סמינר: Graduate Seminar
Learning-based optimal placement of energy storage systems for frequency stability in large-scale power systems
Date:
December,03,2025
Start Time:
15:00 - 16:00
Location:
1061, Meyer Building
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Lecturer:
Eden Dina Horodi
Research Areas:
| The growing integration of renewable energy sources, such as wind and solar, introduces variability and reduces system inertia, challenging the frequency stability of modern power grids. Energy Storage Systems (ESS) can provide synthetic inertia and primary frequency control; however, their effectiveness depends critically on optimal placement within the network. Conventional optimization and brute-force methods become computationally infeasible as the number of ESS units increases due to the exponential growth of possible configurations. This study presents a novel data-driven framework that leverages advanced learning models to predict optimal ESS allocations in large-scale power systems. By learning from single-ESS simulations, the proposed method infers near-optimal multi-ESS placements with constant computational complexity, independent of the number of storage units. Validation on the IEEE 30- and 118- bus systems demonstrates that the framework achieves adequate, computationally efficient, and scalable performance for high-dimensional ESS placement problems. |
| M.Sc. student under the supervision of Prof. Yoash Levron.
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