Dynamic economic dispatch to meet the energy demand using improved artificial bee colony considering practical constrains

Abstract

Abstract: One of the most important issues in power systems is providing the optimal demand for electrical energy’s customers with minimal costs. This goal with non-convex formulation in real-time will be difficult to solve. In this paper, the optimal appropriation of power plants during 24 hours of a day is formulated as an optimization problem which solved by a new modified optimization algorithm. The objective is finding the optimal schedule of the online power plants over a especial time horizon while satisfy the generation unit and ramp-rate constraints. The proposed optimization algorithm work based on the guidance of best solution in the each iteration to enhance searching progress in local and global domains. In addition, by using the chaos theory the local search is enhanced. Also, effect of wind turbine with considering wind speed is investigated in the DED problem solution. The effectiveness of the proposed algorithm is demonstrated on 10-unit, 30-unit, 54-unit and 5-unit with wind power system for a period of 24 hours. The simulation results obtained by the proposed MABC algorithm are compared with the available results for other methods in the literature. In terms of solution quality, the proposed algorithm is found to be better compared to other algorithms.

Keywords


[1] H. Khorramdel, B. Khorramdel, M. Tayebi Khorrami, and H. Rastegar, “A multi-objective economic load dispatch considering accessibility of wind power with here-and-now approach,” Journal of Operation and Automation in Power Engineering, vol. 2, no. 1, pp. 49-59, 2014.
[2] X. Yan, and V. H. Quintana, “An efficient predictor-corrector interior point algorithm for security-constrained economic dispatch,” IEEE Trans. on Power Systems, vol. 12, pp. 803-810, 1997.
[3] G. C. Contaxis, C. Delkis, and G. Kerres, “Decoupled optimal load flow using linear or quadratic programming,” IEEE Trans. on Power Systems, vol. 1, no. 2, pp 1-7, 1986.
[4] A. A. El-Keib, and H. Ding, “Environmentally constrained economic dispatch using linear programming,” Electric Power System Research, vol. 29, pp. 155-159, 1994.
[5] H. Shayeghi, and A. Ghasemi, “A modified artificial bee colony based on chaos theory for solving non-convex emission/economic dispatch,” Energy Conversion and Management, vol. 79, pp. 344-354, 2014.
[6] Y. Chen, J. Wen, L. Jiang, and S. Cheng, “Hybrid algorithm for dynamic economic dispatch with valve-point effects,” IET Gener. Transm. Distrib., vol. 7, no. 10, pp. 1096-1104, 2013.
[7] T. Niknam, R. Azizipanah-Abarghooee, and J. Aghaei, “A new modified teaching-learning algorithm for reserve constrained dynamic economic dispatch,” IEEE Trans. on Power Systems, vol. 28, no. 2, 749-763, 2013.
[8] R. Arul, G. Ravi, and S. Velusami, “Chaotic self-adaptive differential harmony search algorithm based dynamic economic dispatch,” Electrical Power and Energy Systems, vol. 50, pp. 85-96, 2013.
[9] K. Vaisakh, P. Praveena, S. R. Mohana Rao, and K. Meah, “Solving dynamic economic dispatch problem with security constraints using bacterial foraging PSO-DE algorithm,” Electrical Power and Energy Systems, vol. 39, pp. 56-67, 2012.

[10]پدرام شهریاری­نسب، معین پرستگاری و مهدی معلم، «استفاده از الگوریتم زنبورهای عسل برای بهینه‌سازی سیستم‌های انتقال توان بدون تماس به روش القایی برای شارژ خودروهای الکتریکی،» مجله مهندسی برق دانشگاه تبریز، دوره 43، شماره 2، ص 9-20، 1392.

[11] X. Yan, and V. H. Quintana, “An Efficient Predictor-Corrector Interior Point Algorithm for Security-Constrained Economic Dispatch,” IEEE Trans. on Power Systems, vol. 12, pp. 803-10, 1997.
[12] M. Basu, “Dynamic economic emission dispatch using non dominated sorting genetic algorithm-II,” Electrical Power and Energy Systems, vol. 30, pp. 140-149, 2008.
[13] N. Pandita, A. Tripathia, S. Tapaswia, and M. Pandit, “An improved bacterial foraging algorithm for combined static/dynamic environmental economic dispatch,” Applied Soft Computing, vol. 12, pp. 3500-3513, 2012.
[14] Y. Lu, et al., “Chaotic differential evolution methods for dynamic economic dispatch with valve-point effects,” Engineering Application of Artificial Intelligence, vol. 24, pp. 378-387, 2011.
[15] T. Victoire, and A. E. Jeyakumar, “A modified hybrid EP–SQP approach for dynamic dispatch with valve-point effect,” Electrical Power and Energy Systems, vol. 27, pp. 594-601, 2005.
[16] X. Yuan, et al., “An improved PSO for dynamic load dispatch of generators with valve-point effects,” Energy, vol. 34, pp. 67-74, 2009.
[17] P. Lu, et al., “Chaotic differential bee colony optimization algorithm for dynamic economic dispatch problem with valve-point effects,” Electrical Power and Energy Systems, vol. 62, pp. 130-143, 2014.
[18] M. Shahidehpour, [Online], Available online at: motor.ece.iit.edu/data/SCUC_118test.xls, 2011.
[19] B. Mohammadi-Ivatloo, A. Rabiee, A. Soroudi, and M. Ehsan, “Imperialist competitive algorithm for solving non-convex dynamic economic power dispatch,” Energy, vol. 44, pp. 228-240, 2012.
[20] M. Marzband, A. Sumper, A. Ruiz-Álvarez, J. L. Domínguez-García, and B. Tomoiag˘a, “Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets,” Applied Energy, vol. 106, pp. 365-76, 2013.
[21] S. P. Agrawal, K. B. Porate, and G. H. Raisoni, “College of Engg. Economic Dispatch of Thermal Units with the Impact of Wind Power plant,” Third International Conference on Emerging Trends in Engineering and Technology, pp. 48- 53, 2010.

[22] مهدی دارابی، سعید اباذری و جعفر سلطانی، «بررسی تأثیر پارکینگ‌های هوشمند بر تأمین توان راکتیو در شبکه‌های هوشمند با نیروگاه بادی بر اساس کنترل‌کننده غیرخطی مدلغزشی،» مجله مهندسی برق دانشگاه تبریز، دوره 45، شماره 1، ص 11-20، 1394.