The phenomenal drop in the cost of solar panels, which has exceeded an incredible 99 percent since the 1970s, has enabled the mass adoption of photovoltaic systems worldwide. These systems, which convert sunlight directly into electrical energy, have become a key pillar of the global energy transition. However, behind this impressive price reduction is not just a single revolutionary innovation, but a complex network of technical advancements stemming from diverse research efforts and industrial sectors, as revealed by new research from the Massachusetts Institute of Technology (MIT).

This detailed study, which delves deep into the specific innovations that have enabled such a drastic cost reduction, provides valuable insights. Its conclusions can help companies in the renewable energy sector make more effective decisions about research and development investments, while serving as a guide for policymakers to identify priority areas for stimulation to accelerate the growth of production and implementation of solar technologies.

A Complex Network of Knowledge and Innovation

The modeling conducted by the researchers clearly shows that key innovations often originated outside the solar sector itself. This includes advances in semiconductor manufacturing, metallurgy, glass production, oil and gas drilling processes, construction methods, and even legal frameworks. Professor Jessika Trancik from MIT's Institute for Data, Systems, and Society, the senior author of the study, emphasizes the complexity of the cost improvement process. According to her, scientific and engineering progress, often at a very fundamental level, lies at the heart of these cost reductions. A vast amount of knowledge has been drawn from various domains and industries, and it is this network of knowledge that has enabled the improvement of these technologies.

In the paper, published in the journal PLOS ONE, Trancik was joined by co-authors Goksin Kavlak, a former IDSS graduate student and postdoctoral fellow, now a senior associate in energy at The Brattle Group; Magdalena Klemun, also a former IDSS graduate student and postdoctoral fellow, now an assistant professor at Johns Hopkins University; former MIT postdoctoral fellow Ajinkya Kamat; and Brittany Smith and Robert Margolis from the National Renewable Energy Laboratory (NREL).

Identifying Key Innovations

This research builds upon mathematical models previously developed by the researchers, which allowed for the separation of the effects of engineering technologies on the costs of photovoltaic (PV) modules and systems. The goal of this study was to delve even deeper into the scientific advances that led to cost reductions. They combined their quantitative cost model with a detailed, qualitative analysis of the innovations that influenced the costs of PV system materials, manufacturing steps, and implementation processes.

Goksin Kavlak explains that their quantitative cost model guided the qualitative analysis, allowing them to closely examine innovations in areas that are difficult to measure due to a lack of quantitative data. Building on earlier work that identified key cost drivers—such as the number of solar cells per module, wiring efficiency, and silicon wafer area—the researchers conducted a structured literature search for innovations that could affect these drivers. They then grouped these innovations to identify patterns, revealing clusters that reduced costs by improving materials or prefabricating components to simplify manufacturing and installation. Finally, the team tracked the industrial origin and timing of each innovation and consulted with domain experts to focus on the most significant innovations.

In total, they identified 81 unique innovations that have impacted the cost of PV systems since 1970, from improvements in anti-reflective glass to the implementation of fully online permitting interfaces. Trancik notes that with innovations, one can always go to a deeper level, down to the techniques of processing raw materials, so it was challenging to know when to stop. The quantitative model greatly helped in grounding the qualitative analysis.

Modules and "Soft" Costs: Two Faces of Solar Systems

The researchers decided to separate the costs of PV modules from the so-called Balance-of-System (BOS) costs, which cover things like mounting systems, inverters, and wiring. PV modules, which are interconnected to form solar panels, are mass-produced and can be exported, while many BOS components are designed, built, and sold locally. Kavlak explains that by examining innovations at the BOS level and within the modules, they identified different types of innovations that emerged in these two parts of PV technology.

BOS costs are more dependent on "soft technologies"—non-physical elements like permitting procedures, which have contributed significantly less to the cost improvement of PV so far compared to hardware innovations. Trancik points out that it often comes down to delays. Time is money, and delays on construction sites and unpredictable processes affect these balance-of-system costs. Innovations like automated permitting software, which flags code-compliant systems for expedited approval, show promise. Although not yet quantified in this study, the team's framework could support future analysis of their economic impact and similar innovations that streamline implementation processes.

For example, in Croatia and other European Union countries, the process of obtaining permits for solar power plants has often been lengthy and bureaucratic. The introduction of digital platforms for submitting applications, standardization of documentation, and acceleration of administrative procedures are key to reducing these "soft" costs. Such changes not only reduce financial expenses but also shorten the time required to complete projects, which is extremely important for investors and end-users.

Interconnected Industries and Knowledge Transfer

The researchers found that innovations from the semiconductor, electronics, metallurgy, and oil industries played a major role in reducing the costs of both PV and BOS. However, BOS costs were also influenced by innovations in software engineering and electrical power engineering. Non-innovation factors, such as efficiency gains from bulk purchasing and knowledge accumulation in the solar energy industry, also reduced some cost variables.

Furthermore, while most innovations in PV panels originated from research organizations or industry, many BOS innovations were developed by city governments, U.S. states, or professional associations. Trancik expressed surprise at the diversity of all these fields and their close interconnectedness, and the fact that this network is clearly visible through this analysis. Klemun adds that PV was very well-positioned to absorb innovations from other industries—thanks to the right timing, physical compatibility, and supportive policies for adapting innovations for PV applications.

This knowledge transfer, known as "knowledge spillovers," is crucial for rapid progress. For example, precision machining and automation techniques developed for microchip manufacturing in the semiconductor industry were directly applied to the production of silicon wafers for solar cells, enabling thinner, more efficient, and cheaper cells. Similarly, advances in metallurgy led to the development of new alloys for solar panel frames and mounts, which are lighter, more durable, and more resistant to corrosion, reducing transportation and installation costs. Innovations in glass manufacturing, such as the development of low-iron glass and anti-reflective coatings, significantly improved light transmission and reduced losses, thereby increasing the overall efficiency of the panels.

The Digital Revolution and the Future of Solar Technologies

The analysis also reveals the role that greater computing power can play in reducing BOS costs through advances like automated engineering review systems and remote site assessment software. Klemun points out that, in terms of knowledge transfer, what we have seen in PV so far may be just the beginning, indicating the growing role of robotics and AI-powered digital tools in driving future cost reductions and quality improvements.

Artificial intelligence (AI) is already transforming the solar industry. AI algorithms can optimize the design of solar farms, predict energy production based on weather conditions and historical data, and manage energy distribution in the grid. Robots are increasingly being used for automated module assembly, field installation, and even for cleaning and maintenance of solar panels, reducing the need for human labor and increasing safety. Digital twins—virtual replicas of physical solar power plants—allow for real-time performance monitoring, fault prediction, and operational optimization, further reducing operational costs.

In addition to the qualitative analysis, the researchers showed how this methodology can be used to assess the quantitative impact of a specific innovation if numerical data are available to plug into the cost equation. For example, using information on material prices and manufacturing processes, they estimate that wire sawing, a technique introduced in the 1980s, led to a total PV system cost reduction of $5 per watt by reducing silicon losses and increasing throughput during production. This technique allowed for cutting silicon ingots into much thinner wafers with less waste, which directly impacted the cost reduction per watt.

Lessons for the Future and Broader Application

Trancik emphasizes that through this retrospective analysis, something valuable is learned for future strategy because one can see what worked and what didn't, and the models can also be applied prospectively. It is also useful to know which adjacent sectors can help support the improvement of a particular technology. In the future, the researchers plan to apply this methodology to a wide range of technologies, including other renewable energy systems like wind turbines, geothermal systems, and energy storage systems. They also want to further study "soft technologies" to identify innovations or processes that could accelerate cost reductions.

Although the process of technological innovation may seem like a "black box," the researchers have shown that it can be studied like any other phenomenon. Understanding the complex interactions between different industries, scientific disciplines, and regulatory frameworks is key to further progress in the development and implementation of clean energy technologies. This study from MIT provides a powerful framework for analyzing past successes and guiding future efforts, ensuring that the path toward a sustainable energy future is as efficient and cost-effective as possible.