Sustainable Energy and Artificial Intelligence

Power System Resilience Enhancement Based on Network Reconfiguration and Photovoltaic Resources Integration

Document Type : Original Article

Authors

Seyed Masoud Moeini
Abbas Fattahi

Electrical and Computer Engineering Department, Hamedan University of Technology, Hamedan, Iran

https://doi.org/10.66224/seai.2602-1043
Abstract
Natural disasters, such as floods and earthquakes, frequently cause widespread power outages and irreversible damage to equipment and consumers within the power industry. Ensuring a safe and uninterrupted electricity supply during such events represents a primary challenge for modern power system operators, a concept often termed network resilience. This paper proposes a network reconfiguration plan, integrated with photovoltaic (PV) resource management, to enhance the resilience of a power distribution network against natural disaster threats. The proposed approach minimizes the total expected costs, comprising both equipment repair/reinforcement and consumer outage costs, which serve as the objective function. Furthermore, the model incorporates AC power flow constraints, network reconfiguration logic, and PV resource capacity limits. Uncertainties—including active and reactive load demands, PV generation, and the availability of network components (such as main/reserve lines and PV resources)—are modeled using scenario-based stochastic programming. Scenarios are generated via the Monte Carlo method, with a subset selected using the Kantorovich reduction technique. Finally, the resulting stochastic optimization problem is formulated as a Mixed-Integer Nonlinear Programming model and solved using GAMS software. The proposed method is implemented and analyzed on 33-bus and 119-bus sample networks through four distinct case studies. Numerical results conclusively demonstrate that the integration of robust PV resources, combined with network reconfiguration, significantly improves network resilience under various natural disaster scenarios.

Keywords

PV resources
network reconfiguration
network resilience
scenario-based stochastic programming
power system
Subjects
1. Wang, Y., Li, X., Smith, J., & Liu, Z. (2023). A comprehensive review of power system resilience: Indices, frameworks, and enhancement strategies. IEEE Access, 11, 25488–25510.
2. Chen, L., & Rahimi, M. (2023). A graph-based multi-criteria resilience assessment framework for power grids under compound hazards. International Journal of Electrical Power & Energy Systems, 145, 108502.
3. Zhang, H., Zhao, J., Kumar, S., & Nguyen, T. (2023). Markovian modeling of grid component failures under sequential hurricane and flooding events. IEEE Transactions on Power Systems, 38(2), 1123–1134.
4. Patel, R., Gupta, A., & Singh, M. (2023). Deep learning for predictive resilience: Real-time vulnerability assessment using CNNs and satellite data. Applied Energy, 334, 120678.
5. Kumar, S., & Bose, A. (2023). Identifying critical transmission lines using electrical centrality and cascading failure analysis. Electric Power Systems Research, 214, 108891.
6. Li, J., Wang, K., & Zhao, L. (2023). Coordinated control of FACTS devices for transient stability enhancement in resilience-oriented grids. IEEE Transactions on Smart Grid, 14(1), 223–235.
7. Nguyen, F., & Smith, T. (2023). Dynamic line rating and topology optimization for congestion relief during extreme weather. Renewable and Sustainable Energy Reviews, 171, 113024.
8. National Renewable Energy Laboratory. (2024). Community resilience through renewable microgrids: Lessons from recent wildfire and hurricane responses (NREL/TP-5C00-88012). National Renewable Energy Laboratory.
9. Johnson, M., Roberts, L., & Carter, E. (2023). Mobile energy storage for rapid outage response: A resilience-as-a-service framework. Joule, 7(4), 789–805.
10. Panteli, M., & Mancarella, P. (2020). The grid: Stronger, bigger, smarter? Presenting a conceptual framework of power system resilience. IEEE Power and Energy Magazine, 18(3), 58–66.
11. Dehghanian, P., Wang, Z., Wang, J., & Zhang, Y. (2021). A survey on power system resilience: Definitions, concepts, and applications. IEEE Transactions on Smart Grid, 12(4), 3455–3468.
12. Lei, S., Wang, J., Chen, C., & Hou, Y. (2020). Mobile emergency generator pre-positioning and real-time allocation for resilient distribution systems. IEEE Transactions on Smart Grid, 11(6), 5071–5083.
13. Zhang, Y., Xu, Y., Dong, Z. Y., & Wong, K. P. (2020). Robust microgrid planning for resilient distribution systems. IEEE Transactions on Smart Grid, 11(1), 362–372.
14. Nazemi, M., Dehghanian, P., Lu, X., & Chen, C. (2021). Uncertainty-aware deployment of mobile energy storage systems for distribution grid resilience. IEEE Transactions on Smart Grid, 12(4), 3200–3214.
15. Gholami, A., Aminifar, F., & Shahidehpour, M. (2023). Enhancing resilience of distribution systems using coordinated distributed energy resources, energy storage, and network reconfiguration. Electric Power Systems Research, 216, 109057.
16. Ghasemi, M., Kazemi, A., Gilani, M. A., & Shafie-khah, M. (2021). A stochastic planning model for improving resilience of distribution systems considering master–slave distributed generators and network reconfiguration. IEEE Access, 9, 78859–78872.
17. Shahbazi, A., Aghaei, J., Pirouzi, S., & Shafie-khah, M. (2021). Effects of resilience-oriented design on distribution networks operation planning. Electric Power Systems Research, 191, 106902.
18. Shahbazi, A., Aghaei, J., & Shafie-khah, M. (2021). Hybrid stochastic–robust optimization model for resilient architecture of distribution networks against extreme weather conditions. International Journal of Electrical Power & Energy Systems, 126, 106576.
19. Shahbazi, A., Aghaei, J., Pirouzi, S., & Shafie-khah, M. (2021). Holistic approach to resilient electrical energy distribution network planning. International Journal of Electrical Power & Energy Systems, 132, 107212.
20. Ghosh, P., & De, M. (2024). Resilience-oriented planning for active distribution systems: A probabilistic approach considering regional weather profiles. International Journal of Electrical Power & Energy Systems, 158, 109976.
21. Hamidieh, M., & Ghassemi, M. (2022). Microgrids and resilience: A review. IEEE Access, 10, 106059–106080.
22. Domínguez-García, J. L., Pepiciello, A., Paradell, P., & Ivanova, A. (2023). Dynamic microgrids for strengthening power system resilience. IEEE Smart Grid Magazine, 1–7.
23. Younesi, A., Shayeghi, H., Safari, A., & Siano, P. (2020). Assessing the resilience of multi-microgrid based widespread power systems against natural disasters using Monte Carlo simulation. Energy, 207, 118220.
24. Kizito, R., Liu, Z., Li, X., & Sun, K. (2022). Multi-stage stochastic optimization of islanded utility microgrids design after natural disasters. Operations Research Perspectives, 9, 100235.
25. Hamidpour, H., Pirouzi, S., Safaee, S., Norouzi, M., & Lehtonen, M. (2021). Multi-objective resilient-constrained generation and transmission expansion planning against natural disasters. International Journal of Electrical Power & Energy Systems, 132, 107193.
26. Polat, S., Bıyık, E., & Öztura, H. Ş. (2025). Optimal active and reactive power scheduling for inverter-integrated PV and BESS under inverter current constraints. Electric Power Systems Research, 245, 111629.
27. Tavakoli, A., & Karimi, A. (2023). Development of Monte-Carlo-based stochastic scenarios to improve uncertainty modelling for optimal energy management of a renewable energy hub. IET Renewable Power Generation, 17(5), 1139–1164.
28. Ouédraogo, A., Zouma, B., Ouédraogo, E., Guissou, L., & Bathiébo, D. J. (2021). Individual efficiencies of a polycrystalline silicon PV cell versus temperature. Results in Optics, 4, 100101.
Sustainable Energy and Artificial Intelligence
Volume 2, Issue 2
Spring 2026
Pages 131-144

  • Receive Date 05 February 2026
  • Revise Date 29 May 2026
  • Accept Date 05 June 2026
  • First Publish Date 05 June 2026

Home

Guide for Authors

Submit Manuscript

Reviewers

Contact Us