Emission and Environmental Goals in Decision Making Modeling for Load Dispatch

Document Type: Original Research Paper


1 Department of Energy and Resource Economics, Kharazmi University, Tehran-Iran

2 Department of Natural Resources and Environment, University of Birjand – Iran


The main purpose of this research is to determine the generation quantity of each generator in a power system. In this way, not only will the electricity demanded by the system be supplied, but the cost of fuel along with the level of pollution can be minimized. Obviously, calculation of the optimal layout of power plants with the aim of minimizing fuel costs and pollutants level contributes to sustainable socio-economic development. For this purpose, modeling a multi-objective decision making framework by means of the weighting method makes it possible to attain the mentioned goals. After modeling the goals and constraints of the power system, the problem associated with economic-environmental load dispatch with the Institute of Electrical and Electronics Engineers 30-Bus data is optimized by means of the Lagrange approach. Moreover, the sensitivity analysis in connection with the weight of short-term costs is conducted to determine the final point of the system usage. Results show that if the importance coefficient of the fuel cost reduction is 1 (W=1), the economic and environmental load dispatch will pose some problems for the economic load dispatch. In contrast, if the importance coefficient of the reducing fuel cost is zero (W=0), the economic and environmental load dispatch will become problematic for environmental load dispatch. Incidentally, the trade off curve of the fuel cost and the pollutant amount involves the functional information for the system operator. The current research is mainly innovative in its use of a method to reduce fuel consumption and environmental impacts on emission at optimization process. This can, in turn, lead to generation of sustainable energy.


Alsumait, J. S., Sykulski, J. K. and Al-Othman, A. K. (2010). A hybrid GA–PS–SQP method to solve power system valve-point economic dispatch problems. Appl. Energy, 87: 1773-1781.
Balamurugan, R. and Subramanian, S. (2007). A simplified recursive approach to combined economic emission dispatch. Electr. Power. Compo. Syst., 36: 17-27.
Bhattacharjee, K., Bhattacharya, A. and Dey, S. H. (2014).. Solution of economic emission load dispatch problems of power systems by real coded chemical reaction algorithm. Int. J. Electr. Power Energy Syst., 59: 176-187.
Bhattacharya, A. and Chattopadhyay, P. K. (2011). Solving economic emission load dispatch problems using hybrid differential evolution. Appl. Soft Comput., 11: 2526-2537.
Brodsky, S. F. and Hahn, R. W. (1986). Assessing the influence of power pools on emission constrained economic dispatch. IEEE T.Pow. Syst., 1: 57-62.
Chen, F., Huang, G. H., Fan, Y. R. and Liao, R. F. (2016). A nonlinear fractional programming approach for environmental–economic power dispatch. Int. J. Electr. Power Energy Syst., 78: 463-469.
Chen, Y. M. and Wang, W. S. (2009). Economic dispatch with environmental considerations using marginal rate of substitution decision approach. Power Quality, 16: 109-118.
Ciornei, I. and Kyriakides, E. (2013). Recent methodologies and approaches for the economic dispatch of generation in power systems. International Transactions on Electrical Energy Systems, 23: 1002-1027. i i 
i 
Karim, M. H., et al.
De, M., Das, G., Mandal. S. and Mandal, K. K. (2018). Investigating economic emission dispatch problem using improved particle swarm optimization technique. Industry interactive innovations in science, engineering and technology 37-45.
Delson, J. K. (1974). Controlled emission dispatch. IEEE Trans. Power App. Syst., 5: 1359-1366.
Dixit, G. P., Dubey, H. M., Pandit, M. and Panigrahi, B. K. (2011). Economic load dispatch using artificial bee colony optimization. Int. J. Adv. Electr. Eng., 1: 119-124.
Dogra, R., Gupta, N. and Saroa, H. (2014). Economic load dispatch problem and Matlab programming of different methods. In International conference of advance research and innovation (ICARI-2014). http://dl.matlabproject.ir/form/files/265405.pdf
E-Silva, M. D. A. C., Klein, C. E. , Mariani, V. C. and Santos Coelho, L. (2013). Multi-objective scatter search approach with new combination scheme applied to solve environmental/economic dispatch problem. Energy, 53: 14-21.
Gonzalez-Longatt, F.M. and Rueda, J. L. (2014). PowerFactory applications for power system analysis. Power System, Springer. https://www.springer.com/gp/book/9783319129570
Gent, M. and Lamont, J. (1971). Minimum-emission dispatch. IEEE Trans. Power App Syst. 6: 2650-2660.
Granelli, G. P., Montagna, M., Pasini, G. L. and Marannino, P. (1992). Emission constrained dynamic dispatch. Electr. Pow. Syst. Res., 24: 55-64.
Hamedi, H. (2013). Solving the combined economic load and emission dispatch problems using new heuristic algorithm. In. J. Electr. Power Energy Syst., 46: 10-16.
He, X., Rao, Y. and Huang, J. (2016). A novel algorithm for economic load dispatch of power systems. Neurocomputing 171: 1454-1461.
Hooshmand, P. R. A., Parastegari, M. and Morshed, M. J. (2012). Emission, reserve and economic load dispatch problem with non-smooth and non-convex cost functions using the hybrid bacterial foraging-Nelder–Mead algorithm. Appl. Energy 89: 443-453.
Hosseinnezhad, V., Babaei, E. (2013). Economic load dispatch using θ-PSO. Int. J. Electr. Power Energy Syst., 49: 160-169.
Kothari, D. P. (2012). Power system optimization. In Computational Intelligence and Signal Processing (CISP), 2nd National Conference on IEEE. 8-21.
Lamont, J. W. and Obessis, E. V. (1995). Emission dispatch models and algorithms for the 1990s. IEEE T. Power. Syst., 10: 941-947.
Mandal, B., Roy, P. K. and Mandal, S. (2014). Economic load dispatch using krill herd algorithm. Int. J. Electr. Power Energy Syst., 57: 1-10.
Mei, S., Zhang, X. and Cao, M. (2011). Power grid complexity. Springer Science and Business Media. https://www.springer.com/gp/book/9783642162114
Motahari, A. A., Ahmadian, M., Abedi, Z. and Ghafar-Zadeh, H. (2014). Economic appraisal of wind power utilization in Iran, considering the effect of the policy of energy price liberalization. Iran Energy Econom., 3: 179-200.
Pandi, V. R., Panigrahi, B. K., Hong, W. C. and Sharma, R. (2014). A multi-objective bacterial foraging algorithm to solve the environmental economic dispatch problem. Energy Sources, Part B: Econom. Plan. Policy, 9: 236-247.
Pradhan, M., Roy, P. K. and Pal, T. (2016). Grey wolf optimization applied to economic load dispatch problems. Int. J. Electr. Power Energy Syst., 83: 325-334.
REPN (2018). Global status report. Renewable energy policy network for the 21st centuryreport. REN21 secretariat, Paris. http://www.ren21.net/status-of-renewables/global-status-report/
Rao, C. G. K. and Yesuratnam, G. (2013). Emission Constrained optimal power flow by Big-Bang and Big-Crunch optimization. J. Electr. Syst., 9: 256-266.
Reddy, K. S. and Reddy, M. D. (2012). Economic load dispatch using firefly algorithm. Int. J. Eng. Res. Appl., 2: 2325-2330.
Sáenz, J. P., Celik, N., Xi, H., Son, Y. J. and Asfour, S. (2013). Two-stage economic and environmental load dispatching framework using particle filtering. Int. J. Electr. Power Energy Syst., 48: 93-110.
Sivasubramani, S. and Swarup, K. S. (2011). Environmental/economic dispatch using multi-objective harmony search algorithm. Electr. Power Systems Res., 81: 1778-1785.
Turgut, M. S. and Demir, G. K. (2017). Quadratic approximation–based hybrid Artificial Cooperative Search algorithm for economic emission load dispatch problems. Int. Trans. Electr. Energy Syst., 27: e2284.
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Wood, A. J. and Wollenberg, B. F. (2012). Power generation, operation, and control. John Wiley and Sons Publisher. https://www.amazon.com/Power-Generation-Operation-Control-Allen/dp/0471790559
Wu, L. H., Wang, Y. N., Yuan, X. F. and Zhou, S. W. (2010). Environmental/economic power dispatch problem using multi-objective differential evolution algorithm. Electr. Power Syst. Res., 80: 1171-1181.
Xia, X. and Elaiw, A. M. (2010). Optimal dynamic economic dispatch of generation: A review. Electr. Power Syst. Res., 80: 975-986.