Abstract
This study employs the Multi-Objective Grey Wolf Optimizer (MOGWO) to optimize the allocating and sizing of ESS in a modified IEEE 123 Bus Test System integrated with PV systems. The simulation was conducted on MATLAB and the load flow analysis were conducted using OpenDSS through COM interface. The analysis assesses both the operational and placement optimizations of ESSs, demonstrating significant improvements in reducing power loss and voltage deviations while ensuring economic viability. The inclusion of ESSs reduced overand under-voltage events by more than 50%, from 866 in the PVonly scenario to 409 with ESSs, and overall voltage deviation decreased from 7.108 p.u. to 6.809 p.u. The results indicate that optimized ESS deployment can lead to a more stable and efficient power grid, reinforcing the value of MOGWO in complex system optimization.
Original language | English |
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Title of host publication | 8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9798331531492 |
DOIs | |
Publication status | Published - 2024 |
Event | 8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 - Malatya, Turkey Duration: 21 Sept 2024 → 22 Sept 2024 |
Publication series
Name | 8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 |
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Conference
Conference | 8th International Artificial Intelligence and Data Processing Symposium, IDAP 2024 |
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Country/Territory | Turkey |
City | Malatya |
Period | 21/09/24 → 22/09/24 |
Bibliographical note
Publisher Copyright:© 2024 IEEE.
Keywords
- energy storage systems
- multi-objective grey wolf optimizer
- optimization
- renewable energy