Bioenergy Predictions & Expectations

To achieve the 2 °C goal of the Paris Agreement, fossil fuels need to be phased out and replaced by low-carbon sources of energy. This requires the nearly complete de-carbonization of the power sector by 2050, and an accelerated shift towards electricity as a final energy carrier.

The Intergovernmental Panel on Climate Change (IPCC) comprehensively evaluated mitigation pathways to stay within an atmospheric concentration of 430–480 ppm CO2 — roughly corresponding to the 2 °C target, and studied the specific contribution of renewable energy (RE) to mitigation.

Surprisingly, solar energy emerges only as a minor mitigation option in most modeling studies.

For example, a scenario comparison study that fed into the Intergovernmental Panel on Climate Change projected a global solar electricity generation of 8–35 EJ per year in 2050 (25th–75th percentile) for 2 °C consistent mitigation scenarios, corresponding to a ~5–17% contribution to electricity supply.

In contrast, the same study projects biomass-based secondary energy production of 50–90 EJ per year in 2050.

Reasons why the underlying models prefer bioenergy include its higher versatility, making it more broadly applicable throughout the existing energy system, and the possibility of generating negative emissions from bioenergy by combining it with carbon capture and storage.

However, sustainable biomass sourcing and the underlying land requirements are estimated to limit primary bioenergy production to between 100–300 EJ per year in 2050 (that is, secondary energy production of 50–150 EJ), whereas the technical potential for solar energy is many times that of bioenergy and exceeds total projected global energy demand in mid-century.

Recent market developments point to rapid take up of solar energy in both established and emerging markets. That raises the question of why solar energy is only marginally represented in energy system futures so far.

We scrutinize historical scenarios and find that solar energy has so far been systematically underestimated in global energy and mitigation scenarios compared to actual deployment. We investigate the reasons for this underestimation.

Policy Support

Demand grew disruptively after the introduction of feed-in tariffs (FiTs) and other technology support schemes that were not represented in global models.

After decades in which solar PV was mostly adopted for space and off-grid applications in remote areas, policies targeted at supporting renewable energies were put into place accelerating PV deployment, especially since 1998.

The take-off was supported by high public acceptance and valuing non-monetized attributes; PV adopters show a willingness to-pay of US$0.02–0.04 per kWh above traditional energy sources, a premium of about 20%, and higher than for other renewables.

In Germany the FiT triggered a 400-fold growth between 2000 and 2016 (41 GW in 2016, generating about 6.5% of all electricity). Crucial for enabling the rapid growth was that the FiT guaranteed remuneration for a period of 20 years in combination with streamlined permitting procedures; hence, PV was understood as a long-term, low-risk investment.

This led to an influx of private capital from home-owners and small interest groups.

At the end of 2012, 48% of the installed PV capacity was owned by citizens (private persons or farmers), a higher rate than for any other modern power technology, whereas only 3.5% was owned by utility companies, and the remaining capacity by companies, project developers, banks and investment funds.

Similar developments followed in other countries, such as Spain, Italy, Japan and China, after the introduction of FiT schemes, while in the USA an investment tax credit supports PV installations. In 2015 China took over as the largest PV market with a generous FiT focusing heavily on utility scale.

Steep Technological Learning

Technological learning — the positive feedback between cost reductions and capacity — has been a central characteristic of PV’s growth. Module costs have decreased by 22.5% with each doubling of installed capacity, well above the median of learning rates of other technologies.

This combination of rapid learning with faster-than-expected capacity development has thus led to lower-than-expected costs. Levelized costs of residential-scale PV are now at or below the price of retail grid electricity in several countries; in Germany, even systems with battery storage are expected to soon be below grid prices.

Utility-scale PV is also now competitive with wholesale prices in favourable locations. Large PV projects in Dubai, Mexico and Chile are selling power at less than US$0.03 per kWh without subsidies, and at US$0.06 per kWh in Rajasthan, India and Zambia, out-competing conventional energy sources in those more capital constrained locations.

The cost reductions are likely to continue, driven by numerous factors.

Increased module efficiencies and performance ratios (that is, the ratio of actual to theoretically expected energy output) lower all system costs that scale with system area (for example, mounting and labour); plausible developments include a switch to back contact, passivated selective contact silicon solar cell technology in the short term, and tandem solar cells featuring considerably higher thermodynamic efficiency limits in the long term, as well as further improvements in module technology.

Other factors include: reduced material consumption and a switch to cheaper materials, for example, replacing silver contacts by copper; higher inverter efficiency at lower cost; increased system lifetime; economies of scale reducing production costs for system components as well as installation costs in utility-scale installations; reduced balance of system (BOS), as well as soft-costs for planning and permitting in maturing markets; and new business models reducing financing costs.

Cost increases of Competing Technologies

Models were overly optimistic in their assumptions about the costs, potentials, and acceptance of competing low-carbon technologies, such as carbon capture and storage (CCS) and nuclear power. From an energy system perspective this implied a more pessimistic outlook for PV.

In summary, RE support policies, public support, rapid technological learning, and under performing technological competitors explain the more rapid development of PV compared to model projections in the past. But a different set of challenges is perceived as critical for the future development of PV, understood as limiting factor in future projections.