Non-Crystalline Oil-Immersed Transformers: Lifecycle Carbon Study Reveals 99.45% Emissions from Use Phase
A groundbreaking study published in High Voltage Apparatus has quantified the full lifecycle carbon footprint of non-crystalline oil-immersed distribution transformers, revealing that operational use accounts for nearly all emissions—99.45% to be exact. The research, led by Zhang Yibing of State Grid Yingda International Holdings Co., Ltd., in collaboration with experts from State Grid Yingda Carbon Asset Management and Beijing Sino Carbon Innovation & Investment Co., Ltd., offers critical insights into the environmental impact of one of the most essential components in modern power systems.
As global attention intensifies on decarbonizing energy infrastructure, the findings underscore a pivotal truth: while material choices and manufacturing processes matter, the dominant driver of a transformer’s climate impact lies not in its construction but in how it performs over decades of service. This revelation shifts the focus of green design from production-centric thinking to a more holistic, long-term operational efficiency strategy.
The study applied the rigorous framework of Life Cycle Assessment (LCA), adhering to ISO 14067:2018 standards, to trace emissions from “cradle to grave.” The functional unit was a standard 400 kVA, 10/0.4 kV three-phase oil-immersed distribution transformer with a 25-year service life. The model encompassed five distinct phases: raw material acquisition, production, distribution, use, and end-of-life management. By integrating real-world production data from a major Chinese manufacturer with background data from the Ecoinvent database, the researchers constructed a comprehensive inventory of inputs and emissions across the entire supply chain.
The total carbon footprint was calculated at 602,731 kgCO₂e per unit. At first glance, this number may seem staggering, but the distribution of emissions across lifecycle stages tells a more nuanced story. The use phase alone contributed 599,411.72 kgCO₂e—over 99% of the total. This overwhelming dominance stems from the energy losses inherent in transformer operation, particularly no-load and load losses, which translate directly into electricity demand and, consequently, emissions from power generation.
Given China’s current energy mix, which still relies heavily on coal-fired power plants, even small inefficiencies in transformers accumulate into massive carbon outputs over a quarter-century. The study explicitly links the high use-phase footprint to the interplay between transformer design efficiency and regional electricity generation profiles. This dual dependency means that improvements in either domain can significantly reduce lifecycle emissions.
Zhu Chaoyong, a senior engineer at State Grid Yingda and co-author of the study, emphasized that “the operational phase is where the climate battle is won or lost for power equipment.” He added, “Our data shows that even the most sustainable materials and cleanest factories cannot offset the emissions generated by inefficient operation in a carbon-intensive grid.”
The research team did not stop at quantification. They conducted a sensitivity analysis to identify which factors, outside of use-phase electricity consumption, most influence the remaining 0.55% of emissions. This analysis revealed that material recycling—particularly of copper and steel—is the most sensitive parameter. Increasing the recovery rate of these metals at end-of-life not only reduces the need for virgin material extraction but also generates carbon credits that offset upstream emissions.
Among raw materials, amorphous strip (the core material) and polyester-enamelled copper flat wire were identified as the top two contributors to pre-use emissions, accounting for 32.12% and 24.65% respectively of the non-operational footprint. This highlights a critical trade-off: while amorphous metal cores significantly reduce no-load losses during operation, their production is energy-intensive. The study thus calls for a balanced approach—leveraging the efficiency benefits of advanced materials while simultaneously improving their manufacturing sustainability.
Production-phase emissions, though minimal at just 0.06%, were primarily driven by electricity consumption in core and transformer assembly workshops. This points to a clear pathway for manufacturers: transitioning to renewable energy sources for factory operations can further decarbonize the supply chain. Zhu noted that “greening the grid isn’t just about power plants—it’s also about how we power our factories.”
Transportation, often a focal point in consumer product carbon debates, played a negligible role, contributing only 0.08% of total emissions. However, the study found that switching from diesel trucks to electric vehicles for both raw material and finished product transport could cut transport emissions by nearly half. While the absolute impact is small, this shift represents a low-hanging fruit for companies aiming to demonstrate comprehensive environmental stewardship.
One of the most forward-looking aspects of the study is its projection of how changing electricity mixes will affect future transformer footprints. Using data from China’s 2030 Energy and Power Development Plan and 2060 Outlook, the researchers modeled a cleaner grid scenario. Under this forecast, the use-phase carbon footprint could drop by approximately 65.39%, reducing the total lifecycle emissions from over 600,000 kgCO₂e to around 210,000 kgCO₂e per unit.
Even in this cleaner future, the use phase would still dominate, accounting for 98.43% of emissions. This underscores a crucial point: decarbonization of the grid amplifies, rather than diminishes, the importance of transformer efficiency. As generation becomes cleaner, the relative impact of operational losses grows, making high-efficiency designs even more valuable from a climate perspective.
Wu Meichen, an engineer at State Grid Yingda Carbon Asset Management and co-author, explained, “A more efficient transformer in a clean grid delivers exponentially greater carbon savings than the same transformer in a fossil-heavy grid. The value of efficiency compounds as the grid decarbonizes.”
The study also addressed a frequently overlooked but essential aspect of LCA: uncertainty. Using a Taylor series expansion method, the researchers quantified the uncertainty in their results. The geometric standard deviation (GSD) was calculated at 1.064, indicating a 95% confidence interval of approximately ±12.5%. This level of precision is considered low in LCA studies and lends strong credibility to the findings.
The primary source of uncertainty was traced to the carbon footprint factors in the Ecoinvent database, particularly their geographic and technological representativeness for Chinese industrial processes. The authors recommend the development of a China-specific LCA database to further refine such assessments. “Global databases are invaluable, but local data is king when it comes to accurate carbon accounting,” said Tang Jin, the study’s corresponding author and a senior engineer at Sino Carbon Innovation & Investment.
The implications of this research extend beyond transformers. It provides a methodological blueprint for assessing the lifecycle emissions of other power equipment, from switchgear to reactors. More importantly, it challenges the industry to rethink product design and procurement criteria. Traditionally, transformers have been selected based on upfront cost and technical specifications. This study argues for a paradigm shift toward lifecycle cost analysis that includes carbon as a key metric.
For utilities and grid operators, the findings suggest that investing in high-efficiency transformers—even at a higher initial price—can yield substantial long-term environmental and potentially economic returns, especially as carbon pricing mechanisms become more widespread. The study supports policies that incentivize the adoption of amorphous metal and other low-loss technologies.
For manufacturers, the message is clear: innovation must focus on reducing both material intensity and operational losses. This includes exploring alternative core materials, optimizing winding designs, and enhancing cooling systems. It also means designing for disassembly and recyclability, ensuring that valuable metals can be recovered at end-of-life.
The research also has implications for policymakers. As nations strive to meet their Nationally Determined Contributions (NDCs) under the Paris Agreement, attention must be paid not just to generation but to the entire electricity value chain. Standards and regulations could be updated to mandate higher efficiency classes for distribution transformers, similar to energy labeling for appliances.
Furthermore, the study highlights the synergistic relationship between grid modernization and climate goals. Smart grid technologies that optimize load management and reduce idle running time can further minimize transformer losses. Digital monitoring systems can detect inefficiencies early, enabling predictive maintenance and extending equipment life—all of which contribute to lower lifecycle emissions.
Looking ahead, the authors suggest several avenues for future research. One is the integration of dynamic LCA models that account for hourly variations in grid carbon intensity, rather than using annual averages. Another is expanding the system boundary to include installation, maintenance, and decommissioning activities, which were excluded in this study due to data limitations.
Additionally, there is a need to explore the environmental trade-offs of emerging technologies, such as solid-state transformers or those using superconducting materials. While these may offer superior efficiency, their production could involve rare or energy-intensive materials, necessitating a full lifecycle perspective.
The study also opens the door to comparative analyses between different transformer types—dry-type versus oil-immersed, silicon steel versus amorphous metal, conventional versus smart transformers. Such comparisons can help utilities make informed decisions based on comprehensive environmental data.
In the broader context of the energy transition, this research serves as a reminder that decarbonization is not a single-point solution but a systemic challenge. Every component in the power network, no matter how small or seemingly insignificant, contributes to the overall carbon budget. By applying rigorous scientific methods like LCA, the industry can move beyond anecdotal claims and make data-driven decisions that truly advance sustainability.
The work by Zhang, Zhu, Wu, and their colleagues stands as a model of applied environmental science. It combines academic rigor with practical relevance, offering actionable insights for engineers, managers, and policymakers alike. As the world races to net zero, studies like this provide the compass needed to navigate the complex terrain of industrial decarbonization.
In conclusion, the lifecycle carbon footprint of non-crystalline oil-immersed transformers is overwhelmingly determined by their operational phase. However, this does not diminish the importance of upstream and downstream considerations. A truly sustainable transformer is one that is efficient in use, made from low-carbon materials, produced with clean energy, transported sustainably, and fully recyclable at end-of-life. The path to greener power systems lies in optimizing every link in this chain.
Zhang Yibing, Zhu Chaoyong, Wu Meichen, Chen Nan, Li Tongyan, Ma Yalong, Tang Jin. Non-Crystalline Oil-Immersed Transformers: Lifecycle Carbon Study Reveals 99.45% Emissions from Use Phase. High Voltage Apparatus. DOI: 10.13296/j.1001-1609.hva.2024.11.007