Enhanced Method for Emergency Scheduling of Natural Gas Pipeline Networks Based on Heuristic Optimization
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Jiang, Qiangqiang & Cai, Baoping & Zhang, Yanping & Xie, Min & Liu, Cuiwei, 2023. "Resilience assessment methodology of natural gas network system under random leakage," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
- Zarei, Javad & Amin-Naseri, Mohammad Reza, 2019. "An integrated optimization model for natural gas supply chain," Energy, Elsevier, vol. 185(C), pages 1114-1130.
- Mehmet Fatih Işık & Fatih Avcil & Ehsan Harirchian & Mehmet Akif Bülbül & Marijana Hadzima-Nyarko & Ercan Işık & Rabia İzol & Dorin Radu, 2023. "A Hybrid Artificial Neural Network—Particle Swarm Optimization Algorithm Model for the Determination of Target Displacements in Mid-Rise Regular Reinforced-Concrete Buildings," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
- Bahmani-Firouzi, Bahman & Farjah, Ebrahim & Azizipanah-Abarghooee, Rasoul, 2013. "An efficient scenario-based and fuzzy self-adaptive learning particle swarm optimization approach for dynamic economic emission dispatch considering load and wind power uncertainties," Energy, Elsevier, vol. 50(C), pages 232-244.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Yin, Yue & Liu, Tianqi & He, Chuan, 2019. "Day-ahead stochastic coordinated scheduling for thermal-hydro-wind-photovoltaic systems," Energy, Elsevier, vol. 187(C).
- Hongyan Dui & Xinyue Wang & Haohao Zhou, 2023. "Redundancy-Based Resilience Optimization of Multi-Component Systems," Mathematics, MDPI, vol. 11(14), pages 1-16, July.
- Armioun, Majid & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Siano, Pierluigi, 2023. "Optimal scheduling of CCHP-based resilient energy distribution system considering active microgrids' multi-carrier energy transactions," Applied Energy, Elsevier, vol. 350(C).
- Fitiwi, Desta Z. & Olmos, L. & Rivier, M. & de Cuadra, F. & Pérez-Arriaga, I.J., 2016. "Finding a representative network losses model for large-scale transmission expansion planning with renewable energy sources," Energy, Elsevier, vol. 101(C), pages 343-358.
- Dubey, Hari Mohan & Pandit, Manjaree & Panigrahi, B.K., 2015. "Hybrid flower pollination algorithm with time-varying fuzzy selection mechanism for wind integrated multi-objective dynamic economic dispatch," Renewable Energy, Elsevier, vol. 83(C), pages 188-202.
- Ghasemi, Mojtaba & Ghavidel, Sahand & Ghanbarian, Mohammad Mehdi & Gharibzadeh, Masihallah & Azizi Vahed, Ali, 2014. "Multi-objective optimal power flow considering the cost, emission, voltage deviation and power losses using multi-objective modified imperialist competitive algorithm," Energy, Elsevier, vol. 78(C), pages 276-289.
- Sakib, Nazmus & Ibne Hossain, Niamat Ullah & Nur, Farjana & Talluri, Srinivas & Jaradat, Raed & Lawrence, Jeanne Marie, 2021. "An assessment of probabilistic disaster in the oil and gas supply chain leveraging Bayesian belief network," International Journal of Production Economics, Elsevier, vol. 235(C).
- Chen, J.J. & Zhao, Y.L. & Peng, K. & Wu, P.Z., 2017. "Optimal trade-off planning for wind-solar power day-ahead scheduling under uncertainties," Energy, Elsevier, vol. 141(C), pages 1969-1981.
- Gong, Chengzhu & Wu, Desheng & Gong, Nianjiao & Qi, Rui, 2020. "Multi-agent mixed complementary simulation of natural gas upstream market liberalization in China," Energy, Elsevier, vol. 200(C).
- Gherbi, Yamina Ahlem & Bouzeboudja, Hamid & Gherbi, Fatima Zohra, 2016. "The combined economic environmental dispatch using new hybrid metaheuristic," Energy, Elsevier, vol. 115(P1), pages 468-477.
- Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
- Moradi-Dalvand, M. & Mohammadi-Ivatloo, B. & Amjady, N. & Zareipour, H. & Mazhab-Jafari, A., 2015. "Self-scheduling of a wind producer based on Information Gap Decision Theory," Energy, Elsevier, vol. 81(C), pages 588-600.
- Suganthi, L. & Iniyan, S. & Samuel, Anand A., 2015. "Applications of fuzzy logic in renewable energy systems – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 48(C), pages 585-607.
- Chen, J.J. & Wu, Q.H. & Zhang, L.L. & Wu, P.Z., 2017. "Multi-objective mean–variance–skewness model for nonconvex and stochastic optimal power flow considering wind power and load uncertainties," European Journal of Operational Research, Elsevier, vol. 263(2), pages 719-732.
- Jan Abrell & Friedrich Kunz, 2015.
"Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market,"
Networks and Spatial Economics, Springer, vol. 15(1), pages 117-147, March.
- Jan Abrell & Friedrich Kunz, 2013. "Integrating Intermittent Renewable Wind Generation: A Stochastic Multi-Market Electricity Model for the European Electricity Market," Discussion Papers of DIW Berlin 1301, DIW Berlin, German Institute for Economic Research.
- Wang, Chong & Ju, Ping & Wu, Feng & Lei, Shunbo & Hou, Yunhe, 2021. "Coordinated scheduling of integrated power and gas grids in consideration of gas flow dynamics," Energy, Elsevier, vol. 220(C).
- Zhou, Jian & Coit, David W. & Felder, Frank A. & Tsianikas, Stamatis, 2023. "Combined optimization of system reliability improvement and resilience with mixed cascading failures in dependent network systems," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
- Li, Y.Z. & Wu, Q.H. & Li, M.S. & Zhan, J.P., 2014. "Mean-variance model for power system economic dispatch with wind power integrated," Energy, Elsevier, vol. 72(C), pages 510-520.
- Ji, Bin & Yuan, Xiaohui & Chen, Zhihuan & Tian, Hao, 2014. "Improved gravitational search algorithm for unit commitment considering uncertainty of wind power," Energy, Elsevier, vol. 67(C), pages 52-62.
- Yu, L. & Li, Y.P. & Huang, G.H., 2016. "A fuzzy-stochastic simulation-optimization model for planning electric power systems with considering peak-electricity demand: A case study of Qingdao, China," Energy, Elsevier, vol. 98(C), pages 190-203.
More about this item
Keywords
natural gas supply assurance; emergency scheduling; user satisfaction; user reduction; optimization model;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14383-:d:1251120. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.