Gravitational search algorithm-based dynamic economic dispatch by estimating transmission system losses using A-loss coefficients

Gravitational search algorithm-based dynamic economic dispatch by estimating transmission system losses using A-loss coefficients

Dynamic economic dispatch (DED) is an important problem in power system generation, operation, planning, and control. The objective of the DED problem is to schedule power generation for the online units over a time horizon, satisfying the unit and ramp rate constraints. Here, valve point loading effects that cause nonsmoothness of the objective function is also considered while solving the DED. The accuracy of the solution not only depends on the optimal scheduling of generating units, but it also lies in accuracy while estimating transmission system losses. Generally, B-loss coefficients are used in estimating transmission losses. However, in the literature, A-loss coefficients are found to be at par with B-loss coefficients in estimating transmission system losses. Therefore, in this paper, the performance in estimating the transmission system losses using A-loss coefficients are investigated through the solution of the DED problem. Here, a recently evolved heuristic search technique called the gravitational search algorithm is used for solving the DED. The feasibility of the proposed method is tested and validated on standard benchmark test systems such as the IEEE 30-bus system, IEEE 39-bus system, and IEEE 118-bus system. All simulations are carried out using SCILAB 5.4 (www.scilab.org), which is open-source software.

___

  • [1] Chandram K, Subrahmanyam N, Sydulu M. Brent method for dynamic economic dispatch with transmission losses. In: IEEE 2008 Power Engineering Society Transmission Distribution Conference and Exposition; 21–24 April 2008; Chicago, IL, USA. pp. 1-5.
  • [2] Han XS, Gooi HB, Kirschen DS. Dynamic economic dispatch: Feasible and optimal solutions. IEEE T Power Syst 2001; 16: 22-28.
  • [3] Manoharan PS, Kannan P, Baskar S, Irudhayarajan MW, Dhananjeyan V. Covariance matrix adapted evolution strategy algorithm- based solution to dynamic economic dispatch problems. Eng Optimiz 2009; 41: 635-657.
  • [4] Hemamalini S, Simon SP. Dynamic economic dispatch using artificial immune system for units with valve-point effect. Int J Elec Power 2011; 33: 868-874.
  • [5] Wood AJ, Wollenberg BF. Power Generation Operation and Control. 2nd ed. New York, NY, USA: Wiley, 1996.
  • [6] Victoire TAA, Jeyakumar AE. A modified hybrid EP–SQP approach for dynamic economic dispatch with valvepoint effect. Int J Elec Power 2007; 27: 594-601.
  • [7] Sinha N, Chakrabarti R, Chattopadhyay PK. Evolutionary programming techniques for economic load dispatch. IEEE T Evolut Comput 2003; 7: 83-94.
  • [8] Pereira-Neto A, Unsihuay C, Saavedra OR. Efficient evolutionary strategy optimization procedure to solve the nonconvex economic dispatch problem with generator constraints. IEE P-Gener Transm D 2005; 152: 653-660.
  • [9] Wang Y, Zhou J, Qiu H, Lu Y. Improved chaotic particle swarm optimization algorithm for dynamic economic dispatch problem with valve-point effects. Energ Convers Manage 2010; 51: 2893-2900.
  • [10] Attaviriyanupap P, Kita H, Tanaka E, Hasegawa J. A hybrid EP and SQP for dynamic economic dispatch with nonsmooth fuel cost function. IEEE T Power Syst 2002; 17: 411-416.
  • [11] Lee JC, Lin WM, Liao GC, Tsao TP. Quantum genetic algorithm for dynamic economic dispatch with valve-point effects and including wind power system. Int J Elec Power 2011; 33: 189-197.
  • [12] Ongsakul W, Rungpayoonsak N. Constrained dynamic economic dispatch by simulated annealing/genetic algorithm. In: IEEE 2001 Power Industry Computer Applications Conference; 20–24 May 2001; Sydney, Australia. pp. 207-212.
  • [13] Panigrahi CK, Chattopadhyay PK, Chakrabarti RN, Basu M. Simulated annealing technique for dynamic economic dispatch. Electr Pow Compo Sys 2006; 34: 577-586.
  • [14] Basu M. Artificial immune system for dynamic economic dispatch. Int J Elec Power 2011; 33: 131-136.
  • [15] Hemamalini S, Simon SP. Dynamic economic dispatch using artificial bee colony algorithm for units with valve-point effect. Eur T Electr Power 2011; 21: 70-81.
  • [16] Mohammadi-Ivatloo B, Rabiee A, Soroudi A, Ehsan M. Imperialist competition algorithm for solving non-convex dynamic economic power dispatch. Energy 2012; 44: 228-240.
  • [17] Balamurugan R, Subramanian S. Differential evolution-based dynamic economic dispatch of generating units with valve-point effects. Electr Pow Compo Sys 2008; 36: 828-843.
  • [18] He D, Dong G, Wang F, Mao Z. Optimization of dynamic economic dispatch with valve-point effect using chaotic sequence based differential evolution algorithms. Energ Convers Manage 2011; 52: 1026-1032.
  • [19] Rashedi E, Nezamabadi-pour H, Saryazdi S. GSA: a gravitational search algorithm. Inform Sciences 2009; 179: 2232-2248.
  • [20] Duman S, G¨uven¸c U, Y¨or¨ukeren N. Gravitational search algorithm for economic dispatch with valve-point effects. Int Rev Electr Eng-I 2010; 5: 2890-2895.
  • [21] G¨uven¸c U, S¨onmez Y, Duman S, Y¨or¨ukeren N. Combined economic and emission dispatch solution using gravitational search algorithm. Sci Iran 2012; 19: 1754-1762.
  • [22] Shaw B, Mukherjee V, Ghoshal SP. A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems. Int J Elec Power 2012; 35: 21-33.
  • [23] Swain RK, Meher KC, Mishra UC. Dynamic economic dispatch using hybrid gravitational search algorithm. In: IEEE 2012 Power, Control and Embedded Systems Conference; 17–19 December 2012; Allahabad, India. pp. 1-6.
  • [24] Saadat H. Power System Analysis. 1st ed. New York, NY, USA: McGraw-Hill, 1999.
  • [25] Nanda J, Lai LL, Ma JT, Rajkumar N, Nanda A, Prasad M. A novel approach to computationally efficient algorithms for transmission loss and line flow formulations. Int J Elec Power 1999; 21: 555-560.
  • [26] Ziari I, Jadid S, Jalilian A. A new method for modelling loss in a distribution network. In: IEEE 2006 Universities Power Engineering Conference; 6–8 September 2006; Newcastle, UK. pp. 393-397.
  • [27] Nanda J, Narayanan RB. Application of genetic algorithm to economic load dispatch with line flow constraint. Int J Elec Power 2002; 24: 723-729.
  • [28] Chandrasekaran K, Simon SP. Fuzzified artificial bee colony algorithm for nonsmooth and nonconvex multiobjective economic dispatch problem. Turk J Electr Eng Co 2013; 21: 1995-2014.
  • [29] Shahidehpour M, Wang Y. Communication and Control in Electric Power Systems: Applications of Parallel and Distributed Processing. 1st ed. Hoboken, NJ, USA: John Wiley and Sons, 2004.
  • [30] Simon SP, Padhy NP, Anand RS. An ant colony system approach for unit commitment problem. Int J Elec Power 2006; 28: 315-323.
  • [31] Manoharan PS, Kannan PS, Ramanathan V. A novel EP approach for multi-area economic dispatch with multiple fuel options. Turk J Electr Eng Co 2009; 17: 1-19.
  • [32] Athay T, Podmore R, Virmani S. A practical method for the direct analysis of transient stability. IEEE T Power Ap Syst 1979; 2: 573-584.