletonOur latest EPSRC-funded research carried out in CIED (and led by SPRU, Sussex) has something new to say about the testing of statistical models. Available now in the journal Energy Economics and authored by Lee Stapleton, Steve Sorrell and Tim Schwanen, you can access the paper here

The paper estimates the so-called ‘direct rebound effect’ associated with personal car travel in Great Britain. This effect relates to the increased driving that may occur when fuel efficiency improvements make car travel cheaper. Our results suggest that the direct rebound effect has been in the region of 20% in GB over the last 40 years. Put differently, a 1% fall in average fuel prices over this period leads to a 0.2% increase in total distance travelled.

To arrive at this conclusion we developed and estimated a total of 108 different regression models. Some of these models were quite fancy, some were quite simple and together they produced a range of parameter estimates in terms of rebound and other determinants of distance travelled. So, how did we choose between them?

To do this, we quantified the robustness (strength or quality) of each model in terms of the extent to which it adhered to governing rules and assumptions about structure, stability, parsimony and the behaviour of parameter estimates and non-fitted data (residuals).   Unfortunately, most applied research which uses these kinds of models pays insufficient attention to these rules and assumptions – many of which are well-documented in textbooks and routinely covered in courses on research methods. So why are they so often ignored? Other assumptions and rules are confined to the more technical, specialist literature which makes it easier to understand their limited diffusion in applied research.

Capturing multi-dimensional concepts such as robustness can be achieved by constructing so-called composite indicators. In other words, uni-dimensional constituents of robustness can be combined mathematically into weighted, aggregated, multi-dimensional representations of the concept. And that’s what we did. Specifically, we assessed 96 of our 108 models in terms of 13 ‘quality indicators’ to create aggregate, composite measures of robustness for each model. We took two approaches based on different weightings. The first (unequally weighted) is based on our judgement of the ‘relative importance’ of each robustness constituent. The second (equally weighted) does not differentiate in terms of importance.  We assessed the remaining 12 models in terms of a reduced set of 6 quality indicators because the robustness of these models was trickier to assess. Here, again, we developed unequally and equally weighted robustness composites.

Doing this allowed us to explore the relationship between model robustness and parameter estimates. We haven’t seen this done before. Previously, this has only been approached using relatively narrow operationalisations of robustness compared to the multi-dimensional indicators developed and used here.

So, the $64,000 question is Do bad methods lead to biased results? And conversely Do good methods lead to less biased results? We can provide answers using our robustness indicators. If there are systematic relationships between parameter estimates and robustness we should be concerned that bad methods do indeed lead to ‘wrong’ answers. But, if there is no relationship between parameter estimates and robustness we can afford to be less concerned about these bad methods.

In our latest work here, we found some evidence to suggest that bad methods lead to biased results, but only some. It depends on which model parameter estimates you look at. More studies need to be done which apply comparable robustness indicators to other models to get a better handle on this. Regardless of the answer, it is a good idea to choose and use statistical models which are multi-dimensionally robust. Hence, we are currently applying the indicators developed in this work to models being developed in other projects.

Lee Stapleton is a Research Fellow at the Science Policy Research Unit and the Tyndall Centre for Climate Change Research.  Working principally in the EPSRC-funded Centre on Innovation and Energy Demand (CIED) within the Sussex Energy Group, Lee’s research focusses on the application of time-series (static, dynamic and co-integrating) regression models to estimate so-called ‘rebound effects’ in the transport sector. 

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