How Next-Gen AI Data Centers Are Optimizing Power Efficiency with SiC
Rapid growth AI and cloud computing is straining data center power systems. To meet increasing demands, 400V DC rack distribution is emerging as a more efficient and scalable solution. However, this transition comes with challenges, including safety concerns, thermal management and standardization. Silicon Carbide (SiC) semiconductors provide a powerful solution to make them a key component in modern data center power architectures.
The exponential growth of artificial intelligence (AI) workloads is reshaping the landscape of data center power infrastructure. As AI models become more complex and compute-intensive, the demand for highly efficient, scalable and reliable power solutions is at an all-time high. Traditional AC power distribution methods, with their multiple conversion stages and inherent inefficiencies, are struggling to keep pace with these new demands.
To address this, data centers are exploring the integration of both high-efficiency AC and 400V DC rack power distribution by leveraging mSiC™ technology to optimize power conversion, reduce energy losses and enhance overall system reliability. However, transitioning to a more efficient DC-based system introduces new challenges, including thermal management and standardization hurdles.
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Figure 1: Traditional AC rack power distribution architecture
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Figure 2: OCP ORv3 high-power AC rack power distribution architecture with 48V Battery Backup Units (BBUs) and power shelf
The Evolution of AC Power in Data Centers
AC power remains the dominant method of power distribution in data centers due to existing infrastructure and standardization. (Figure 1) However, as AI workloads drive unprecedented energy consumption, the inefficiencies of AC power systems become increasingly evident. Multiple conversion stages—from the grid to UPS systems, PDUs and server power supplies—result in significant energy losses. Transitioning to an OCP Open Rack v3 (ORv3) high-power AC rack power distribution architecture (Figure 2) reduces conversion losses, eliminates inefficient UPS/PDU infrastructure, improves power density and enhances scalability—critical factors for the growing demands of AI and high-performance computing (HPC) workloads.
Additionally, integrating renewable energy sources further complicates AC-based power systems, as DC-based storage solutions require additional conversion steps to interface with AC infrastructure. This highlights the need for a more streamlined power distribution strategy. Despite these challenges, advancements in Silicon Carbide (SiC) power devices are enabling significant improvements in AC-DC conversion efficiency.
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Figure 3: SiC-based OCP ORv3 high-power AC rack power distribution architecture further reduces conversion losses
The integration of SiC devices in an OCP ORv3 architecture (Figure 3) significantly enhances efficiency, power density and thermal performance. SiC-based rectifiers and power conversion modules operate at higher switching frequencies with lower conduction and switching losses compared to traditional silicon-based devices. This results in improved power conversion efficiency—often exceeding 98%—which is critical in reducing energy waste and cooling requirements in high-power AI and HPC workloads.
Additionally, SiC devices enable compact, lightweight power modules due to reduced heat dissipation and smaller passive components, allowing for higher power density in rectifier bays. This is particularly beneficial in ORv3’s 48V DC architecture, where lower distribution losses and improved thermal management directly translate into increased rack-level reliability and performance.
SiC’s ability to handle high voltages and operate efficiently at elevated temperatures further strengthens power infrastructure robustness, reducing failure rates and maintenance costs. As AI data centers push for greater power efficiency and sustainability, SiC technology plays a pivotal role in maximizing performance while minimizing operational expenses.
The Limits of AC Optimization and the Need for a More Efficient Power Solution
While ORv3 and SiC-based power conversion improve AC power distribution efficiency, they do not eliminate the fundamental inefficiencies of multiple conversion stages. Solid-state transformers (SST) have been proposed as an alternative to traditional medium-voltage (MV) transformers, leveraging highly efficient 3.3 kV SiC MOSFETs and diodes. However, this approach primarily replaces the MV transformer without addressing the inherent conversion losses that persist throughout the AC distribution chain.
As AI workloads continue to scale, data centers must explore more efficient power architectures beyond traditional AC distribution. High-voltage DC (HVDC) and hybrid AC-DC architectures present compelling alternatives, offering reduced conversion losses, improved integration with renewable energy sources and enhanced overall efficiency. The transition toward these architectures, enabled by SiC and other emerging technologies, may be critical in meeting the power demands of next-generation AI data centers while achieving long-term sustainability and operational cost reductions.
The Future of Data Center Power Architectures
Data centers are increasingly adopting 400V DC rack power distribution as an alternative to traditional AC systems, driven by the need for improved efficiency, reliability and cost-effectiveness. This shift is largely facilitated by advanced SiC technology, which offers superior electrical properties when compared to traditional silicon-based components. These advantages result in more efficient power delivery, reduced cooling requirements and lower operational costs.
At the most fundamental level, a 400V DC system reduces the number of power conversion stages, minimizing energy losses and improving overall efficiency. It also provides more stable and reliable power, reducing the risk of power quality issues that can affect sensitive data center equipment. The higher power density of 400V DC allows more power to be delivered with smaller conductors, optimizing space usage and simplifying the power architecture by reducing the need for complex rectification and inversion stages. This enhances reliability and facilitates seamless integration with renewable energy sources like solar PV and batteries, which naturally produce DC power.
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Figure 4: SiC-based 400V DC rack power distribution architecture
However, implementing 400V DC rack power distribution (Figure 4) presents its own engineering challenges. Traditional AC distribution cabling and installation costs are high, but integrating 400V DC can significantly reduce these costs compared to 48V DC, freeing up space and simplifying infrastructure. Deploying 400V DC as the main power distribution allows for flexible conversion to 48V DC or AC as needed, consolidating site backup onto a single power bus. Modular 400V DC power systems enable scalable capacity expansion while simplifying the power chain architecture, reducing unnecessary AC-DC conversions and improving overall power chain efficiency.
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Figure 5: Microchip mSiC™ MOSFET devices in various packages
SiC plays a significant role in enhancing the efficiency of both AC and DC data center power systems. SiC devices offer higher efficiency, superior thermal conductivity, enhanced voltage and current handling and greater durability, making them ideal for high-power-density AI data center environments versus silicon-based devices. SiC power components cut switching and conduction losses, boosting system efficiency. In AC-DC conversion, SiC rectifiers and power factor correction (PFC) circuits improve efficiency, while in Uninterruptible Power Supplies (UPS), they enable higher-frequency operation, reducing transformer and inductor size and weight. SiC-based inverters enhance power quality with lower harmonics and reduced filtering needs and their high-temperature operation lessens cooling demands, further optimizing energy efficiency.
SiC-based power electronics can be integrated into several critical areas within a 400V DC AI data center power architecture. Efficient DC-DC converters using SiC enable precise voltage regulation from 400V DC to the lower voltage rails required by AI accelerators. Server power supplies benefit from SiC rectifiers and PFC circuits, contributing to overall energy savings. Battery energy storage solutions (BESS) in AI data centers see improved charge/discharge efficiency and system reliability with SiC technology. Additionally, UPS incorporating SiC-based inverters and converters enhance performance and response times, crucial for ensuring high availability in AI workloads. By strategically deploying SiC-based components, AI data centers can optimize efficiency, power density and system reliability.
The Path to Optimized Power Architecture
As AI workloads continue to drive up data center power demands, both AC and 400V DC rack power distribution present compelling solutions for improving efficiency and scalability. While AC infrastructure remains dominant, its inefficiencies are becoming more apparent, particularly in high-power-density AI data centers. The integration of 400V DC rack power distribution offers a streamlined, energy-efficient alternative, reducing conversion losses and enabling seamless renewable energy integration. SiC semiconductors play a crucial role in enhancing the efficiency of both AC and DC power conversion systems, offering higher efficiency, better thermal performance and increased reliability. By leveraging SiC technology, AI data centers can achieve greater power density and efficiency, paving the way for the next generation of high-performance computing infrastructures.
For those looking to take advantage of Silicon Carbide’s benefits in AI data centers, explore high-efficiency mSiC products and solutions, designed to optimize power distribution and enhance energy efficiency. To gain deeper insights into SiC's role in transforming data center power efficiency, we invite you to listen to episode 18 of our Beyond the Microchip podcast, where industry experts further discuss the impact of Silicon Carbide on data center energy performance.