Abstract

Economic dispatch is a highly constrained optimization problem in power system encompassing interaction among decision variables. Environmental concerns that arise due to the operation of fossil fired electric generators, transforms classical problem into multiobjective Emission Constrained Economic Dispatch (ECED) problem. The idea behind this problem formulation is to estimate the optimal generation schedule of generating units in such a manner that fuel cost and emission levels are simultaneously minimized. This multi-objective optimization problem is converted into a single objective function using price penalty factor. This paper presents a Sequential Approach with a Matrix Framework (SAMF) for solving ECED of thermal units. This is a maiden attempt has been developed to obtain the optimal dispatches for all achievable load demands of a system in single execution. The feasibility of the proposed method is demonstrated for two standard test systems. Numerical simulation results indicate that the proposed method has close agreement with the recent reports.

References

• IEEE Current Operating Problems Working Group, Potential impacts of clean air regulations on system operations, Vol. 10, pp 647-653, 1998.
• El-keib, A.A., Ma, H. and Hart, J.L. 1994. Environmentally constrained economic dispatch using a Lagrangian relaxation method. IEEE Trans. Power Systems. 9, 4, 1723-1729.
• Lamont, M.W. and Qbessis, E.V. 1995. Emission dispatch models and algorithms for the 1990’s. IEEE Trans. Power Systems. 10, 2, 941-947.
• Srikrishna, K. and Palanichamy, C. 1991. Economic thermal power dispatch with emission constraint. J. Institution. Engineers. (India), 72, 11-18.
• Song, Y.H., Wang, G.S., Wang, P.Y. and Johns, A.T. 1997. Environmental/economic dispatch using fuzzy logic controlled genetic algorithms. IEE Proc. Generation, Transmission and Distribution. 144, 4, 377 -382.
• Singh, G., Srivastava, S.C., Kalra, P.K. and Vinoth Kumar, D.M. 1995. Fast approach to artificial neural network training and its application to economic load dispatch. Electrical Machines and Power Systems. 13-24.
• Su, C.T. and Chiou, G.J. 1997. A fast computation Hopfield method to economic load dispatch of power systems. IEEE Trans. Power System. 12, 4, 1759 -1764.
• Haung, C.M, Yang, H.T. and Huang, C.L. 1997. Bi-objective power dispatch using fuzzy satisfaction – maximizing decision approach. IEEE Trans. Power Systems. 12, 4, 1715-1721.
• Wong, K.P. and Yuryevich, J. 1998. Evolutionary programming based algorithm for environmentally constrained economic dispatch. IEEE Trans. Power Systems. 13, 2, 301-309.
• Hota, P.K., Chakrabarti, R. and Chattopadhyay, P.K. 2000. Economic emission load dispatch through an interactive fuzzy satisfying method. Electric Power System Research. 54, 151-157.
• Chiou, G.-J. and Su, C.-T. 2000. Economic dispatching with prohibited zones using an extended linear Hopfield model. European Trans. Electrical Power, 10, 2, 113-118.
• Jayabarathi, T., Jayaprakash, K., Jayakumar, D. N. and Raghunathan, T. 2005. Evolutionary programming techniques for different kinds of economic dispatch problems. Electric Power Systems Research. 73,169-176.
• Jeyakumar, D.N., Jayabharathi, T. and Raghunathan, T. 2006. Particle swarm optimization for various types of economic dispatch problems. Int. J. Electrical Power. Energy Systems. 28, 36-42.
• Danaraj, R.M.S. and Gajendran, F. 2005. Quadratic programming solution to emission and economic dispatch problems. J. Institution of Engineers (India). 86, 129-132.
• Muralidharan, S., Srikrishna, K. and Subramanian, S. 2006. Emission constrained economic dispatch – A new recursive approach. Electric Power Components and Systems. 34, 343-353.
• Wang, L. and Singh, C. 2007. Environmental/economic power dispatch using a fuzzified multi-objective particle swarm optimization algorithm. Electric Power Systems Research. 77,1654-1664.
• AL-Sumait, J.S., Sykulski, J.K. and L-Othman, A.K. 2008. Solution of different types of economic dispatch problems using pattern search method. Electric Power Components and Systems. 36, 250-265.
• Balamurugan, R. and Subramanian, S. 2008. A simplified recursive approach to combined economic emission dispatch. Electric Power Components and Systems. 36, 17-27.
• Palanichamy, C. and Sundar Babu, N. 2008. Analytical solution for combined economic and emissions dispatch. Electric Power Systems Research. 78, 1129-1137.
• Krishna Teerth Chaturvedi, Manjaree Pandit, and Laxmi Srivstava. 2008. Modified neo-fuzzy neuron based approach for economic and environmental optimal power dispatch. Applied Soft Computing. 8, 1428-1438.
• Shubham Agrawal, Panigrahi, B.K. and Manoj Kumar Tiwari. 2008. Multiobjective particle swarm algorithm with fuzzy clustering for electrical power dispatch. IEEE Trans. Evolutionary Computation. 12, 15, 529-541.
• Li Xuebin. 2009. Study of multi-objective optimization and multi-attribute decision-making for economic and environmental power dispatch. Electric Power Systems Research. 79, 789-795.