Techno-Economic Modelling of a Resilience Enhancement Strategy Based on Multi-microgrid Operational Capabilities

Subject Areas : Power Engineering

Samira Salahi ¹ (Department of Electrical Engineering, University of Kurdistan, Sanandaj, Iran)
Navid Rezaei ² (Department of Electrical Engineering, University of Kurdistan, Sanandaj, Iran)
Jamal Moshtagh ³ (Department of Electrical Engineering, University of Kurdistan, Sanandaj, Iran)

Received: 2023-09-20 Accepted : 2023-12-02 Published : 2024-05-21

Keywords: Multi-microgrids, HILP events, Black-start services, Resilience enhancement, Bilateral contract,

Abstract :

The increasing growth of natural disasters and cyber-physical attacks has made developing resilience enhancement strategies for distribution networks become a significant challenge for researchers. Hence, in this paper, a black-start strategy based on multi-microgrids capability is presented in two layers of preventive and corrective measures within a hierarchical centralized energy management framework. The preventive measures layer is based on the regulation of black-start bilateral contracts between the active distribution network operator and the multi-microgrids owner, as well as the regulation of demand response contracts between the multi-microgrids owner and the microgrid response loads. The corrective measures layer includes islanding of microgrids during events, calling of responsive loads, and finally economic-resilient operational planning of the active distribution network in order black-start the distribution system. The developed model is formulated in the framework of hierarchical centralized energy management using an LP-metric-based multi-objective optimization approach, then it is solved by the DICOPT solver in the GAMS package. The effectiveness of the proposed black-start strategy is investigated by evaluating the supplied load as a resilience index on the modified IEEE 33-bus distribution network. The recovery of all the curtailed load of the distribution system after utilizing the proposed strategy indicates the efficiency of the proposed strategy indicates the effectiveness of the proposed black-start strategy.

References:

1. N. Bhusal, M. Abdelmalak, M. Kamruzzaman, and M. Benidris, “Power system resilience: Current practices, challenges, and future directions,” IEEE Access, vol. 8, no. January, pp. 18064–18086, 2020, doi: 10.1109/ACCESS.2020.2968586.


2. A. A. Bajwa, H. Mokhlis, S. Mekhilef, and M. Mubin, “Enhancing power system resilience leveraging microgrids: A review,” J. Renew. Sustain. Energy, vol. 11, no. 3, 2019, doi: 10.1063/1.5066264.


3. M. Izadi, S. H. Hosseinian, S. Dehghan, A. Fakharian, and N. Amjady, “A critical review on definitions, indices, and uncertainty characterization in resiliency-oriented operation of power systems,” Int. Trans. Electr. Energy Syst., vol. 31, no. 1, 2021, doi: 10.1002/2050-7038.12680.


4. E. Hossain, S. Roy, N. Mohammad, N. Nawar, and D. R. Dipta, “Metrics and enhancement strategies for grid resilience and reliability during natural disasters,” Appl. Energy, vol. 290, no. January, p. 116709, 2021, doi: 10.1016/j.apenergy.2021.116709.


5. M. Panteli and P. Mancarella, “The grid: Stronger, bigger, smarter?: Presenting a conceptual framework of power system resilience,” IEEE Power Energy Mag., vol. 13, no. 3, pp. 58–66, 2015, doi: 10.1109/MPE.2015.2397334.


6. G. Liu, T. Jiang, T. B. Ollis, X. Li, F. Li, and K. Tomsovic, “Resilient distribution system leveraging distributed generation and microgrids: A review,” IET Energy Syst. Integr., vol. 2, no. 4, pp. 289–304, 2020, doi: 10.1049/iet-esi.2019.0134.


7. H. Farzin, M. Fotuhi-Firuzabad, and M. Moeini-Aghtaie, “Enhancing Power System Resilience Through Hierarchical Outage Management in Multi-Microgrids,” IEEE Trans. Smart Grid, vol. 7, no. 6, pp. 2869–2879, 2016, doi: 10.1109/TSG.2016.2558628.


8. A. Shahbazi, J. Aghaei, S. Pirouzi, M. Shafie-khah, and J. P. S. Catalão, “Hybrid stochastic/robust optimization model for resilient architecture of distribution networks against extreme weather conditions,” Int. J. Electr. Power Energy Syst., vol. 126, 2021, doi: 10.1016/j.ijepes.2020.106576.


9. S. Ma, B. Chen, and Z. Wang, “Resilience enhancement strategy for distribution systems under extreme weather events,” IEEE Trans. Smart Grid, vol. 9, no. 2, pp. 1442–1451, 2018, doi: 10.1109/TSG.2016.2591885.


10. M. Mahzarnia, M. Parsa Moghaddam, P. Siano, and M. R. Haghifam, “A comprehensive assessment of power system resilience to a hurricane using a two-stage analytical approach incorporating risk-based index,” Sustain. Energy Technol. Assessments, vol. 42, no. May, p. 100831, 2020, doi: 10.1016/j.seta.2020.100831.


11. Y. Li, Z. Li, F. Wen, and M. Shahidehpour, “Minimax-Regret Robust Co-Optimization for Enhancing the Resilience of Integrated Power Distribution and Natural Gas Systems,” IEEE Trans. Sustain. Energy, vol. 11, no. 1, pp. 61–71, 2020, doi: 10.1109/TSTE.2018.2883718.


12. S. Lei, C. Chen, Y. Li, and Y. Hou, “Resilient Disaster Recovery Logistics of Distribution Systems: Co-Optimize Service Restoration with Repair Crew and Mobile Power Source Dispatch,” IEEE Trans. Smart Grid, vol. 10, no. 6, pp. 6187–6202, 2019, doi: 10.1109/TSG.2019.2899353.


13. Q. Shi et al., “Network reconfiguration and distributed energy resource scheduling for improved distribution system resilience,” Int. J. Electr. Power Energy Syst., vol. 124, no. August, p. 106355, 2021, doi: 10.1016/j.ijepes.2020.106355.


14. S. Mousavizadeh, M. R. Haghifam, and M. H. Shariatkhah, “A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources,” Appl. Energy, vol. 211, no. August 2017, pp. 443–460, 2018, doi: 10.1016/j.apenergy.2017.11.067.


15. M. Rajabzadeh and M. Kalantar, “Improving the resilience of distribution network in coming across seismic damage using mobile battery energy storage system,” J. Energy Storage, vol. 52, no. PB, p. 104891, 2022, doi: 10.1016/j.est.2022.104891.


16. M. Ott, M. Almuhaini, and M. Khalid, “A MILP-Based Restoration Technique for Multi-Microgrid Distribution Systems,” IEEE Access, vol. 7, pp. 136801–136811, 2019, doi: 10.1109/ACCESS.2019.2942633.


17. D. N. Trakas and N. D. Hatziargyriou, “Resilience Constrained Day-Ahead Unit Commitment under Extreme Weather Events,” IEEE Trans. Power Syst., vol. 35, no. 2, pp. 1242–1253, 2020, doi: 10.1109/TPWRS.2019.2945107.


18. A. Shahbazi, J. Aghaei, S. Pirouzi, T. Niknam, M. Shafie-khah, and J. P. S. Catalão, “Effects of resilience-oriented design on distribution networks operation planning,” Electr. Power Syst. Res., vol. 191, no. October 2020, 2021, doi: 10.1016/j.epsr.2020.106902.


19. S. Nikkhah, K. Jalilpoor, E. Kianmehr, and G. B. Gharehpetian, “Optimal wind turbine allocation and network reconfiguration for enhancing resiliency of system after major faults caused by natural disaster considering uncertainty,” IET Renew. Power Gener., vol. 12, no. 12, pp. 1413–1423, 2018, doi: 10.1049/iet-rpg.2018.5237.


20. M. Borghei and M. Ghassemi, “A Multi-Objective Optimization Scheme for Resilient, Cost-Effective Planning of Microgrids,” IEEE Access, vol. 8, no. November, pp. 206325–206341, 2020, doi: 10.1109/ACCESS.2020.3038133.


21. M. Ebadat-Parast, M. H. Nazari, and S. H. Hosseinian, “Distribution system resilience enhancement through resilience-oriented optimal scheduling of multi-microgrids considering normal and emergency conditions interlink utilizing multi-objective programming,” Sustain. Cities Soc., vol. 76, no. October 2021, p. 103467, 2022, doi: 10.1016/j.scs.2021.103467.


22. A. S. Kahnamouei and S. Lotfifard, “Enhancing Resilience of Distribution Networks by Coordinating Microgrids and Demand Response Programs in Service Restoration,” IEEE Syst. J., vol. 16, no. 2, pp. 3048–3059, 2022, doi: 10.1109/JSYST.2021.3097263.


23. H. Gao, Y. Chen, Y. Xu, and C. C. Liu, “Resilience-Oriented Critical Load Restoration Using Microgrids in Distribution Systems,” IEEE Trans. Smart Grid, vol. 7, no. 6, pp. 2837–2848, 2016, doi: 10.1109/TSG.2016.2550625.


24. M. A. Gilani, R. Dashti, M. Ghasemi, M. H. Amirioun, and M. Shafie-khah, “A microgrid formation-based restoration model for resilient distribution systems using distributed energy resources and demand response programs,” Sustain. Cities Soc., vol. 83, no. February, p. 103975, 2022, doi: 10.1016/j.scs.2022.103975.


25. A. Younesi, H. Shayeghi, P. Siano, and A. Safari, “A multi-objective resilience-economic stochastic scheduling method for microgrid,” Int. J. Electr. Power Energy Syst., vol. 131, no. October 2020, p. 106974, 2021, doi: 10.1016/j.ijepes.2021.106974.


26. A. Arif and Z. Wang, “Networked microgrids for service restoration in resilient distribution systems,” IET Gener. Transm. Distrib., vol. 11, no. 14, pp. 3612–3619, 2017, doi: 10.1049/iet-gtd.2017.0380.


27. A. M. Zein Alabedin, E. F. El-Saadany, and M. M. A. Salama, “Generation scheduling in Microgrids under uncertainties in power generation,” 2012 IEEE Electr. Power Energy Conf. EPEC 2012, pp. 133–138, 2012, doi: 10.1109/EPEC.2012.6474937.


28. [2M. Jasemi, F. Adabi, B. Mozafari, and S. Salahi, “Optimal operation of micro-grids considering the uncertainties of demand and renewable energy resources generation,” Int. J. Renew. Energy Dev., vol. 5, no. 3, pp. 233–248, 2016, doi: 10.14710/ijred.5.3.233-248.


29. T. Logenthiran and D. Srinivasan, “Short term generation scheduling of a microgrid,” IEEE Reg. 10 Annu. Int. Conf. Proceedings/TENCON, pp. 1–6, 2009, doi: 10.1109/TENCON.2009.5396184.


30. M. E. Parast, M. H. Nazari, and S. H. Hosseinian, “Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance,” IEEE Access, vol. 9, no. July, pp. 102930–102952, 2021, doi: 10.1109/ACCESS.2021.3098528.


31. M. Mazidi, N. Rezaei, and A. Ghaderi, “Simultaneous power and heat scheduling of microgrids considering operational uncertainties: A new stochastic p-robust optimization approach,” Energy, vol. 185, pp. 239–253, 2019, doi: 10.1016/j.energy.2019.07.046.


32. R. Li, W. Wang, Z. Chen, and X. Wu, “Optimal planning of energy storage system in active distribution system based on fuzzy multi-objective bi-level optimization,” J. Mod. Power Syst. Clean Energy, vol. 6, no. 2, pp. 342–355, 2018, doi: 10.1007/s40565-017-0332-x.


33. C. Kongnam, S. Nuchprayoon, S. Premrudeepreechacharn, and S. Uatrongjit, “Decision analysis on generation capacity of a wind park,” Renew. Sustain. Energy Rev., vol. 13, no. 8, pp. 2126–2133, 2009, doi: 10.1016/j.rser.2009.01.023.


34. https://www.nordpoolgroup.com/en/Market-data1/GB/Auction-prices/UK/Hourly/?view=table