Minimizing Electricity Fuel Cost of Thermal Generating Units by Using Improved Firefly Algorithm

Thang Trung Nguyen, Bao Quoc Nguyen, Phuong Duy Nguyen, Chiem Trong Hien

Abstract


This paper presents the application of an improved firefly algorithm (IFA) for minimizing total electricity generation fuel cost while all loads are supplied by thermal generating units. The proposed IFA was developed by combining two proposed improvements of the firefly algorithm (FA), i.e. improvement of the distance between two considered solutions and improvement of the new-solution production technique. The effect of each proposed improvement on the conventional firefly algorithm (FA) and the performance of IFA were investigated in two study cases, i.e. single- and multi-fuel option based thermal generating units. In the first case, three different systems with three, six and twenty units were employed, while a ten-unit system with four different loads was tested in the second case. The comparison results between IFA and existing methods, including three other FA variants, revealed that the two proposed improvements of FA are very efficient and make IFA a very promising meta-heuristic algorithm for minimizing fuel cost of thermal generating units.

Keywords


improved firefly algorithm; multi-fuel; single-fuel; thermal generating units; total fuel

Full Text:

PDF

References


Vo, D.N. & Ongsakul, W., Economic Dispatch with Multiple Fuel Types by Enhanced Augmented Lagrange Hopfield Network, Applied Energy, 91(1), pp. 281-289, 2012.

Tran, C.D., Nguyen, T.T., Hoang, H.M. & Nguyen, B.Q., One Rank Cuckoo Search Algorithm for Bi-Objective Load Dispatch Problem, International Journal of Grid and Distributed Computing, 9(4), pp. 13-26, 2016.

Park, J.H., Kim, Y.S., Eom, I.K. & Lee, K.Y., Economic Load Dispatch for Piecewise Quadratic Cost Function Using Hopfield Neural Network, IEEE Transactions on Power Systems, 8(3), pp. 1030-1038, 1993.

Baskar, S., Subbaraj, P. & Rao, M.V.C., Hybrid Real Coded Genetic Algorithm Solution to Economic Dispatch Problem, Computers & Electrical Engineering 29(3), pp. 407-419, 2003.

Noman, N. & Iba, H., Differential Evolution for Economic Load Dispatch Problems, Electric Power Systems Research, 78(8), pp. 1322-1331, 2008.

Lin, C.E. & Viviani, G.L., Hierarchical Economic Dispatch for Piecewise Quadratic Cost Functions, IEEE Transactions on Power Apparatus and Systems, 6, pp. 1170-1175, 1984.

Lee, K.Y., Sode-Yome, A. & Park, J.H., Adaptive Hopfield Neural Networks for Economic Load Dispatch, IEEE Transactions on Power Systems, 13(2), pp. 519-526, 1998.

Lee, S.C. & Kim, Y.H., An Enhanced Lagrangian Neural Network for the ELD Problems with Piecewise Quadratic Cost Functions and Nonlinear Constraints, Elect Power, Syst Res, 60(3), pp. 167-77, 2002.

Park, Y.M., Wong, J.R. & Park, J.B., A New Approach to Economic Load Dispatch Based on Improved Evolutionary Programming, Eng Intell Syst Elect Eng Commun, 6(2), pp. 103-10, 1998.

Panigrahi, B.K., Yadav, S.R., Agrawal, S. & Tiwari, M.K., A Clonal Algorithm to Solve Economic Load Dispatch, Elect Power Syst Res, 77(10), pp. 1381-9, 2007.

Balamurugan, R. & Subramanian, S., Hybrid Integer Coded Differential Evolution–Dynamic Programming Approach for Economic Load Dispatch with Multiple Fuel Options, Energy Convers Manage, 49(4), pp. 608-14, 2008.

Bard, J.F., Short-Term Scheduling of Thermal-Electric Generators Using Lagrangian Relaxation, Operations Research, 36(5), pp. 756-766, 1988.

Dodu, J.C., Martin, P., Merlin, A. & Pouget, J., An Optimal Formulation and Solution of Short-Range Operating Problems for A Power System with Flow Constraints, Proceedings of the IEEE, 60(1), pp. 54-63, 1972. DOI: 10.1109/PROC.1972.8557.

Chen, C.L. & Wang, S.C., Branch-And-Bound Scheduling for Thermal Generating Units, IEEE Transactions on Energy Conversion, 8(2), pp. 184-189, 1993.

Su, C.T. & Lin, C.T., New Approach with A Hopfield Modeling Framework to Economic Dispatch, IEEE Transactions on Power Systems, 15(2), pp. 541-545, 2000.

King, T.D., El-Hawary, M.E. & El-Hawary, F., Optimal Environmental Dispatching of Electric Power Systems Via an Improved Hopfield Neural Network Model, IEEE Transactions on Power Systems, 10(3), pp.1559-1565, 1995.

Vo, D.N. & Ongsakul, W., Economic Dispatch with Multiple Fuel Types by Enhanced Augmented Lagrange Hopfield Network, Applied energy, 91(1), pp. 281-289, 2012.

Roa, C., Salazar, E., Gracia, E., Knight, U. G., & Coonick, A., Environmental Economic Dispatch Via Hopfield Neural Network and Taboo Search, In 31st Universities Power Engineering Conference Proceedings, Irakilo, Greece., pp. 18-20, 1996.

Mandal, K.K., & Chakraborty, N., Effect of Control Parameters on Differential Evolution Based Combined Economic Emission Dispatch with Valve-Point Loading and Transmission Loss, International Journal of Emerging Electric Power Systems, 9(4), 2008.

Rughooputh, H.C. & King, R.A., Environmental/Economic Dispatch of Thermal Units Using an Elitist Multiobjective Evolutionary Algorithm, In Industrial Technology, IEEE International Conference, pp. 48-53, 2003.

Roy, P.K., Ghoshal, S.P. & Thakur, S.S., Combined Economic and Emission Dispatch Problems Using Biogeography-Based Optimization, Electrical Engineering, 92(4-5), pp. 173-184, 2010.

Bhattacharya, A. & Chattopadhyay, P.K., Biogeography-Based Optimization for Different Economic Load Dispatch Problems, IEEE transactions on power systems, 25(2), pp. 1064-1077, 2010.

Song, Y.H., Wang, G.S., Wang, P.Y., & Johns, A.T., Environmental/Economic Dispatch Using Fuzzy Logic Controlled Genetic Algorithms, IEE Proceedings-Generation, Transmission and Distribution., pp. 377-382, 1997.

Thao, N.T.P. & Thang, N.T., Environmental Economic Load Dispatch with Quadratic Fuel Cost Function Using Cuckoo Search Algorithm, International Journal of u-and e-Service, Science and Technology, 7(2), pp. 199-210, 2014.

Nguyen, T.T. & Vo, D.N., The Application of One Rank Cuckoo Search Algorithm for Solving Economic Load Dispatch Problems, Applied Soft Computing, 37, pp. 763-773, 2015.

Le, K. C., Dinh, B.H., & Nguyen, T.T., Environmental Economic Hydrothermal System Dispatch by Using a Novel Differential Evolution, Journal of Engineering and Technological Sciences, 50(1), pp. 1-20, 2018.

Yang, X.S., Nature-Inspired Metaheuristic Algorithms, 1st, Frome, UK: Luniver Press, Bristol, United Kingdom, 2008.




DOI: http://dx.doi.org/10.5614%2Fj.eng.technol.sci.2019.51.1.9

Refbacks

  • There are currently no refbacks.