| Issue |
E3S Web Conf.
Volume 680, 2025
The 4th International Conference on Energy and Green Computing (ICEGC’2025)
|
|
|---|---|---|
| Article Number | 00127 | |
| Number of page(s) | 11 | |
| DOI | https://doi.org/10.1051/e3sconf/202568000127 | |
| Published online | 19 December 2025 | |
Multi-layer energy storage framework for flexible power grids
1 Assistant Professor, Department of CS & IT, Kalinga University, Raipur, India
2 Assistant Professor, Department of CS & IT, Kalinga University, Raipur, India
* Corresponding author: ku.ManjulataBhoi@kalingauniversity.ac.in
Problems with grid stability, dependability, and effective energy management are brought about by the rising use of renewable energy sources like wind and solar, which bring an element of unpredictability and variable into today’s power systems. To integrate these resources effectively, we need cutting-edge technologies that can control demand and supply, handle peak loads, and lessen our reliance on fossil fuels. The goal of this research is to improve the sustainability, dependability, and adaptability of current power grids via the creation of a Multi-Layer Energy Storage Framework (MLESF). Energy dispatch, peak load management, and renewable energy use are all optimized by integrating short-term, medium-term, and long-term storage technologies. This coordination is done via a smart energy management system. The simulation results show that MLESF has great potential for future low-carbon energy systems, with notable improvements in renewable energy integration (91%), storage efficiency (88%), peak load reduction (35%), grid reliability (48% improvement in SAIDI), cost savings ($22/MWh), and CO₂ emission reduction (18%).
Key words: Multi-Layer Energy Storage / Flexible Power Grids / Renewable Energy Integration / Grid Reliability / Smart Energy Management / Storage Optimization / Resilient Power Systems / Sustainable Energy
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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