News linked to both this project and an event.
According to TechFlow Research, Goldman Sachs' July 16 energy storage report pointed out that electricity demand from data centers is surging, traditional grid expansion requires four to eight years, and energy storage has become the fastest solution with a 12 to 18-month deployment cycle. Goldman Sachs estimates that by 2030, behind-the-meter energy storage opportunities in the US will bring about 50GWh of increment, plus 11GWh from 800V DC data centers, total US energy storage deployment will reach 172GWh, significantly upwardly revised from the previous 112GWh. Globally, annual energy storage installations are expected to reach 2100GWh by 2040. Goldman Sachs believes energy storage is transitioning from renewable energy supporting equipment to a necessity for AI infrastructure, which will change the industry valuation logic. In terms of targets, FLNC (Buy) secured exclusive battery partner qualification for Nvidia DSX Vera Rubin, data center pipeline projects reached 12GW, up 30% sequentially; CATL (Buy) has about 30% global energy storage market share, already used in Shanghai SenseTime data center; Tesla (Neutral) 2025 energy storage deployment 46.7GWh, energy business 2028 estimated revenue 29 billion USD; Energy Vault (Neutral) received 6x EV/EBITDA valuation; LGES (Buy) North America ESS capacity expected to reach 50GWh by end of 2026. Canadian Solar, Ford, Samsung SDI, Shoals, Sungrow are also worth watching. Goldman Sachs emphasizes the need to distinguish those with real order support
Sharon AI Holdings, a Nasdaq-listed company, announced a six-year strategic computing cooperation agreement with NVIDIA to jointly expand AI infrastructure capabilities in Australia.Under the agreement, the two parties will collaborate to build approximately 72MW of data center computing capacity and deploy infrastructure based on the NVIDIA DSX AI Factory architecture. The plan is to gradually scale up to 40,000 Grace Blackwell GB300 GPUs to meet the computing needs of AI startups, enterprise clients, and research institutions.The cooperation model adopts a structure combining revenue generation with credit support: Sharon AI will be responsible for selling cloud services based on NVIDIA's computing power, while NVIDIA, upon receiving hardware and basic product revenue, will also participate in a share of cloud service revenue, forming a sustainable "usage-driven revenue model."Sharon AI stated that this collaboration will significantly enhance its capital efficiency, enabling it to expand AI infrastructure capabilities without relying on traditional heavy-asset financing and accelerate the deployment of "sovereign AI computing power" in Australia. With this partnership, Sharon AI's total AI factory capacity will increase to 132MW, of which approximately 102MW is already contracted by clients. The company expects to deploy over 55,000 NVIDIA GPUs by mid-2027. (Businesswire)