Huawei Advances Grid-Forming Energy Storage Strategy with Global Deployments and New Smart String ESS Platform

As global renewable energy adoption accelerates, many countries are facing challenges with power system infrastructure at different stages of development. To meet these evolving needs, energy storage systems (ESS) are increasingly being deployed across diverse scenarios.

With the rising penetration of solar and wind energy, grid-forming technologies are emerging as a critical and inevitable pathway for the long-term evolution of global power systems. Huawei FusionSolar’s Grid-Forming ESS solution—previously launched and deployed at the Red Sea destination in the Middle East—represents a significant step in this direction. The project, featuring 400 MW of solar PV capacity combined with 1.3 GWh of ESS, is 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 deployed in Germany, Bulgaria, the Philippines, and China, reinforcing the company’s commitment to global energy transformation.

At a recent launch event, Huawei introduced the next-generation Smart String Grid-Forming ESS Platform under its “FusionSolar Strategy.” Steven Zhou, President of the Smart PV & ESS Product Line at Huawei Digital Power, emphasized the company’s long-term vision: integrating “4T technologies”—bit, watt, heat, and battery—to build the digital energy infrastructure of the future.

Zhou outlined three core value propositions of Huawei’s grid-forming approach:

• All-Scenario Grid Forming: Applying grid-forming capabilities across generation, transmission, distribution, and consumption to ensure long-term grid stability.
• Cell-to-Grid Safety: Implementing comprehensive safety measures from the cell level to the grid to protect equipment, personnel, and assets.
• 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.