Volume 21, Issue 4 (JIAEEE Vol.21 No.4 2024)
Journal of Iranian Association of Electrical and Electronics Engineers 2024, 21(4): 39-47 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Kiani R, Jahanbani F, Mazidi M R. Optimal Stochastic Planning of Microgrid with Considering Resiliency against Hurricanes and Floods. Journal of Iranian Association of Electrical and Electronics Engineers 2024; 21 (4) :39-47
URL: http://jiaeee.com/article-1-1636-en.html
URL: http://jiaeee.com/article-1-1636-en.html
Optimal Stochastic Planning of Microgrid with Considering Resiliency against Hurricanes and Floods
yazd university
Abstract: (900 Views)
With the increasing penetration of distributed generation resources (DERs) in distribution networks, the strategic placement of these resources has garnered increased attention. Due to the uncertain power generation of renewable based DERs, it is necessary to use stochastic models. Additionally, in recent years, due to the rise in the occurrence of weather-related disasters such as hurricanes and floods, leading to serious damages to power grids, the necessity of considering methods to mitigate these damages in installation planning has become crucial.
This study introduces a comprehensive model for optimizing the deployment of distributed renewable (solar and wind) and non-renewable (diesel generator) generation resources, accompanied by energy storage systems (batteries), network reinforcement, and equipment upgrades to enhance its resilience against two specific weather events: hurricanes and floods. The model is applied to the IEEE standard 33-bus network. The planning problem is defined as a costs function while considering the environmental constraints. The optimization problem is structured as a probabilistic programming model and solved using the CPLEX solver in the GAMS software.
The results obtained from case studies on the IEEE standard 33-bus network demonstrate the efficiency of the proposed model in minimizing costs and increasing system resilience.
This study introduces a comprehensive model for optimizing the deployment of distributed renewable (solar and wind) and non-renewable (diesel generator) generation resources, accompanied by energy storage systems (batteries), network reinforcement, and equipment upgrades to enhance its resilience against two specific weather events: hurricanes and floods. The model is applied to the IEEE standard 33-bus network. The planning problem is defined as a costs function while considering the environmental constraints. The optimization problem is structured as a probabilistic programming model and solved using the CPLEX solver in the GAMS software.
The results obtained from case studies on the IEEE standard 33-bus network demonstrate the efficiency of the proposed model in minimizing costs and increasing system resilience.
Keywords: : Optimal Planning, Resiliency, Microgrid, Hardening, Siting and sizing, Uncertainty, Renewable energy resources
Type of Article: Research |
Subject:
Power
Received: 2023/09/8 | Accepted: 2024/04/6 | Published: 2025/01/11
Received: 2023/09/8 | Accepted: 2024/04/6 | Published: 2025/01/11
Extended Abstract [PDF 211 KB] (11 Download)
References
1. [1] F. Mumtaz and I. S. Bayram, "Planning, Operation, and Protection of Microgrids: An Overview", Energy Procedia, vol. 107, pp. 94-100, Feb. 2017. [DOI:10.1016/j.egypro.2016.12.137]
2. [2] P. Singh, M. Pandit, and L. Srivastava, "Multi-objective optimal sizing of hybrid micro-grid system using an integrated intelligent technique", Energy, vol. 269, p. 126756, Apr. 2023. [DOI:10.1016/j.energy.2023.126756]
3. [3] S. Amara, S. Toumi, C. Ben Salah, and A. S. Saidi, "Improvement of techno-economic optimal sizing of a hybrid off-grid micro-grid system", Energy, vol. 233, p. 121166, Oct. 2021. [DOI:10.1016/j.energy.2021.121166]
4. ]4[ امینی‌فر، ف. و فرهومندی، م. "مفاهیم و مبانی ارزیابی تاب آوری در شبکه‌های برق"، مجله انجمن مهندسی برق و الکترونیک ایران- شماره 3، صفحهها 83-92، 1397.
5. [5]. کریمی، م. نجفی روادانق س. حقی فام، م. "چارچوب طراحی شبکه‌های توزیع تاب‌آور در برابر حوادث طبیعی"، مجله انجمن مهندسی برق و الکترونیک ایران- شماره 2، صفحهها 119-129، 1400.
6. [6] 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]
7. [7] X. Wu, Z. Wang, T. Ding, X. Wang, Z. Li, and F. Li, "Microgrid planning considering the resilience against contingencies", IET Gener. Transm. Distrib., vol. 13, no. 16, pp. 3534-3548, 2019. [DOI:10.1049/iet-gtd.2018.6816]
8. [7] حقشناس، مرتضی. هوشمند، رحمت‌االله. قلیپور، مهدی. "برنامه‌ریزی تصادفی بهبود تاب آوری سیستم های توزیع انرژی الکتریکی در مقابل طوفان‌های گرد و غبار شدید"، نشریه مهندسی برق و مهندسی کامپیوتر ایران، شماره 20، شماره صفحهها 108-120، 1401.
9. [9] S. Ma, S. Li, Z. Wang, and F. Qiu, "Resilience-oriented design of distribution systems", IEEE Trans. Power Syst., vol. 34, no. 4, pp. 2880-2891, 2019. [DOI:10.1109/TPWRS.2019.2894103]
10. [10] J. Najafi, A. Peiravi, A. Anvari-Moghaddam, and J. M. Guerrero, "Resilience improvement planning of power-water distribution systems with multiple microgrids against hurricanes using clean strategies", J. Clean. Prod., vol. 223, pp. 109-126, Jun. 2019. [DOI:10.1016/j.jclepro.2019.03.141]
11. [11] H. Zhang, S. Ma, T. Ding, Y. Lin, and M. Shahidehpour, "Multi-Stage Multi-Zone Defender-Attacker-Defender Model for Optimal Resilience Strategy with Distribution Line Hardening and Energy Storage System Deployment", IEEE Trans. Smart Grid, vol. 12, p. 1194-1205, 2020. [DOI:10.1109/TSG.2020.3027767]
12. [12] Y. Wang, Y. Yang, and Q. Xu, "Integrated planning of natural gas and electricity distribution systems for enhancing resilience", Int. J. Electr. Power Energy Syst., vol. 151, p. 109103, 2023. [DOI:10.1016/j.ijepes.2023.109103]
13. [13] M. Ghasemi, A. Kazemi, E. Bompard, and F. Aminifar, "A two-stage resilience improvement planning for power distribution systems against hurricanes", Int. J. Electr. Power Energy Syst., vol. 132, p. 107214, 2021. [DOI:10.1016/j.ijepes.2021.107214]
14. [14] X. Wu, Z. Wang, T. Ding, X. Wang, Z. Li, and F. Li, "Microgrid planning considering the resilience against contingencies", IET Gener. Transm. Distrib., vol. 13, no. 16, pp. 3534-3548, Aug. 2019. [DOI:10.1049/iet-gtd.2018.6816]
15. [15] A. SoltaniNejad Farsangi, S. Hadayeghparast, M. Mehdinejad, and H. Shayanfar, "A novel stochastic energy management of a microgrid with various types of distributed energy resources in presence of demand response programs", Energy, vol. 160, pp. 257-274, Oct. 2018. [DOI:10.1016/j.energy.2018.06.136]
16. [16] N. E. Koltsaklis, M. Giannakakis, and M. C. Georgiadis, "Optimal energy planning and scheduling of microgrids", Chem. Eng. Res. Des., vol. 131, pp. 318-332, 2018. [DOI:10.1016/j.cherd.2017.07.030]
17. [17] S. Bjarnadottir, Y. Li, M. Asce, M. G. Stewart, and M. Asce, "Hurricane risk assessment of power distribution poles considering impacts of a changing climate", J. Infrastruct. Syst., vol. 19, no. 1, pp. 12-24, 2013. [DOI:10.1061/(ASCE)IS.1943-555X.0000108]
18. [18] C. Ozay and M. S. Celiktas, "Statistical analysis of wind speed using two-parameter Weibull distribution in Alaçatı region", Energy Convers. Manag., vol. 121, pp. 49-54, Aug. 2016. [DOI:10.1016/j.enconman.2016.05.026]
Send email to the article author
| Rights and permissions | |
 |
This Journal is an open access Journal Licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. (CC BY NC 4.0) |
