As the global adoption of renewable energy accelerates, numerous countries are encountering challenges related to power system infrastructure at various stages of development. To address these evolving requirements, energy storage systems (ESS) are increasingly being implemented across a range of scenarios.
With the growing integration of solar and wind energy, grid-forming technologies are becoming a vital and unavoidable pathway for the long-term advancement of global power systems. Huawei FusionSolar’s Grid-Forming ESS solution previously launched and deployed at the Red Sea destination in the Middle East—marks a significant milestone in this direction. The project, which features 400 MW of solar PV capacity combined with 1.3 GWh of ESS, is recognized as the world’s largest 100% renewable PV-plus-ESS microgrid. It has been operating stably for over 21 months, delivering more than 1 billion kWh of clean electricity.
Beyond the Middle East, Huawei’s grid-forming ESS solutions have also been installed in Germany, Bulgaria, the Philippines, and China, further solidifying the company’s commitment to global energy transformation.
At a recent launch event, Huawei unveiled the next-generation Smart String Grid-Forming ESS Platform as part of its “FusionSolar Strategy.” Steven Zhou, President of the Smart PV & ESS Product Line at Huawei Digital Power, highlighted the company’s long-term vision: integrating “4T technologies” bit, watt, heat, and battery to construct the digital energy infrastructure of the future.
Zhou outlined three core value propositions of Huawei’s grid-forming approach:
1. All-Scenario Grid Forming: Applying grid-forming capabilities across generation, transmission, distribution, and consumption to ensure long-term grid stability.
2. Cell-to-Grid Safety: Implementing comprehensive safety measures from the cell level to the grid to protect equipment, personnel, and assets.
3. One Matches All: Utilizing an AI-powered PV+ESS collaborative management platform to support diverse business models, enabling energy yield forecasting and automated operational optimization.
Source: Huawei
