Solving Problem of Unit Commitment by Exchange Market Algorithm and Dynamic Planning Method
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-25252-5_96
Reference26 articles.
1. Abujarad, S.Y., Mustafa, M.W., Jamian, J.J: Recent approaches of unit commitment in the presence of intermittent renewable energy resources: a review. Renew. Sustain. Energy Rev. 70, 215–223 (2017). https://doi.org/10.1016/j.rser.2016.11.246
2. Farhat, A., El-Hawary, M.E.: Optimization methods applied for solving the short-term hydrothermal coordination problem. Electr. Power Syst. Res. 79(9), 1308–1320 (2009). https://doi.org/10.1016/j.epsr.2009.04.001
3. Yang, L., Zhang, C., Jian, J., Meng, K., Xu, Y., Dong, Z.: A novel projected two-binary-variable formulation for unit commitment in power systems. Appl. Energy 187, 732–745 (2017). https://doi.org/10.1016/j.apenergy.2016.11.096
4. Hua, B., Baldick, R., Wang, J.: Representing operational flexibility in generation expansion planning through convex relaxation of unit commitment. IEEE Trans. Power Syst. 33(2), 2272–2281 (2018). https://doi.org/10.1109/tpwrs.2017.2735026
5. Reddy, K.S., Panwar, L.K., Panigrahi, B.K., Kumar, R.: Solution to unit commitment in power system operation planning using binary coded modified moth flame optimization algorithm (BMMFOA): a flame selection based computational technique. J. Comput. 25, 298–317 (2018). https://doi.org/10.1016/j.jocs.2017.04.011
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