The AI infrastructure wave ignites the surge in demand for green electricity, and Morgan Stanley outlines the "Renewable Energy Super Cycle".

Wall Street financial giant Morgan Stanley recently released a research report stating that the unprecedented expansion cycle of AI data centers is increasingly linked to clean electricity supply/networking based on renewable energy sources. For example, the narrative core of Alphabet Inc. Class C's parent company Alphabet's acquisition of Intersect is "the integration of data center development with electricity infrastructure (renewable + energy storage), first securing power sources and then introducing large customers." Morgan Stanley also provided clear mid-term investment targets and data center capital expenditure clues (200 billion US dollars / 400 billion US dollars). The Morgan Stanley analyst team stated that Alphabet Inc. Class C's acquisition is equivalent to strengthening this investment theme: AI load growth will push the scarcity of "clean power-side assets, networking capacity, and long-term contracts" onto Wall Street trading desks. Stock market statistics show that iShares Global Clean Energy (Global Clean Energy Fuels Corp. ETF, US stock code: ICLN) has risen by as much as 47% since 2025, mainly due to the strong performance of US Clean Energy Fuels Corp. and renewable energy infrastructure giants Bloom Energy (BE.US) and First Solar (FSLR.US), especially the former with a 300% increase in stock price during the year. Although the Trump administration is dismissive of renewable energy, the stock market still has a very positive outlook on the future of renewable energy, believing that the AI-driven new cycle has begun, and that this 100% clean energy-driven green electricity with long-term contracts is the future of the global energy system, as traditional resources such as coal and oil do not align with global government ambitions for carbon reduction and will eventually be completely depleted. In the United States, the immense power demand brought by AI training/inference systems, as well as the inevitable emission reduction pressure brought by global climate change, may further accelerate US technology giants leading the construction of AI data centers towards more affordable and low-carbon energy transformation. Morgan Stanley cited Alphabet Inc. Class C's parent company, Alphabet's acquisition of Intersect Power, in this research report, pointing out that technology giants need renewable energy to meet the 24/7 clean electricity demand. Alphabet Inc. Class C plans to mobilize 200 billion US dollars in renewable energy investments by 2030, with similar plans from Amazon.com, Inc., and Microsoft Corporation. Alphabet Inc. Class C also plans to invest approximately $400 billion in building three new large-scale AI data center campuses in Texas by 2027 (Morgan Stanley specifically mentioned that one of the campuses is the "CECEP Solar Energy + Battery Energy Storage" co-location project developed in collaboration with Intersect). In terms of stock market performance, renewable energy stocks since Trump's second term have shown very impressive overall performance, highlighting the market's strong outlook for the long-term demand curve for renewable energy. Particularly in the background of the new demand cycle driven by AI, the market is pricing the demand for renewable energy that combines cost-effectiveness and clean attributes into a strong growth trajectory. The renewable energy infrastructure sector faces structural growth opportunities, and Morgan Stanley calls it a good buying opportunity to buy on dips. The Morgan Stanley analyst team stated that the Trump administration's suspension of five major offshore wind projects (involving 6.9GW capacity) has put short-term pressure on the renewable energy industry, but long-term demand is driven by the sharp increase in power supply for data centers and the exponential growth in AI computing power demand. Morgan Stanley believes that grid modernization, storage support, and co-location models will be key breakthroughs for renewable energy systems. Morgan Stanley believes that the renewable energy infrastructure sector faces structural growth opportunities, and those with high-quality fundamentals, high cash flow visibility, and moderate dividend return capabilities in renewable energy infrastructure assets present good buying opportunities. In terms of specific valuations, Morgan Stanley believes that the pricing of the renewable energy infrastructure sector currently reflects some macro and policy risks, and key companies such as Brookfield Renewable (BEP.US) and Clearway Energy (CWEN.US) have defensive cash flow visibility. Morgan Stanley maintains an "attractive" bullish view on the renewable energy sector, and recommends overweighting leading renewable energy infrastructure companies with scale advantages and storage technologies, while giving a "neutral" (Equal-Weight) rating to utility-class renewable energy. The Morgan Stanley analyst team stated that the structural power demand increase (AI data centers) is shifting the theme of "clean power + storage + networking" from thematic investment to asset allocation issues, especially for basic infrastructure renewable assets with contract cash flows at their core, which are better described in terms of "target price + dividends + total returns" to characterize risk-return relationships, making it easier to achieve valuation recovery in the stage of interest rate cuts and improving risk appetite. In terms of specific investments, Morgan Stanley identifies the following renewable energy infrastructure stocks (in capital letters US stock market codes) as worth "overweighting": Brookfield Renewable Partners L.P. (BEP.US), Brookfield Renewable Corp (BEPC.US), Clearway Energy (CWEN.US), and HA Sustainable Infrastructure (HASI.US). The end of AI is in electricity! The wave of AI infrastructure construction is sweeping the world, and renewable energy is entering a new era of growth The essence of the global AI competition is the competition for AI computing power infrastructure, and the core foundation driving the massive AI GPU/AI ASIC computing power clusters is a stable and large power supply system. Therefore, the electricity demand of AI data centers is skyrocketing at an unprecedented speed, with AI becoming a "power devourer". The enormous energy-consuming AI data centers, which are expanding exponentially along with the demand for AI chips and other computing power infrastructure, cannot do without electricity supply, which is the origin of the market view that "the end of AI is electricity." Goldman Sachs Group, Inc., another financial giant on Wall Street, recently raised its forecast for the massive electricity demand driven by global data centers by 2030, projecting a 175% expansion (Goldman Sachs Group, Inc.'s previous forecast was +165%) compared to 2023, equivalent to adding the electricity resource burden of another "top ten electricity-consuming country" to the world. In the view of the strategy analysts at Goldman Sachs Group, Inc., the ultimate goal of AI models is electricitythe organization emphasizes that the "power-devouring monster" AI will usher in an unprecedented global electricity "super demand cycle" and a "super bull market" for electricity stocks. After the launch of the Gemini3 AI application ecosystem by Alphabet Inc. Class C at the end of November, this cutting-edge AI application software quickly gained global popularity, driving a sharp increase in AI computing power demand for Alphabet Inc. Class C. The Gemini3 series of products brought an immense processing volume of AI tokens upon release, forcing Alphabet Inc. Class C to significantly reduce the free access to Gemini 3 Pro and Nano Banana Pro, as well as temporarily restrict subscriptions for Pro users. Additionally, recent South Korean trade export data showing continued strong demand for HBM storage systems and enterprise SSDs further validates the "AI boom is still in the early stages of artificial intelligence computing power infrastructure construction," which means that future electricity demand will continue to rise sharply. According to the latest cost report from the International Renewable Energy Agency (IRENA) cited by Morgan Stanley, the majority of new renewable projects added by 2024 have lower overall costs than similar fossil energy solutions; especially the average cost of solar and onshore wind power continues to decline. Therefore, as global data center electricity demand soars due to AI, lower-cost renewable energy sources such as wind and solar power are naturally getting priority allocation. In terms of new installed capacity and cost per kilowatt-hour, renewable energy sources may soon become the "first choice" for expanding power systems in the age of AI, supplemented by energy storage/nuclear power to fill the supply curve. In the AI era, the supply of Clean Energy Fuels Corp. becomes increasingly important. The strong demand from large data centers for Clean Energy Fuels Corp. from Alphabet Inc. Class C, Microsoft Corporation, and others is mainly due to the global decarbonization trend focusing on efficient, cost-effective, and zero-emission, clean energy resources such as wind and geothermal, which may be the most important sources for the global artificial intelligence power system. Analysts at the international major bank UBS Group AG stated in a research report that the demand for utility-scale CECEP Solar Energy projects in the United States is gradually exceeding supply, with some of the momentum coming from the large-scale construction of AI data centers targeting 100% Clean Energy Fuels Corp. This positive factor provides a huge upward potential for the growth curve of the US CECEP Solar Energy industry and significantly increases demand certainty. In addition, analysts at UBS Group AG also stated that in the context of Trump's tariff protection policy, US-based CECEP Solar Energy hardware suppliers are in a very favorable position. (Note: This translation is provided for the purpose of understanding the content of the original text. It may contain errors or inaccuracies.)