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All issues Volume 184 (2020) E3S Web Conf., 184 (2020) 01070 References
Open Access
Issue
E3S Web Conf.
Volume 184, 2020
2nd International Conference on Design and Manufacturing Aspects for Sustainable Energy (ICMED 2020)
Article Number 01070
Number of page(s) 8
DOI https://doi.org/10.1051/e3sconf/202018401070
Published online 19 August 2020
  1. J.S. Dhaliwal and J.S. Dhillon, “Profit based unit commitment using memetic binary differential evolution algorithm,” Appl. Soft Comput. J., p. 105502, 2019. [Google Scholar]
  2. A. Nandi and V.K. Kamboj, “Hgwo-RES : A Hybrid Algorithm with Improved Exploitation Capability For Profit Based Unit Commitment Problem,” no. 16, pp. 4731-4741, 2019. [Google Scholar]
  3. S. Reddy K, L.K. Panwar, B.K. Panigrahi, R. Kumar, and A. Alsumaiti, “Binary grey wolf optimizer models for profit based unit commitment of price-taking GENCO in electricity market,” Swarm Evol. Comput., 2018. [Google Scholar]
  4. K.S. Reddy, L. Kumar, R. Kumar, and B.K. Panigrahi, “Electrical Power and Energy Systems Binary fireworks algorithm for profit based unit commitment (PBUC ) problem,” Int. J. Electr. POWER ENERGY Syst., Vol. 83, pp. 270-282, 2016. [CrossRef] [Google Scholar]
  5. S.R. K, L.K. Panwar, B.K. Panigrahi, R. Kumar, and A. Alsumaiti, “SC,” Swarm Evol. Comput. BASE DATA, 2018. [Google Scholar]
  6. A. Shukla, V.N. Lal, S. Members, S.N. Singh, and S. Member, “Profit-Based Unit Commitment Problem Using PSO with Modified Dynamic Programming,” pp. 1-6, 2015. [Google Scholar]
  7. K. Venkatesan, G. Selvakumar, and C.C.A. Rajan, “EP BASED PSO METHOD FOR SOLVING PROFIT BASED MULTI AREA UNIT COMMITMENT PROBLEM,” vol. 10, no. 4, pp. 442-460, 2015. [Google Scholar]
  8. G. Morales-españa, A. Ramos, and C. Gentile, “Tight MIP formulations of the power-based unit commitment problem,” OR Spectr., Vol. 37, no. 4, pp. 929-950, 2015. [Google Scholar]
  9. S. Maghsudlu and S. Mohammadi, “Optimal scheduled unit commitment considering suitable power of electric vehicle and Optimal scheduled unit commitment considering suitable power of electric vehicle and photovoltaic uncertainty,” vol. 043705, 2018. [Google Scholar]
  10. M. Shahbazitabar and H. Abdi, “AC,” Energy, 2018. [Google Scholar]
  11. F. Rahiman, P. Mohd, F. Othman, and S. Ottukuloth, “Power Station Scheduling with Energy Storage,” J. Inst. Eng. Ser. B, 2018. [Google Scholar]
  12. Yogeswara Reddy B, Srinivas Rao J, Suresh Kumar T, Nagarjuna A, Int. J. of Inn. Tech. and Exp. Engg., vol. 8, no.11, pp:1194-1198, 2019 [Google Scholar]
  13. H. Quan, D. Srinivasan, and A. Khosravi, “Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk : A comparative study,” Energy, Vol. 103, pp. 735-745, 2016. [CrossRef] [Google Scholar]
  14. S.Y. Abujarad, M.W. Mustafa, and J.J. Jamian, “crossmark,” Renew. Sustain. Energy Rev., Vol. 70, no. November 2016, pp. 215-223, 2017. [CrossRef] [Google Scholar]
  15. K. Selvakumar, B. Vignesh, C.S. Boopathi, and T. Kannan, “Thermal Unit Commitment Strategy Integrated with Solar Energy System,” vol. 11, no. 9, pp. 6856-6860, 2016. [Google Scholar]
  16. E.A. Jasmin, G.E. College, and G.E. College, “A FUNCTION APPROXIMATION APPROACH TO REINFORCEMENT LEARNING FOR SOLVING UNIT COMMITMENT PROBLEM WITH PHOTO VOLTAIC SOURCES.” [Google Scholar]
  17. H. Quan, D. Srinivasan, A.M. Khambadkone, and A. Khosravi, “A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources,” Appl. Energy, Vol. 152, pp. 71-82, 2015. [Google Scholar]
  18. K. Chandrasekaran and S.P. Simon, “Binary / Real Coded Particle Swarm Optimization for Unit Commitment Problem,” no. 3. [Google Scholar]
  19. T. Senjyu, S. Chakraborty, A.Y. Saber, H. Toyama, and A. Yona, “Thermal Unit Commitment Strategy with Solar and Wind Energy Systems Using Genetic Algorithm Operated Particle Swarm Optimization,” no. PECon 08, pp. 866-871, 2008. [Google Scholar]
  20. S. Saurabh and M. Ahmed, Optimization Method for Unit Commitment in High-Level Wind Generation and Solar Power. Springer Singapore. [Google Scholar]
  21. A. Safari and H. Shahsavari, “Frequency-constrained unit commitment problem with considering dynamic ramp rate limits in the presence of wind power generation,” Neural Comput. Appl., Vol. 0123456789, 2018. [Google Scholar]
  22. M.P. Varghese and A. Amudha, “Artificial Bee Colony and Cuckoo Search Algorithm for Cost Estimation with Wind Power Energy,” pp. 1-8. [Google Scholar]
  23. [M. Govardhan, R. Roy, M. Govardhan, and R. Roy, “Electric Power Components and Systems Comparative Analysis of Economic Viability with Distributed Energy Resources on Unit Commitment Comparative Analysis of Economic Viability with Distributed Energy Resources on Unit Commitment,” vol. 5008, no. August, 2016. [Google Scholar]
  24. V.K. Kamboj, A. Nandi, A. Bhadoria, and S. Sehgal, “An intensify Harris Hawks optimizer for numerical and engineering optimization problems,” Appl. Soft Comput., p. 106018, 2019. [Google Scholar]

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