The accelerating growth of renewable energy is one of the most hopeful signs when it comes to addressing climate change. For example, the cost of utility-scale solar photovoltaic energy (solar PV) fell by 77% from 2010 to 2018. It may come as a surprise that renewable energy does not grow faster, sooner, or larger in En-ROADS, but the model reflects the dynamics of the system. Here we explore three main points to help you understand this.
En-ROADS is consistent with other models in both baseline and low-emissions scenarios.
Several dynamics slow the growth of renewables, most importantly slow capital stock turnover.
You can explore higher renewable growth scenarios in En-ROADS.
1. En-ROADS is consistent with other models in both baseline and low-emissions scenarios.
Both the En-ROADS baseline scenario (Business as Usual) and high growth scenarios for renewables are consistent with the results of other simulations in the academic and business literature. To demonstrate this, we compare En-ROADS scenarios for renewable primary energy demand with similar scenarios from other models.
First, let’s examine the baseline scenario. The graph below compares the En-ROADS Business-as-Usual (baseline) scenario to baseline scenarios from eight different models, including the International Energy Agency’s (IEA) Current Policies Scenario in its World Energy Outlook (WEO) report in 2018, and Shell’s Mountains scenario, as well as six major Integrated Assessment Models (IAMs) (Riahi et al., 2017; Rogelj et al., 2018; Gidden et al., 2019).
For the IAMs, the baseline scenarios shown in the graph below are SSP2, a “middle of the road” scenario in which major economic, social, and political trends do not change much from their historical trajectories. (To learn more about Shared Socioeconomic Pathways (SSPs), this article by Carbon Brief is helpful).
The En-ROADS baseline scenario (the blue line below) for primary energy demand from renewables aligns with or is slightly higher than these other models. It is consistent with the IEA’s 2040 forecast, it falls at the high end of the spread of the 2050 forecasts, and it falls at the high end of the spread of the 2100 forecasts, except for PIK REMIND-MAGPIE (which is well above the others).
Now let’s examine scenarios that imagine higher rates of growth for renewables. The graph below compares a low-emissions scenario in En-ROADS to low-emissions scenarios from eight different models, including the IEA WEO New Policies Scenario, the IEA WEO Sustainable Development Scenario, Shell’s Sky scenario, and six major Integrated Assessment Models (versions of SSP2 2.6). This En-ROADS low emissions scenario includes a renewables subsidy of -$0.07/kWh that begins in 2020 and a hypothetical breakthrough in energy storage technology in 2030 that reduces the supply cost of storage by 50%.
This En-ROADS low emissions scenario (the blue line below) for primary energy demand from renewables is higher than the IEA New Policies and SDS scenarios and the Integrated Assessment Models scenarios. It aligns with the Shell Sky scenario.
The En-ROADS Business-as-Usual scenario for renewable use is at the high end of the span of scenarios created by the IAMs for the SSPs. The graph below compares primary energy demand from renewables in En-ROADS to the same six Integrated Assessment Models (PBL IMAGE, PNNL GCAM4, PIK REMIND-MAGPIE, NIES AIM/CGE, IIASA MESSAGE-GLOBIOM, and EIEE WITCH-GLOBIOM). In this graph, the baseline scenarios from each of the five standardized Shared Socioeconomic Pathways (SSPs) are shown. The light-colored solid lines represent the IAMs, while the dashed lines represent En-ROADS. The solid blue line represents the En-ROADS default Business-as-Usual scenario.
2. Several dynamics slow the growth of renewables, most importantly slow capital stock turnover.
Slow capital stock turnover: New energy sources (e.g., renewables and new technology) take decades (not years) to scale up to sufficiently compete with coal, oil, and gas. New supply capacity doesn’t show up until old, long-lived capacity is retired (e.g., coal-fired power plants and oil refineries, which can survive for ~30 years). Only 6% of the total stock gets added every year. New zero-carbon energy may secure 20-50% of that market share, but even then, it adds only 1-3% to the total stock. The climate is only helped when coal, oil, and gas is retired away, and in the absence of other interventions, that amount is relatively small – approximately 3% per year.
Other dynamics affecting the growth of renewable energy include:
Large-scale use of renewables requires energy storage: Solar and wind energy is intermittent (the sun doesn’t shine and wind doesn’t blow 24 hours a day), but energy is constantly needed. Excess energy from renewable sources must be stored somehow in order to be used during times of peak demand, or when the energy source isn’t producing energy. Fossil fuels, on the other hand, can be stored in their current form before being burned, and the amount turned into energy can easily be increased or decreased. Therefore, to scale renewable energy up significantly, energy storage needs to be increased.
Large-scale energy storage technologies are still in a research-and-development phase. You can model a decrease in the cost of energy storage in En-ROADS. Open the advanced view of the Renewables slider by clicking the 3 dots, and scroll down to “Storage R&D breakthrough cost reduction” and “Storage breakthrough year.”
So much of the energy system uses fuels instead of electricity: Most of our energy system powers things through directly burning fuels, rather than converting fuels to electricity. Therefore, electrification of transport, buildings, and industry is a necessary step to ensuring that renewable energy can be widely adopted. If the switch is made to electrify things (e.g. installing home electric heating systems rather than gas), then when the renewables are available they can be used.
If you maximize the amount of electrification in transport and buildings & industry like in this scenario and then subsidize renewable energy, you'll see that the renewable energy subsidy makes a larger difference than without electrification.
The rebound effect: In order to grow, renewables are made to be less expensive. The drop in energy prices then boosts demand. You can see this happen in this En-ROADS scenario, where renewables are subsidized and a hypothetical breakthrough reduces the cost of energy storage by 50%. In the Cost of Energy graph on the left, notice how the blue line of this scenario declines as the price of energy drops, while simultaneously in the Final Energy Consumption graph on the right, energy consumption increases, relative to the black line of the baseline scenario.
3. You can explore higher renewable growth scenarios in En-ROADS.
Some analysts, such as Bloomberg New Energy Finance and Rocky Mountain Institute, have suggested the possibility of renewables growing even faster than shown in most models. The IEA, for instance, has historically underestimated the growth of renewables. You can explore scenarios of even faster and higher growth in En-ROADS by changing the following settings:
Renewables R&D breakthrough cost reduction: Click the 3 dots next to the Renewables slider to show the Renewables advanced settings. Scroll down to find the “Renewables R&D breakthrough cost reduction” and “Renewables breakthrough year” sliders. See this scenario in En-ROADS.
Progress ratio for renewables: Click the Simulation drop-down menu at the top of the En-ROADS simulator and select Assumptions, which opens the advanced settings to alter the assumptions built into En-ROADS. Under “Progress ratio” you can alter how fast the cost of renewables falls due to learning, experience, and economies of scale. See this scenario in En-ROADS.
What if we maximize the policies and assumptions in En-ROADS that would lead to faster growth of renewables? Policies such as a carbon price or electrifying transport and buildings & industry boost renewables even more. Here we have created an example En-ROADS scenario with the following settings:
You can use the simulator to explore possibly unrealistic but interesting “what if” questions. The graph below compares this scenario in En-ROADS to SSP1 2.6 scenarios from six Integrated Assessment Models, IEA WEO’s New Policies scenario, IEA WEO SDS, and Shell’s Sky scenario. In this very low emissions scenario, SSP1 is a better scenario comparison than SSP2, which we compared against in the previous graphs. In this case, primary energy demand for renewable energy in En-ROADS (the blue line below) grows to 528 exajoules/year by 2050 and 1270 exajoules/year by 2100, far above any of the scenarios from similar models.