Siemens Unveils Gridscale X Platform Enhancements and AI-Powered PSS E

Siemens launched the next evolution of its Gridscale X platform and the next generation of PSS E software to manage grid complexity and transmission planning. The platform utilizes a unified grid model and digital twin to provide system-wide visibility. This architecture is intended to allow operators to manage flexibility and reduce operational risks while operating grids near technical limits.

The platform supports self-developed applications, allowing utilities to migrate proprietary software onto the shared grid model. This integration enables innovations to be incorporated directly into system operations workflows.

Implementation and Strategic Partnerships
Dutch network operator Alliander has integrated custom-built applications into the Gridscale X platform. Following the commencement of a strategic partnership in 2024, Alliander expanded its medium-voltage grid coverage from 65 percent to 100 percent. The operator migrated 85 applications onto the platform, resulting in a 30 percent reduction in IT landscape density.

AI-Powered Transmission Planning
Siemens introduced the next generation of PSS E on Gridscale X at the Grid Software Summit in Amsterdam, held from May 6 to May 8, 2026. The updated software incorporates AI-powered agentic capabilities and domain-specific automation to accelerate planning studies and workflows.

The software includes over 2,000 open APIs to facilitate integration and automation for digital twin-based planning. The latest release is specifically designed to support data center and large load integration scenarios. According to company data, a redesigned cloud-native user experience for connection studies can reduce response times by up to 50 percent.

Sabine Erlinghagen, CEO of Siemens Grid Software, stated that the platform bridges long-term planning and real-time operations. She noted that the introduction of agentic capabilities and a modern user experience is intended to provide planners with tools to manage increasing time pressure and system complexity.

Additional Context
The global transition toward renewable energy and the rapid expansion of high-load industries, such as AI-driven data centers, have placed unprecedented strain on existing electrical infrastructure. Traditional grid management often relies on fragmented data models and manual planning processes that struggle to account for the volatility of weather-dependent energy sources like wind and solar.

Digital twins and unified grid models are increasingly employed in the utility sector to create virtual replicas of physical assets. These technologies allow for real-time simulation and predictive analysis, enabling utilities to test "what-if" scenarios without risking physical infrastructure. Agentic AI in this context refers to autonomous or semi-autonomous software agents capable of performing complex tasks—such as running thousands of load-flow simulations—with minimal human intervention. This shift toward automation is viewed as a primary method for utilities to increase connection capacity and maintain system reliability as electrification accelerates worldwide.

Edited by Romila DSilva, Induportals Editor, with AI assistance.