Abstract
An improved dual grey wolf optimization (GWO) algorithm with binary and dogmatic parts were proposed. The up and down state of units were optimized by binary grey wolf optimization (bGWO), and the exchange velocity was modified by adding two dynamical factors in random number producing. The GWO was used in units’ load scheduling during the process of deciding up-down states and after the solution. One examples with 10 units including 24 period of time was simulated, the results showed the proposed algorithm improved convergence rate and accuracy of the solution.
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Acknowledgements
This work was financially supported by the Innovation Program of Shanghai Municipal Education Commission (Nos. 15ZZ106, 14YZ157), Shanghai Natural Science Foundation (Nos. 12ZR1411600, 14ZR1417200, 15ZR1417300), Climbing Peak Discipline Project of Shanghai Dianji University (No. 15DFXK01).
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Liu, J., Liu, S. (2017). An Improved Dual Grey Wolf Optimization Algorithm for Unit Commitment Problem. In: Yue, D., Peng, C., Du, D., Zhang, T., Zheng, M., Han, Q. (eds) Intelligent Computing, Networked Control, and Their Engineering Applications. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 762. Springer, Singapore. https://doi.org/10.1007/978-981-10-6373-2_16
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DOI: https://doi.org/10.1007/978-981-10-6373-2_16
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