Tensor-Based Analysis for a More Stable Grid

Renewable energy resources are challenging established grid operations. As these intermittent resources increase, grids may underperform or struggle to meet energy demands.

Currently, only simulations can accurately predict energy generation and usage. These models tend to be computationally intensive. However, Fraunhofer Institute for Wind Energy Systems (IWES) and partners are developing the TenSyGrid Project, which uses newer mathematical models to enable real-time assessment of non-traditional grids.

Wind turbines. Image used courtesy of Unsplash

What’s the Deal With Renewable Energy?

Traditional energy plants connect to the grid through a means of rotating masses. This allows for a stable connection that can contribute inertia to frequency stabilization, which creates linear power grid simulations. However, renewable energy plants, such as photovoltaic or wind energy plants, connect to the grid through converters. These rapid transitional behaviors cannot be mapped linearly and require a more innovative method.

That’s why Fraunhofer IWES and its partners are developing the TenSyGrid, which can help electricity grid operators manage and assess the energy gains from renewable resources.

TenSyGrid is a toolbox for assessing the direct stability of renewable resources, using mathematical tensors to capture non-linear dynamics within the grid in real time. It will be compatible with commercial software, so it can easily integrate into standard workflows.

The project began in December 2024. Fraunhofer IWES’ partners include eRoots Analytics, Hamburg University of Applied Sciences, Universitat Politècnica de Catalunya/Barcelona Tech (UPC), and the University of Malta. Major funding comes from BMWK Germany, MICIU, CDTI Spain, MICIU, and XJENZA Malta through the E.U.’s Clean Energy Transition Partnership.

The Many Approaches to a Stable Grid

Simplified power grid simulations cannot map how grids with large renewable resources might behave. Due to converter connections, large-scale renewable energy networks are subject to various uncertainties, and old methodologies may be too computationally intensive. This is where the TenSyGrid method comes into play.

Grid operations. Image used courtesy of Wikimedia Commons

The TenSyGrid project aims to create a method for mapping the power grid as a multilinear model using tensors. Tensors are mathematical objects used to describe physical properties. With these tensors, the models can use significantly less computational energy and enable a real-time assessment of power grids. This unique toolbox could also allow grid operators to plan and control their systems as they become increasingly dynamic.

Eduardo Prieto-Araujo, project coordinator at UPC, stated, “Future power systems will be radically different from the traditional networks of previous decades. The massive integration of power electronics-based renewable energy generation, storage, and loads is profoundly transforming modern power systems.”

Prieto-Araujo said systems like TenSygrid can help model modern networks efficiently and reliably.

“Multilinear systems present an interesting alternative for accurately capturing the characteristics of modern power systems, offering innovative methods to support real-time operation of power networks,” he said in a press release.

With the shift away from fossil fuels to renewable energy sources, projects like the TenSyGrid will be crucial in addressing the complexities that arise. By leveraging more accurate mathematical models, grid operators can enhance the stability of our electrical grid with improved planning and real-time assessment tools to ensure a reliable energy supply that can support energy grids with 100% renewable energy sources.