Teaching–learning-based optimization algorithm for multi-area economic dispatch
Author
Abstract
Suggested Citation
DOI: 10.1016/j.energy.2014.02.064
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Nwulu, Nnamdi I. & Xia, Xiaohua, 2015. "Implementing a model predictive control strategy on the dynamic economic emission dispatch problem with game theory based demand response programs," Energy, Elsevier, vol. 91(C), pages 404-419.
- Mohammadian, M. & Lorestani, A. & Ardehali, M.M., 2018. "Optimization of single and multi-areas economic dispatch problems based on evolutionary particle swarm optimization algorithm," Energy, Elsevier, vol. 161(C), pages 710-724.
- Chen, Xu & Lu, Qi & Yuan, Ye & He, Kaixun, 2024. "A novel derivative search political optimization algorithm for multi-area economic dispatch incorporating renewable energy," Energy, Elsevier, vol. 300(C).
- Secui, Dinu Calin, 2015. "The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch," Energy, Elsevier, vol. 93(P2), pages 2518-2545.
- Chen, Xu & Tang, Guowei, 2022. "Solving static and dynamic multi-area economic dispatch problems using an improved competitive swarm optimization algorithm," Energy, Elsevier, vol. 238(PC).
- Meng, Anbo & Zeng, Cong & Xu, Xuancong & Ding, Weifeng & Liu, Shiyun & Chen, De & Yin, Hao, 2022. "Decentralized power economic dispatch by distributed crisscross optimization in multi-agent system," Energy, Elsevier, vol. 246(C).
- Ghasemi, Mojtaba & Aghaei, Jamshid & Akbari, Ebrahim & Ghavidel, Sahand & Li, Li, 2016. "A differential evolution particle swarm optimizer for various types of multi-area economic dispatch problems," Energy, Elsevier, vol. 107(C), pages 182-195.
- Narimani, Hossein & Razavi, Seyed-Ehsan & Azizivahed, Ali & Naderi, Ehsan & Fathi, Mehdi & Ataei, Mohammad H. & Narimani, Mohammad Rasoul, 2018. "A multi-objective framework for multi-area economic emission dispatch," Energy, Elsevier, vol. 154(C), pages 126-142.
- Modiri-Delshad, Mostafa & Rahim, Nasrudin Abd, 2014. "Solving non-convex economic dispatch problem via backtracking search algorithm," Energy, Elsevier, vol. 77(C), pages 372-381.
- Ouyang, Hai-bin & Gao, Li-qun & Kong, Xiang-yong & Zou, De-xuan & Li, Steven, 2015. "Teaching-learning based optimization with global crossover for global optimization problems," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 533-556.
- Sharifian, Yeganeh & Abdi, Hamdi, 2024. "Multi-area economic dispatch problem: Methods, uncertainties, and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
- Lin, Jian & Wang, Zhou-Jing, 2019. "Multi-area economic dispatch using an improved stochastic fractal search algorithm," Energy, Elsevier, vol. 166(C), pages 47-58.
- Sharifian, Yeganeh & Abdi, Hamdi, 2023. "Solving multi-area economic dispatch problem using hybrid exchange market algorithm with grasshopper optimization algorithm," Energy, Elsevier, vol. 267(C).
- Guojiang Xiong & Jing Zhang & Xufeng Yuan & Dongyuan Shi & Yu He & Yao Yao & Gonggui Chen, 2018. "A Novel Method for Economic Dispatch with Across Neighborhood Search: A Case Study in a Provincial Power Grid, China," Complexity, Hindawi, vol. 2018, pages 1-18, November.
- Elattar, Ehab E., 2019. "Environmental economic dispatch with heat optimization in the presence of renewable energy based on modified shuffle frog leaping algorithm," Energy, Elsevier, vol. 171(C), pages 256-269.
- Secui, Dinu Calin, 2016. "A modified Symbiotic Organisms Search algorithm for large scale economic dispatch problem with valve-point effects," Energy, Elsevier, vol. 113(C), pages 366-384.
- Meng, Anbo & Xu, Xuancong & Zhang, Zhan & Zeng, Cong & Liang, Ruduo & Zhang, Zheng & Wang, Xiaolin & Yan, Baiping & Yin, Hao & Luo, Jianqiang, 2022. "Solving high-dimensional multi-area economic dispatch problem by decoupled distributed crisscross optimization algorithm with population cross generation strategy," Energy, Elsevier, vol. 258(C).
- Xu, Shengping & Xiong, Guojiang & Mohamed, Ali Wagdy & Bouchekara, Houssem R.E.H., 2022. "Forgetting velocity based improved comprehensive learning particle swarm optimization for non-convex economic dispatch problems with valve-point effects and multi-fuel options," Energy, Elsevier, vol. 256(C).
More about this item
Keywords
Multi-area economic dispatch; Tie line constraints; Teaching–learning-based optimization;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:eee:energy:v:68:y:2014:i:c:p:21-28. 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.
We have no bibliographic references for this item. You can help adding them by using 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.