Open Access
Issue |
MATEC Web Conf.
Volume 214, 2018
2018 2nd International Conference on Information Processing and Control Engineering (ICIPCE 2018)
|
|
---|---|---|
Article Number | 03007 | |
Number of page(s) | 6 | |
Section | Electronic Information Technology and Control Engineering | |
DOI | https://doi.org/10.1051/matecconf/201821403007 | |
Published online | 15 October 2018 |
- G. Zwe-Lee, “Particle swarm optimization to solving the economic dispatch considering the generator constraints,” IEEE Transactions on Power Systems, Vol. 18, pp. 1187–1195, 2003. [Google Scholar]
- S. Rastgoufard, S. Iqbal, M. T. Hoque, and D. Charalampidis, “Genetic algorithm variant based effective solutions for economic dispatch problems,” in 2018 IEEE Texas Power and Energy Conference (TPEC), 2018, pp. 1–6. [Google Scholar]
- M. Modiri-Delshad, S. H. Aghay Kaboli, E. Taslimi-Renani, and N. A. Rahim, “Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options,” Energy, Vol. 116, pp. 637–649, 2016/12/01/ 2016. [CrossRef] [Google Scholar]
- M. H. Sulaiman and M. R. Mohamed, “Solving economic dispatch problems utilizing Cuckoo Search algorithm,” in 2014 IEEE 8th International Power Engineering and Optimization Conference (PEOCO2014), 2014, pp. 89–93. [CrossRef] [Google Scholar]
- X.-S. Yang, S. S. Sadat Hosseini, and A. H. Gandomi, “Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect,” Applied Soft Computing, Vol. 12, pp. 1180–1186, 2012/03/01/ 2012. [Google Scholar]
- M. H. Sulaiman, H. Daniyal, and M. W. Mustafa, “Modified Firefly Algorithm in solving economic dispatch problems with practical constraints,” in 2012 IEEE International Conference on Power and Energy (PECon), 2012, pp. 157–161. [Google Scholar]
- L. I. Wong, M. H. Sulaiman, M. R. Mohamed, and M. S. Hong, “Grey Wolf Optimizer for solving economic dispatch problems,” in 2014 IEEE International Conference on Power and Energy (PECon), 2014, pp. 150–154. [CrossRef] [Google Scholar]
- S. Vijayaraj and R. K. Santhi, “Multi-area economic dispatch using flower pollination algorithm,” in 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), 2016, pp. 4355–4360. [CrossRef] [Google Scholar]
- F. Mohamed, M. Abdel-Nasser, K. Mahmoud, and S. Kamel, “Economic dispatch using stochastic whale optimization algorithm,” in 2018 International Conference on Innovative Trends in Computer Engineering (ITCE), 2018, pp. 19–24. [CrossRef] [Google Scholar]
- H. Lotfi, A. Dadpour, and M. Samadi, “Solving economic dispatch in competitive power market using improved particle swarm optimization algorithm,” in 2017 Conference on Electrical Power Distribution Networks Conference (EPDC), 2017, pp. 188–195. [CrossRef] [Google Scholar]
- K. Zare and T. G. Bolandi, “Modified iteration particle swarm optimization procedure for economic dispatch solving with non-smooth and non-convex fuel cost function,” in 3rd IET International Conference on Clean Energy and Technology (CEAT) 2014, 2014, pp. 1–6. [Google Scholar]
- S. Chansareewittaya, “Hybrid BA/TS for economic dispatch considering the generator constraint,” in 2017 International Conference on Digital Arts, Media and Technology (ICDAMT), 2017, pp. 115–119. [CrossRef] [Google Scholar]
- S. Mirjalili, “Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm,” Knowledge-Based Systems, Vol. 89, pp. 228–249, 2015/11/01/ 2015. [Google Scholar]
- C. Po-Hung and C. Hong-Chan, “Large-scale economic dispatch by genetic algorithm,” IEEE Transactions on Power Systems, Vol. 10, pp. 1919–1926, 1995. [CrossRef] [Google Scholar]
- C.-C. Kuo, “A novel string structure for economic dispatch problems with practical constraints,” Energy Conversion and Management, Vol. 49, pp. 3571–3577, 2008/12/01/ 2008 [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.