Solving the Economic Load Dispatch Problem Considering Units with Different Fuels Using Evolutionary Algorithms

Authors

1 Electric Engineering Department, Science and Research branch, Islamic Azad University Kermanshah, Iran

2 Electric Engineering Department, Faculty of Engineering, Razi University, Kermanshah, Iran

Abstract

Nowadays, economic load dispatch between generation units with least cost involved is one of the most important issues in utilizing power systems. In this paper, a new method i.e. Water Cycle Algorithm (WCA) which is similar to other intelligent algorithm and is based on swarm, is employed in order to solve the economic load dispatch problem between power plants. In order to investigate the effectiveness of the proposed method in solving non-linear cost functions which is composed of the constraint for input steam valve and units with different fuels, a system with 10 units is studied for more accordance with literatures in two modes: one without considering the effect of steam valve and load of 2400, 2500, 2600 and 2700 MW and the other one with considering the effect of steam valve and load of 2700 MW. The results of the paper comparing to the results of the other valid papers show that the proposed algorithm can be used to solve in any kind of economic dispatch problems with proper results.

Keywords


[1]
A. A. El-Keib, H. Ma, and J. L. Hart, “Environmentally constrained economic dispatch using the Lagrangian relaxation method. IEEE Transactions on Power Systems, Vol.9, No.4, pp.1723–1729, Nov. 1994.
[2]
N. Sinha, B. Purkayastha, “PSO embedded
evolutionary programming technique for non-convex
economic load dispatch,” Proc. Power Systems
Conference and Exposition, Vol.1, pp.66–71, October
2004.
[3]
Z.-L. Gaing, “Particle swarm optimization to solving the economic dispatch considering the generator
constraints,” IEEE Transactions on Power Systems, Vol. 18, No.3, pp. 1187–1195, Aug. 2003.
[4]
Adler.R.B and Fischl.R,” Security constrained economic dispatch with participation factors based on worst case bus load variations”, IEEE Trans. on Power Apparatus and Systems, Vol.96, No.2, pp.347–356, 2006.
[5]
Bui.R.T. and Ghaderpanah.S,” Real power rescheduling and security assessment”, IEEE Trans. on Power Apparatus and Systems, Vol.101, No.8, pp.2906–2915, 2007.
[6]
J. H. Park, Y. S. Kim, I. K. Eom, and K. Y. Lee, “Economic load dispatch for piecewise quadratic cost function using Hopfield neural network,” IEEE Transactions on Power Systems, Vol.7, No.3, pp.1232–1237, 1993.
[7]
C.-L. Chiang, “Improved Genetic Algorithm for Power Economic Dispatch of Units with Valve-Point Effects and Multiple Fuels,” IEEE Transactions on Power Systems, Vol. 22, No. 4, pp.1692–1699, Nov. 2005.
[8]
M. Vanitha and K. Thanushkodi, “Solving non-convex economic load dispatch problem by Efficient Hybrid Simulated Annealing algorithm,” 2212 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT), No.927, pp.362–365, Aug. 2012.
[9]
N. A. Rahmat and I. M. M. Ieee, “Differential Evolution Ant Colony Optimization (DEACO) Technique In Solving Economic Load Dispatch Problem,” IEEE Power Engineering and Optimization Conference, pp.6–2, 2012.
[10]
T. Satoh, H. Kuwabara, M. Kanezashi, and K. Nara, “Artificial Life System and its Application to Mult iple-Fuel Economic Load Dispatch Problem,” Proceedings of Evolutionary Computation, Vol.2, pp.1432–1432, 2002.
[11]
B. Vanaja, S. Hemamalini, and S. P. Simon, “Artificial Immune based Economic Load Dispatch with valve-point effect,” TENCON 2227 - 2227 IEEE Region 12 Conference, pp.1–5, Nov. 2007.
[12]
R. Gonc, C. Almeida, and M. Goldbarg, “Improved Cultural Immune Systems to Solve the Economic Load Dispatch Problems,” IEEE Congress on Evolutionary Computation, pp.621–627, 2013.
[13]
A. Ghasemi, “A fuzzified multi objective Interactive Honey Bee Mating Optimization for Environmental/Economic Power Dispatch with valve point effect,” International Journal of Electrical Power & Energy Systems, Vol.49, pp.327–321, Jul. 2013.
[14]
N. Amjady and H. Sharifzadeh, “Solution of non-convex economic dispatch problem considering valve loading effect by a new Modified Differential Evolution algorithm,” International Journal of Electrical Power & Energy Systems, Vol.32, No.7, pp.793–923, Oct. 2012.
[15]
T. Niknam, M. R. Narimani, and R. Azizipanah-Abarghooee, “A new hybrid algorithm for optimal power flow considering prohibited zones and valve point effect,” Energy Conversion and Management, Vol.57, pp.192–226, Jun. 2012.
[16]
K. Vaisakh and a. S. Reddy, “MSFLA/GHS/SFLA-GHS/SDE algorithms for economic dispatch problem considering multiple fuels and valve point loadings”, Applied Soft Computing, pp.1–11, Jul. 2013.
[17]
a. K. Barisal, “Dynamic search space squeezing strategy based intelligent algorithm solutions to economic dispatch with multiple fuels”, International Journal of Electrical Power & Energy Systems, Vol.45, No.1, pp.52–59, Feb. 2013.
[18]
H. Eskandar, A. Sadollah, A. Bahreininejad, and M. Hamdi, “Water cycle algorithm – A novel metaheuristic optimization method for solving constrained engineering optimization problems,” Computers & Structures, Vol.112–111, pp.151–166, Nov. 2012.
[19]
H. Eskandar, A. Sadollah, A. Bahreininejad, and K. Lumpur, “Weight Optimization of Truss Structures Using Water Cycle Algorithm”, International Journal of Optimization in Civil Engineering, Vol.3, No.1, pp.115–129, 2013.
International Journal of Smart Electrical Engineering, Vol.2, No.4, Fall 2013 ISSN: 2251-9246
EISSN: 2345-6221
208
[20]
C. E. Lin and G. L. Viviani, “Hierarchical economic dispatch for piecewise quadratic cost functions,” IEEE Transactions on Power Apparatus and Systems, vol. PAS-123, No.62, pp.1122–1125, 1974.
[21]
J. H. Park, Y. S. Kim, I. K. Eom, and K. Y. Lee, “Economic load dispatch for piecewise quadratic cost function using Hopfield neural network,” IEEE Transactions on Power Systems, Vol.7, No.3, pp.1232–1237, 1993.
[22]
K. Y. Lee, A. Sode-Yome, and J. H. Park, “Adaptive Hopfield neural networks for economic load dispatch,” IEEE Transactions on Power Systems, Vol.13, No.2, pp.519–526, 1997.
[23]
S. C. Lee and Y. H. Kim, “An enhanced Lagrangian neural network for the ELD problems with piecewise quadratic cost functions and nonlinear constraints”, Electric Power Systems Research, Vol.62, No.3, pp.162–122, Jan. 2002.
[24]
Y. M. Park, J. R. Won, and J. B. Park, “A new approach to economic load dispatch based on improved evolutionary programming”, Eng. Intell. Syst. Elect. Eng. Commun, Vol.6, No.2, pp.123–112, 1997.
[25]
N. Noman and H. Iba, “Differential evolution for economic load dispatch problems,” Electric Power Systems Research, Vol.27, No.7, pp.1322–1331, Aug. 2007.
[26]
J.-B. Park, K.-S. Lee, J.-R. Shin, and K. Y. Lee, “A Particle Swarm Optimization for Economic Dispatch with Non-smooth Cost Functions,” IEEE Transactions on Power Systems, Vol.22, No.1, pp.34–42, Feb. 2005.
[27]
S. Baskar, P. Subbaraj, and M. V. C. Rao, “Hybrid real coded genetic algorithm solution to economic dispatch problem,” Computers & Electrical Engineering, Vol.29, No.3, pp. 422–419, May 2003.
[28]
B. K. Panigrahi, S. R. Yadav, S. Agrawal, and M. K. Tiwari, “A clonal algorithm to solve economic load dispatch,” Electric Power Systems Research, Vol.22, No. 12, pp.1371–1379, Aug. 2002.
[29]
R. Balamurugan and S. Subramanian, “Hybrid integer coded differential evolution – dynamic programming approach for economic load dispatch with multiple fuel options,” Energy Conversion and Management, Vol.49, No.4, pp.627–614, Apr. 2007.
[30]
C.-L. Chiang, “Improved Genetic Algorithm for Power Economic Dispatch of Units with Valve-Point Effects and Multiple Fuels,” IEEE Transactions on Power Systems, Vol.22, No.4, pp.1692–1699, Nov. 2005.
[31]
C.-L. Chiang, “Improved Genetic Algorithm for Power Economic Dispatch of Units with Valve-Point Effects and Multiple Fuels”, IEEE Transactions on Power Systems, Vol.22, No.4, pp.1692–1699, Nov. 2005.