Enhancing Grid Stability with Tensor-Based Analysis: The TenSyGrid Project
By leveraging advanced mathematical models, it offers a promising solution for managing the complexities of modern power systems.
Image for illustration purposes.
As the world shifts towards renewable energy, power grids face new challenges. Renewable sources like solar and wind are intermittent, making it difficult for traditional grid models to predict energy supply and demand accurately. To address these challenges, Fraunhofer Institute for Wind Energy Systems (IWES) and its partners are developing the TenSyGrid project.
The Challenge of Renewable Energy Integration
Traditional power plants connect to the grid via rotating masses, providing inertia that helps stabilize frequency. However, renewable energy sources use power electronics converters, which introduce rapid transient behaviors that cannot be captured by traditional linear models. This complexity necessitates innovative approaches to ensure grid stability.
TenSyGrid Solution
TenSyGrid uses multilinear models based on tensors to capture the non-linear dynamics of converter-dominated power grids. This approach is less computationally intensive than traditional electromagnetic transient (EMT) simulations, allowing for real-time stability assessments. The project aims to develop a toolbox compatible with existing commercial software, making it easy for grid operators to integrate into their workflows.
Key Features and Benefits
Real-Time Assessment: Enables grid operators to assess stability in real-time, enhancing grid resilience and reliability.
Scalability: The multilinear framework is scalable and easily updatable, reflecting ongoing changes in the grid.
Interpretability: Tensor models are highly interpretable, providing clear insights into grid dynamics.
Compatibility: Designed to integrate seamlessly with existing software, minimizing the need for significant system changes.
Source: EEPower
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