Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events
Frequent disruptions from extreme weather events pose a significant threat to modern power distribution systems. To enhance grid resilience, this study proposes a novel framework for the strategic placement of virtual power plants (VPPs) within interconnected microgrids (MGs), integrating diverse di...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-07-01
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| Series: | Energy Conversion and Management: X |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590174525003083 |
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| Summary: | Frequent disruptions from extreme weather events pose a significant threat to modern power distribution systems. To enhance grid resilience, this study proposes a novel framework for the strategic placement of virtual power plants (VPPs) within interconnected microgrids (MGs), integrating diverse distributed energy resources (DERs) such as solar, wind, battery energy storage systems (BESS), and battery electric vehicles (BEVs). Utilizing a modified IEEE 118-bus radial distribution system (RDS), segmented into residential, commercial, and industrial zones, the black widow optimization (BWO) algorithm is employed to optimally size and site VPPs, minimizing operational costs and maximizing system resilience. Renewable energy uncertainty is modeled via the two-point estimation method, with performance assessed using key resilience metrics like energy not supplied (ENS) and load restoration index (LRI). Simulation results demonstrate the BWO-based strategy’s superior performance, reducing total objective cost to $2.54 million, outperforming genetic algorithm (GA) and particle swarm optimization (PSO) by 5.01% and 8.54% respectively. Furthermore, it achieves the lowest ENS, highest LRI across critical zones, and exhibits faster convergence with fewer fitness evaluations. This work highlights the significant potential of VPP-enabled MGs coupled with bio-inspired optimization to improve power system resilience under adverse conditions. |
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| ISSN: | 2590-1745 |