To continue to reduce the costs of solar and other clean energy technologies, scientists and engineers will likely need to focus, at least in part, on improving technological features that are not based on hardware, according to MIT researchers. They describe this discovery and the mechanisms underlying it in Natural energy.
While the cost of installing a solar energy system has fallen more than 99 percent since 1980, this new analysis shows that the characteristics of “soft technologies,” such as codified permitting practices, The supply chain management techniques and system design processes that go into deploying a solar power plant, contributed only 10 to 15 percent of the total cost decline. Improvements to hardware features take the lion’s share.
But as soft technologies increasingly dominate the total installation costs of solar energy systems, this trend threatens to slow future cost savings and hinder the global transition to clean energy, says the lead author of the study, Jessika Trancik, professor at the Institute for Data at MIT. Systems and Society (IDSS).
Trancik’s co-authors include lead author Magdalena M. Klemun, a former IDSS graduate student and postdoctoral fellow who is now an assistant professor at the Hong Kong University of Science and Technology; Goksin Kavlak, a former IDSS graduate student and postdoctoral fellow who is now associated with the Brattle Group; and James McNerney, former IDSS postdoctoral fellow and now senior fellow at the Harvard Kennedy School.
The team created a quantitative model to analyze the cost evolution of solar energy systems, which captures the contributions of hardware technology features and software technology features.
The framework shows that software technology has not improved much over time and that software technology features have contributed even less to overall cost declines than expected.
Their results indicate that to reverse this trend and accelerate the decline in costs, engineers could first consider making solar energy systems less dependent on soft technologies, or alternatively tackle the problem directly by improving the processes of ineffective deployment.
“Understanding where efficiencies and inefficiencies exist, and how to address these inefficiencies, is critical to supporting the clean energy transition. We are investing a huge amount of public dollars in this area, and soft technology will be absolutely essential to generating these funds. matters,” says Trancik.
“However,” adds Klemun, “we haven’t thought as systematically about designing soft technologies as we have for hardware. This needs to change.”
The Hard Truth About Soft Costs
Researchers observed that the “soft costs” of building a solar power plant – the costs of designing and installing the plant – now represent a much larger share of total costs. In fact, the share of soft costs now generally ranges between 35 and 64 percent.
“We wanted to take a closer look at where these soft costs were coming from and why they weren’t decreasing as quickly as hardware costs,” says Trancik.
In the past, scientists have modeled the evolution of solar energy costs by dividing total costs into additive components (material components and non-material components) and then tracking how these components change over time.
“But if you really want to understand where these rates of change are coming from, you need to go deeper to look at technological characteristics. Then things break down differently,” says Trancik.
Researchers developed a quantitative approach that models the evolution of solar energy costs over time by attributing contributions to individual technology features, including hardware features and software technology features.
For example, their framework would determine the extent to which lower system installation costs – a software cost – are due to standardized practices of certified installers – a soft technology feature. This would also help understand how this same indirect cost is affected by the increased efficiency of photovoltaic modules – a hardware technology feature.
With this approach, researchers found that hardware improvements had the greatest impact on reducing the soft costs of solar energy systems. For example, the efficiency of photovoltaic modules doubled between 1980 and 2017, reducing overall system costs by 17%. But about 40% of this overall decline could be attributed to the reduction in soft costs linked to improved module efficiency.
The framework shows that although hardware technology features tend to improve many cost elements, software technology features affect only a few.
“You can see this structural difference even before you collect data on how technologies change over time. “That’s why mapping a technology’s web of cost dependencies is a useful first step in identifying levers for change, for solar PV and for other technologies like well,” notes Klemun.
Static soft technology
The researchers used their model to study multiple countries because ancillary costs can vary widely around the world. For example, the indirect costs of solar energy in Germany are approximately 50% lower than those in the United States.
The fact that hardware technology improvements are often shared globally has led to dramatic declines in costs over the past few decades across all locations, according to the analysis. Soft technological innovations are generally not shared across borders. Additionally, the team found that countries with better performance on soft technologies 20 years ago still perform better today, while those with worse performance have not seen much improvement.
This difference between countries could be due to regulatory and licensing processes, cultural factors, or market dynamics such as how companies interact with each other, Trancik says.
“But not all variables in soft technologies are ones that you would want to change in the direction of reducing costs, such as lowering wages. So there are other considerations, beyond just reducing the cost technology, which we need to think about when interpreting these results,” she says.
Their analysis highlights two strategies for reducing soft costs. On the one hand, scientists could focus on developing hardware improvements that make soft costs more dependent on hard technological variables and less on soft technological variables, for example by creating simpler, more standardized equipment that could reduce the installation time on site.
Researchers could also directly target the functionality of software technologies without modifying the hardware, perhaps by creating more efficient workflows for system installation or automated authorization platforms.
“In practice, engineers often follow both approaches, but separating the two in a formal model makes it easier to target innovation efforts by leveraging specific relationships between technological characteristics and costs,” explains Klemun.
“Often when we think about information processing, we leave aside processes that still take place in a very rudimentary way through communication between people. But it is just as important to think of this as a technology as to design sophisticated software,” notes Trancik.
In the future, she and her collaborators want to apply their quantitative model to study the ancillary costs of other technologies, such as electric vehicle charging and nuclear fission. They also want to better understand the limits of improving soft technology and how to design better soft technology from the start.
This research is funded by the U.S. Department of Energy’s Office of Solar Energy Technologies.