A comparative study of economic load dispatch using sine cosine algorithm

Document Type : Article

Authors

Department of Electrical Engineering, Institute of Technology, Nirma University, SG Highway, Gota Ahmedabad - 382481, India

Abstract

Economic Load Dispatch (ELD) is an important part of cost minimization procedure in power system operation. Different derivative and probabilistic methods are used to solve ELD problems. This paper proposes a powerful Sine Cosine Algorithm (SCA) to explain the ELD issue including equality and inequality restrictions. The main aim of ELD is to satisfy the entire electric load at minimum cost. The SCA is a population based probabilistic method which guides its search agents that are randomly placed in the search space, towards an optimal point using their fitness function and also keeps a track of the best solution achieved by each search agent. SCA is being used to solve the ELD problem with their high exploration and local optima escaping technique. This algorithm confirms that the promising areas of the search space are exploited to have a smooth transition from exploration to exploitation using sine and cosine functions. Simulation results prove that the proposed algorithm surpasses other existing optimization techniques in terms quality of solution obtained and computational efficiency. The final results also prove the robustness of the SCA.

Keywords

References

References:
1. Dhar, R.N. and Mukherjee, P.K. "Reduced-gradient method for economic dispatch", Electrical Engineers, Proceedings of the Institution, 120(5) pp. 608-610 (1973).
2. Aoki, K. and Satoh, T. "Economic dispatch with network security constraints using parametric quadratic programming", IEEE Power Engineering Review, 2(12), pp. 37-38 (1982).
3. El-Keib, AA., Ma, H., and Hart, J.L. "Environmentally constrained economic dispatch using the Lagrangian relaxation method", IEEE Trans Power Syst, 9(4), pp. 1723-1729 (1994).
4. Ching-Tzong, S. and Chien-Tung, L. "New approach with a Hopfield modeling framework to economic dispatch", IEEE Transactions on Power Systems, 15(2), pp. 541-545 (2000).
5. Jabr, R.A., Coonick, A.H., and Cory, B.J. "A homogeneous linear programming algorithm for the security constrained economic dispatch problem", IEEE Transactions on Power Systems, 15(3) pp. 930-936 (2000).
6. Shailti Swamp, K. and Natarajan, A. "Constrained optimization using evolutionary programming for dynamic economic dispatch", Proceedings of 2005 International Conference on Intelligent Sensing and Information Processing, pp. 314-319 (2005).
7. Farooqi, M.R., Jain, P., and Niazi, K.R. "Using Hopfield neural network for economic dispatch of power systems", Proceedings. National Power Engineering Conference, pp. 5-10 (2003).
8. Sheng-Kuan, W., Chih-Wen, L., and Ji-Pyng, C. "Ant direction hybrid differential evolution for solving economic dispatch of power system", 2006 IEEE International Conference on Systems, Man and Cybernetics, 2(1) pp. 1154-1159 (2006).
9. Ali Ahmadi, K., Amir, M., Naser, S., et al "Fuzzy economic dispatch and spinning reserve allocation using evolutionary programming", 2008 40th North American Power Symposium Year, pp. 1-5 (2008).
10. Bavafa, M., Monsef, H., and Navidi, N. "A new hybrid approach for unit commitment using lagrangian relaxation combined with evolutionary and quadratic programming", 2009 Asia-Pacific Power and Energy Engineering Conference, pp. 1-6 (2009).
11. Yongqiang, W., Jianzhong, Z., Wen, X., et al "Economic load dispatch of hydroelectric plant using a hybrid particle swarm optimization combined simulation annealing algorithm", 2010 Second WRI Global Congress on Intelligent Systems, 2(1), pp. 231-234 (2010).
12. Himanshu, A. and Nitin, N. "Civilized swarm optimization for combined heat and power economic emission dispatch", 2016 7th India International Conference on Power Electronics (IICPE), pp. 1-6 (2016).
13. Chaturvedi, K.T., Pandit, M., and Srivastava, L. "Particle swarm optimization with crazy particles for nonconvex economic dispatch", Appl Soft Comput, 9(1), pp. 962-969 (2009).
14. Lu, H., Sriyanyong, P., Song, Y.H., et al "Experimental study of a new hybrid PSO with mutation for economic dispatch with non smooth cost function", Int J Electr Power Energy Syst, 32(1) pp. 921-935 (2010).
15. Taher, N., Farank, G., and Bahman, B. "Modified adaptive PSO algorithm to solve dynamic economic dispatch", 2011 IEEE Power Engineering and Automation Conference, 1(1), pp. 108-111 (2011).
16. King, D.J. and Oezveren Warsono, C.S. "A genetic algorithm based economic dispatch (GAED) with environmental constraint optimisation universities", Power Engineering Conference (UPEC), Proceedings of 2011 46th International, pp. 1-6 (2011).
17. Jamal, S.A and Jan, K.S. "Solving economic dispatch problem using hybrid GA-PS-SQP method", IEEE EUROCON, pp. 333-338 (2009).
18. Amjady, N. and Nasiri-Rad, H. "Solution of nonconvex and non-smooth economic dispatch by a new adaptive real coded genetic algorithm", Expert Syst Appl, pp. 5239-5245 (2009).
19. Hazra, J. and Sinha, A.K. "Environmental constrained economic dispatch using bacteria foraging optimization", 2008 Joint International Conference on Power System Technology and IEEE Power India Conference, pp. 1-6 (2008).
20. Deblina, M., Sumit, B., and Chandan, K.C. "Multiobjective economic emission load dispatch using modified biogeography based optimization algorithm", 2016 IEEE 7th Power India International Conference (PIICON), pp. 1-6 (2016).
21. Nagur, P.N., Shubham, R., and Jadhav, H.T. "Modified artificial bee colony algorithm for non-convex economic dispatch problems", 2012 International Conference on Green Technologies (ICGT), pp. 258-262 (2012).
22. Shaw, B., Mukherjee, V., and Ghoshal, S.P. "Seeker optimisation algorithm: application to the solution of economic load dispatch problems", IET Generation, Transmission & Distribution, 5(1), pp. 81-91 (2011).
23. Rahmat, N.A., Musirin, I., Abidin, A.F., et al. "Economic load dispatch with valve-point loading effect by using differential evolution immunized ant colony optimization technique", 2014 Australasian Universities Power Engineering Conference (AUPEC), pp. 1-6 (2014).
24. Khamsawang, S., Pothiya, S., and Boonseng, C. "Distributed tabu search algorithm for solving the economic dispatch problem", 2004 IEEE Region 10 Conference TENCON 2004, 3(1), pp. 484-487 (2004).
25. Bhattacharjee, K. "Economic dispatch problems using backtracking search optimization", International Journal of Energy Optimization and Engineering, IGIGlobal, 7(2) pp. 39-60 (2018).
26. Bhattacharjee, K., Bhattacharya, A., and Halder, S. "Teaching learning based optimization for different economic dispatch problems", International Journal of Science and Technology, 21(3), pp. 870-884 (2014).
27. Roy, S. and Bhattacharjee, K. "The use of krill herd based optimization to solve complex economic load dispatch problems", 2017 Conference on Emerging Devices and Smart Systems (ICEDSS), pp. 72-78 (2017).
28. Zarei, E., Hemmatpour, M., and Mohammadian, M. "The effects of demand response on securityconstrained unit commitment", Scientia Iranica, 26(3), pp. 1627-1636 (2019). DOI: 10.24200/sci.2017.4536.
29. Sandeep, K. and Shushil, P. "A novel sine cosine algorithm for the solution of unit commitment problem", International Journal of Science, Engineering and Technology Research (IJSETR), 5(12), pp. 3298- 3310 (2016).
30. Mohamed, A.T. and Vimal, S. "Multi-objective sinecosine algorithm (MO-SCA) for multi-objective engineering design problems", Neural Computing and Applications, 31(4), pp. 1-15 (2017).
31. Sujoy, D., Bhattacharya, A., and A Kumar, C. "Solution of short-term hydrothermal scheduling using sine cosine algorithm", Soft Computing, 22, pp. 6409-6427 (2018). https://doi.org/10.1007/s00500-017-2695-3.
32. Quande, Q., Cheng, S., and Xianghua, C. "Solving non-convex/non-smooth economic load dispatch problems via an enhanced particle swarm optimization", Applied Soft Computing, 59(1), pp. 229-242 (2017).
33. Sanjoy, R. "The maximum likelihood optima for an economic load dispatch in presence of demand and generation variability", Energy, 147(1), pp. 915-923 (2018).
34. Roy, S., Bhattacharjee, K., and Bhattacharya, A. "A modern approach to solve of economic load dispatch using group leader optimization technique", International Journal of Energy Optimization and Engineering, IGI-Global., 6(1), pp. 66-85 (2016).
35. Seyedali, M. "SCA: A sine cosine algorithm for solving optimization problems", Knowledge-Based Systems, 96, pp. 120-133 (2016).
36. Bhattacharjee, K., Bhattacharya, A., and Halder, S. "Chemical reaction optimisation for different economic dispatch problems", IET Generation Transmission Distribution, 8(3), pp. 530-541 (2014).
37. Srinivasa, R.A. and Vaisakh, K. "Shuffled differential evolution for large scale economic dispatch", Electric Power Syst Res, 96, pp. 237-245 (2013).
38. Sinha, N., Chakrabarti, R., and Chattopadhyay, P.K. "Evolutionary programming techniques for economic load dispatch", IEEE Trans Evol Comput, 7(1), pp. 83-94 (2003).
39. Bhattacharjee, K., Bhattacharya, A., and Sunita, H. "Oppositional real coded chemical reaction optimization for different economic dispatch problems", Electrical Power and Energy Systems, 55, pp. 378-391 (2014).
40. Barisal, A.K. and Prusty, R.C. "Large scale economic dispatch of power systems using oppositional invasive weed optimization", Applied Soft Computing, 29, pp. 122-137 (2015).
41. Duman, S., Yorukeren, N., and Altas, I.H. "A novel modified hybrid PSOGSA based on fuzzy logic for nonconvex economic dispatch problem with valve-point effect", Electrical Power and Energy Systems, 64, pp. 121-135 (2015).
42. Sydulu, M. "A very fast and effective non-iterative lambda logic based", Algorithm for Economic Dispatch of Thermal Units, in Proc. IEEE Region 10 Conf. TENCON, 2(1), pp. 1434-1437 (1999).
43. Bhattacharya, A. and Chattopadhyay, P.K. "Hybrid differential evolution with biogeography-based optimization for solution of economic load dispatch", IEEE Trans. Power Syst., 25(4), pp. 1955-1964 (2004).
44. Ciornei, I. and Kyriakides, E. "Efficient hybrid optimization solution for the economic dispatch with nonsmooth cost function", Proc IEEE Power Tech. Bucharest, Romania, 2(1), pp. 1-7 (2009).
45. Jong-Bae, P., Yun-Won, J., and Joong-Rin, S. "An improved particle swarm optimization for nonconvex economic dispatch problems", IEEE Transactions on Power Systems, 25(1), pp. 156-166 (2010).
Scientia Iranica
Volume 27, Issue 3
Transactions on Computer Science & Engineering and Electrical Engineering (D)
June 2020
Pages 1467-1480

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