[Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
Main Menu
Home::
Journal Information::
Articles archive::
For Authors::
For Reviewers::
Registration::
Contact us::
Site Facilities::
::
Social Network Membership
Linkedin
Researchgate
..
Indexing Databases
..
DOI
کلیک کنید
..
ِDOR
..
Search in website

Advanced Search
..
Receive site information
Enter your Email in the following box to receive the site news and information.
..
:: Volume 10, Issue 3 (10-2021) ::
ieijqp 2021, 10(3): 85-96 Back to browse issues page
Multi-Level Multi-Microgrid Expansion Planning to Enhance Resilience against Seismic Risks Arising from Earthquake
Reza Artis1 , Mojtaba Shivaie * 1, Mohsen Assili1
1- Shahrood University of Technology
Abstract:   (3326 Views)
In today’s industrial world, it is indispensable to strengthen the power distribution network infrastructure against unexpected power losses and financial damages caused by earthquakes. This paper presents a new tri-level framework for multi-microgrid expansion planning (MMEP) against seismic risks stemming from the earthquake in which the lower level describes short-term corrective actions as the distribution network operator (DNO)’s reaction after the seismic risks to apply feeder reconfiguration and generation resource redispatch. The intermediate level meticulously models the destructive effects of seismic risks on the power distribution network components, such as substations, feeders, and distributed energy resources (DERs) through a well-defined seismic scenario generation method (SSGM). In the SSGM, with a new point of view, maximum horizontal ground acceleration is modeled using a reduction procedure in terms of effective seismic parameters, including soil type, seismic magnitude, occurrence depth, and surface distance. Additionally, and more importantly, the probability of complete destruction of the power distribution network components is estimated by predetermined fragility curves. Relying on maximum horizontal ground acceleration and probability of complete destruction, multiple seismic scenarios are generated by maximizing the technical-economic damage subject to structural constraints. Then, the worst-case seismic scenario is selected. In the third level, however, the resilient optimal microgrid expansion plans, as the long-term preventive actions after the seismic risks, are identified. The MMEP objectives, modeled through the third level, are the minimization of the investment and operation costs and maximization of participation profits while satisfying long- and short-term constraints over the planning horizon. A potent melody search algorithm (MSA) is widely employed to solve the proposed large-scale mixed-integer linear tri-level framework. The proposed planning framework is implemented on a standard 9-bus 33-kV test system to demonstrate the feasibility and effectiveness of the newly developed framework. The simulation results corroborate the effective performance of the proposed planning framework in improving the resilience of power distribution networks against seismic risks.
Keywords: Fragility curves, long-term preventive actions, melody search algorithm (MSA), multi-microgrid expansion planning (MMEP), short-term corrective actions.
Full-Text [PDF 892 kb]   (1201 Downloads)    
Type of Study: Research |
Received: 2021/03/19 | Accepted: 2021/06/21 | Published: 2021/06/27
References
1. Bajwa, A. A., Mokhlis, H., Mekhilef, S., & Mubin, M. (2019). Enhancing power system resilience leveraging microgrids: A review, Journal of Renewable and Sustainable Energy, 11(3), 035503. [DOI:10.1063/1.5066264]
2. Bagheria, A., Ghodrati Amirib, G., Khorasanib, M., & Haghdoust, J. (2011). Determination of attenuation relationships using an optimization problem, International Journal of Optimization in Civil Engineering, 1(4), 597-607.
3. Bhusal, N., Abdelmalak, M., Kamruzzaman, M., & Benidris, M. (2020). Power system resilience: Current practices, challenges, and future directions, IEEE Access, 8, 18064-18086. [DOI:10.1109/ACCESS.2020.2968586]
4. Bui, V. H., Hussain, A., & Kim, H. M. (2016). A multiagent-based hierarchical energy management strategy for multi-microgrids considering adjustable power and demand response, IEEE Transactions on Smart Grid, 9(2), 1323-1333. [DOI:10.1109/TSG.2016.2585671]
5. Ding, T., Lin, Y., Bie, Z., & Chen, C. (2017). A resilient microgrid formation strategy for load restoration considering master-slave distributed generators and topology reconfiguration, Applied Energy, vol. 199, 205-216. [DOI:10.1016/j.apenergy.2017.05.012]
6. Falaghi, H., Singh, C., Haghifam, M. R., & Ramezani, M. (2011). DG integrated multistage distribution system expansion planning, International Journal of Electrical Power & Energy Systems, 33(8), 1489-1497. [DOI:10.1016/j.ijepes.2011.06.031]
7. Farzin, H., Fotuhi-Firuzabad, M., & Moeini-Aghtaie, M. (2016). A stochastic multi-objective framework for optimal scheduling of energy storage systems in microgrids, IEEE Transactions on Smart Grid, 8(1), 117-127. [DOI:10.1109/TSG.2016.2598678]
8. Ghaffarpour, R., Jannati Oskuee, M. R., & Ranjbar, A. M. (2020). Resilience-oriented distribution network optimal planning to improve the continuity of power supply, International Journal of Ambient Energy, 41(4), 466-474. [DOI:10.1080/01430750.2018.1451373]
9. Hussain, A., Bui, V. H., & Kim, H. M. (2018). A proactive and survivability-constrained operation strategy for enhancing resilience of microgrids using energy storage system, IEEE Access, 6, 75495-75507. [DOI:10.1109/ACCESS.2018.2883418]
10. Kiani-Moghaddam, M., Shivaie, M., & Weinsier, P. D. (2019). Modern Music-Inspired Optimization Algorithms for Electric Power Systems: Springer. [DOI:10.1007/978-3-030-12044-3]
11. Lin, Y., and Bie, Z. (2018). Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and DG islanding, Applied Energy, 210, 1266-1279. [DOI:10.1016/j.apenergy.2017.06.059]
12. Mousavizadeh, S., Haghifam, M. R., & Shariatkhah, M. H. (2018). A linear two-stage method for resiliency analysis in distribution systems considering renewable energy and demand response resources, Applied Energy, 211, 443-460. [DOI:10.1016/j.apenergy.2017.11.067]
13. Najafi, J., Peiravi, A., & Anvari-Moghaddam, A. (2020). Enhancing Integrated Power and Water Distribution Networks Seismic Resilience Leveraging Microgrids, Sustainability, 12(6), 2167. [DOI:10.3390/su12062167]
14. Najafi, J., Peiravi, A., Anvari-Moghaddam, A., & Guerrero, J. M. (2019). Resilience improvement planning of power-water distribution systems with multiple microgrids against hurricanes using clean strategies, Journal of Cleaner Production, 223, 109-126. [DOI:10.1016/j.jclepro.2019.03.141]
15. Najafi, J., Peiravi, A., & Guerrero, J. M. (2018). Power distribution system improvement planning under hurricanes based on a new resilience index, Sustainable Cities and Society, 39, 592-604. [DOI:10.1016/j.scs.2018.03.022]
16. Nazemi, M., Moeini-Aghtaie, M., Fotuhi-Firuzabad, M., & Dehghanian, P. (2019). Energy storage planning for enhanced resilience of power distribution networks against earthquakes, IEEE Transactions on Sustainable Energy, 11(2), 795-806. [DOI:10.1109/TSTE.2019.2907613]
17. Nikmehr, N., & Ravadanegh, S. N. (2015). Optimal power dispatch of multi-microgrids at future smart distribution grids, IEEE Transactions on Smart Grid, 6(4), 1648-1657. [DOI:10.1109/TSG.2015.2396992]
18. Rastgou, A., Moshtagh, J., & Bahramara, S. (2018). Improved harmony search algorithm for electrical distribution network expansion planning in the presence of distributed generators, Energy,151, 178-202. [DOI:10.1016/j.energy.2018.03.030]
19. Salimi, M., Nasr, M. A., Hosseinian, S. H., Gharehpetian, G. B., & Shahidehpour, M. (2020). Information Gap Decision Theory-Based Active Distribution System Planning for Resilience Enhancement, IEEE Transactions on Smart Grid. [DOI:10.1109/TSG.2020.2992642]
20. Shahbazi, A., Aghaei, J., Pirouzi, S., Niknam, T., Shafie-khah, M., & Catalão, J. P. (2021). Effects of resilience-oriented design on distribution networks operation planning, Electric Power Systems Research,191,106902. [DOI:10.1016/j.epsr.2020.106902]
21. Shahidehpour, M., Ding, T., Ming, Q., Huang, C., Wang, Z., & Du, P. (2020). Multi-Period Active Distribution Network Planning Using Multi-Stage Stochastic Programming and Nested Decomposition by SDDIP, IEEE Transactions on Power Systems. [DOI:10.1109/TPWRS.2020.3032830]
22. Shivaie, M., & Ameli, M. T. (2016). Risk-constrained multi-level framework for coordination of generation and transmission expansion planning in liberalised environments-part I: theory and formulation, IET Generation, Transmission & Distribution, 10(13), 3183-3190. [DOI:10.1049/iet-gtd.2015.1239]
23. Shivaie, M., Ameli, M. T., Sepasian, M. S., Weinsier, P. D., & Vahidinasab, V. (2015). A multistage framework for reliability-based distribution expansion planning considering distributed generations by a self-adaptive global-based harmony search algorithm, Reliability Engineering & System Safety, 139, 68-81. [DOI:10.1016/j.ress.2015.03.001]
24. Shivaie, M., Kiani-Moghaddam, M., and Weinsier, P. D. (2020). A vulnerability-constrained quad-level model for coordination of generation and transmission expansion planning under seismic-and terrorist-induced events, International Journal of Electrical Power & Energy Systems, 120,105958, (1). [DOI:10.1016/j.ijepes.2020.105958]
25. Shivaie, M., Kiani-Moghaddam, M., and Weinsier, P. D. (2020). Resilience-based tri-level framework for simultaneous transmission and substation expansion planning considering extreme weather-related events, IET Generation, Transmission & Distribution, 14(16), 3310-3321, (2). [DOI:10.1049/iet-gtd.2019.1512]
26. Tari, A. N., Sepasian, M. S., and Kenari, M. T. (2021). Resilience assessment and improvement of distribution networks against extreme weather events, International Journal of Electrical Power & Energy Systems,125, 106414. [DOI:10.1016/j.ijepes.2020.106414]
27. Vo Ngoc, D., & Tran Anh, N. (2020). Distribution network reconfiguration for power loss reduction and voltage profile improvement using chaotic stochastic fractal search algorithm, Complexity. [DOI:10.1155/2020/2353901]
28. Xie, H., Teng, X., Xu, Y., and Wang, Y. (2019). Optimal energy storage sizing for networked microgrids considering reliability and resilience, IEEE Access, 7, 86336-86348. [DOI:10.1109/ACCESS.2019.2922994]
29. Xu, G., Shang, C., Fan, S., Hu, X., & Cheng, H. (2017). A hierarchical energy scheduling framework of microgrids with hybrid energy storage systems, IEEE Access, 6, 2472-2483. [DOI:10.1109/ACCESS.2017.2783903]
30. Yuan, W., Wang, J., Qiu, F., Chen, C., Kang, C., & Zeng, B. (2016). "Robust optimization-based resilient distribution network planning against natural disasters, IEEE Transactions on Smart Grid, 7(6), 2817-2826. [DOI:10.1109/TSG.2015.2513048]


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Artis R, Shivaie M, Assili M. Multi-Level Multi-Microgrid Expansion Planning to Enhance Resilience against Seismic Risks Arising from Earthquake. ieijqp 2021; 10 (3) :85-96
URL: http://ieijqp.ir/article-1-818-en.html


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 10, Issue 3 (10-2021) Back to browse issues page
نشریه علمی- پژوهشی کیفیت و بهره وری صنعت برق ایران Iranian Electric Industry Journal of Quality and Productivity
Persian site map - English site map - Created in 0.08 seconds with 40 queries by YEKTAWEB 4645