Key Component of W2C-1000GW: The Computing Pod (BROAD AI Battery)

Against the backdrop of accelerating global digital economy penetration and the in-depth advancement of the "dual carbon" goals, the W2C-1000GW initiative—focused on the integration of green energy and high-efficiency computing— is leading the transformation direction of the energy and computing industries. As a core component of this ambitious initiative, the Computing Pod (BROAD AI Battery, or BAB for short) features "prefabrication, high energy efficiency, low carbon footprint and smart operation" as its core traits. Leveraging its unique technical architecture and notable comprehensive advantages, it serves as the critical infrastructure supporting W2C-1000GW to achieve the goals of "efficient energy utilization and inclusive computing supply".

Currently, global computing demand is experiencing explosive growth, but traditional data center construction models are plagued by multiple challenges: construction cycles last 2 to 3 years, failing to meet immediate computing needs; Power Usage Effectiveness (PUE) remains stubbornly high, resulting in low energy efficiency that runs counter to the "dual carbon" goals; The increase in single-cabinet power density is hampered by cooling bottlenecks, restricting the release of computing performance; Additionally, there is heavy reliance on grid power, leading to insufficient reliability in areas with unstable power grids or special scenarios. These pain points not only hinder the high-quality development of the computing industry, but also pose challenges to the advancement of the W2C-1000GW initiative. In this context, the BROAD AI Battery Computing Pod has emerged. Its core vision is to create an integrated computing infrastructure solution characterized by "low PUE, low cost, high reliability and value-added potential" through "waste heat recovery + AI intelligent management and control" technologies, providing solid support for the implementation of W2C-1000GW.

As an important component of W2C-1000GW, the core value of the BROAD AI Battery Computing Pod is first reflected in its precise resolution of industry pain points, perfectly aligning with W2C-1000GW's demand for green and high-efficiency computing. In terms of deployment efficiency, the computing pod adopts Broad's prefabricated building module design. All facilities including IT cabinets, power supply equipment, cooling systems and control terminals are integrated and prefabricated in factories. On-site, only module hoisting, interface connection and system joint debugging are required for commissioning. The deployment cycle is shortened by over 80% compared with traditional data centers, enabling rapid response to the computing capacity expansion needs of W2C-1000GW across different regions and scenarios. In terms of energy utilization, the computing pod innovatively adopts a "natural gas combined cooling, heating and power (CCHP) + waste heat recovery for cooling" model. After natural gas is burned by generators to generate electricity for computing needs, the resulting high-temperature waste heat (above 300°C) is recovered to drive Broad's non-electric air conditioners, producing 7–12°C chilled water for liquid cooling. This achieves cascade energy utilization with an overall energy efficiency rate of over 90%, and the PUE is stably controlled below 1.1, far lower than the industry average. It significantly reduces energy consumption and carbon emissions in the W2C-1000GW initiative. In terms of reliability, the computing pod employs a dual natural gas generator redundancy configuration combined with a UPS emergency power supply scheme, achieving seamless switching within 0.15 seconds to ensure uninterrupted power supply. The overall infrastructure reliability reaches Tier III standard with a designed availability rate of 99.995%, providing core support for the stable operation of W2C-1000GW.

The overall architecture design of the BROAD AI Battery Computing Pod centers on "AI-driven + modularization", balancing flexibility and stability to adapt to the deployment needs of W2C-1000GW across different scenarios. In scenario-specific architecture selection, for high-load scenarios requiring independent power supply—such as remote edge nodes and emergency support computing centers—a generator-equipped architecture is adopted, relying on the natural gas CCHP system to achieve independent energy supply. For urban areas with stable power grids—such as urban computing clusters and park computing centers—a generator-free architecture is adopted, which connects to grid power while retaining waste heat recovery for cooling functions to further optimize energy efficiency. This flexible architecture design allows the computing pod to seamlessly integrate into the multi-scenario computing layout of W2C-1000GW, covering urban areas, edge locations and special emergency scenarios.

In terms of technical approach, the BROAD AI Battery Computing Pod builds an efficient and stable technical system through high integration of hardware modules and intelligent collaboration of software modules. On the hardware side, the transportation and installation modules adopt a 40-foot international standard container design, which can be integrated into the global logistics network for rapid on-site assembly, reducing construction costs and cycles. The power supply module adopts a redundant design of "generator + UPS + intelligent power distribution cabinet" to achieve full-link monitoring and zero-interruption switching. The waste heat recovery module realizes cascade energy utilization through the process of high-temperature flue gas recovery and non-electric air conditioner-driven cooling/heating. The core process forms a closed loop: "natural gas power generation → high-temperature waste heat recovery → non-electric air conditioner chilled water production → liquid cooling heat dissipation → hot water return cooling". The cooling module adopts a three-level hybrid cooling architecture of "chip-level cold plate liquid cooling + cabinet-level liquid cooling backplane + room-level non-electric air conditioning", precisely addressing the cooling bottleneck of high-density computing and supporting the deployment of single-cabinet power density above 10kW. The control module is centered on a DCIM (Data Center Infrastructure Management) intelligent system, realizing centralized management and control as well as intelligent linkage of power supply, cooling and security equipment. On the software side, the DCIM intelligent system reduces manual operation and maintenance costs and downtime losses through real-time monitoring, AI-optimized scheduling and fault early warning functions. The BROAD AI Battery selection tool adopts a four-layer integrated architecture of "perception – understanding – generation – interaction", supporting natural language input and 3D visualized configuration to realize "design through dialogue". It helps users quickly complete scheme selection and cost-benefit simulation, reducing decision-making risks.

In terms of performance and benefits, the BROAD AI Battery Computing Pod also meets the development demands of W2C-1000GW. In terms of performance indicators, in addition to the ultra-low PUE (≤1.1), its waste heat recovery efficiency reaches over 70%, and the cooling capacity of non-electric air conditioners can fully cover the heat load requirements of the computing pod. It demonstrates excellent Mean Time Between Failures (MTBF) and strong adaptability to extreme environments, enabling stable operation under high temperature, low temperature and power outage conditions. Its carbon emission per unit computing capacity is significantly lower than that of traditional data centers, with a full-life-cycle carbon reduction rate of over 80%, perfectly aligning with the low-carbon goals of W2C-1000GW. In terms of economic benefits, the computing pod reduces construction costs through prefabricated design and lowers operation and maintenance costs through ultra-high energy efficiency. According to typical case calculations, its annual operating costs are only 34% of those of traditional electric air conditioner-based computing pods. Meanwhile, it supports multiple cooperation models such as product procurement, project co-construction and customized development, lowering the decision-making threshold for customers and accelerating the implementation and promotion of W2C-1000GW in different fields.

In terms of application scenario adaptation, the diverse advantages of the BROAD AI Battery Computing Pod are fully demonstrated, comprehensively covering the core application fields of W2C-1000GW. In artificial intelligence (AI) and high-performance computing (HPC) cluster scenarios, its high power density and efficient cooling capacity can meet the high computing demands of AI training and HPC operations. In edge computing node scenarios, its modular and rapid deployment capability addresses the low-latency computing needs of edge areas such as industrial parks and mining areas. In zero-carbon/low-carbon park scenarios, its natural gas clean energy and waste heat recovery technologies help parks achieve "dual carbon" goals. In special scenarios such as natural disaster emergency response, its grid-independent feature ensures stable supply of temporary computing power. The wide adaptation to these scenarios makes the BROAD AI Battery Computing Pod the core hub connecting energy and computing for W2C-1000GW.

Looking ahead, with the continuous deepening of the W2C-1000GW initiative, the BROAD AI Battery Computing Pod will continue to advance technological iteration and scenario expansion. In terms of technology, it will explore higher-temperature liquid cooling technologies and energy supply models combining photovoltaic power and natural gas to further improve energy efficiency and low-carbon levels. In terms of scenarios, it will enhance adaptability to extreme environments such as polar regions and high-temperature areas, expanding applications in more special scenarios. In terms of ecology, it will build a more open ecosystem for device compatibility and promote the development of industry standards. As an important component of W2C-1000GW, the BROAD AI Battery Computing Pod is not only a benchmark for current green and high-efficiency computing infrastructure, but will also contribute core strength to achieving the goals of "inclusive computing and low-carbon energy" amid the global wave of integration between digital economy and green energy, leading the computing infrastructure industry into a new stage of development.