Developing a new algorithm (G-JPSO) for optimal control of pumps in water distribution networks

Document Type : Article


1 Department of Civil Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran

2 Department of Civil and Environmental Engineering, Environmental Research and Sustainable Development Center, Shiraz University, Shiraz, Iran.

3 Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran.


Meta-heuristic methods have been widely used for solving complex problems recently. Among these methods, JPSO is regarded as a promising algorithm. However, in order to achieve more robust performance, the probability to solve the graph-based problems is modified by changing the jumping nature of this algorithm and a new algorithm called G-JPSO is presented which is evaluated by solving Fletcher-Powell function and optimal control of pumps in water distribution network problems. In addition to reduction of electricity cost and the problem limitations such as minimum required pressure in each node, minimum and maximum height of tanks, should also be considered. Moreover, another limitation was performed on the objective function which includes the maximum times of turning the pumps on and off. In order to determine the pumps optimal operation, an optimization-simulation model based on the optimization algorithms G-JPSO and JPSO is developed. This proposed model is used for determination of optimal operation program of Van Zyl distribution network. The comparison carried out between the results of our proposed algorithm and those of the similar algorithms including ant colony, genetic and JPSO shows the high ability of the presented algorithm in finding solutions near the optimal solutions with reasonable computation costs.


Main Subjects

1. Yeniay, O. A comparative study on optimization methods for the constrained nonlinear programming problems", Mathematical Problems in Engineering, 2, pp. 165{173 (2005). 2. Lee, K.S., Geem, Z.W., Lee, S.H., and Bae, K.W. The harmony search heuristic algorithm for discrete structural optimization", Eng. Optim., 37, pp. 663{ 684 (2005). 3. Afshar, H. and Rajabpour, R. Application of local and global particle swarm optimization algorithms to optimal design and operation of irrigation pumping systems", Irrig. and Drain., 58(3), pp. 321{331 (2009). 4. Mackle, G., Savic, D.A., and Walters, G.A. Application of genetic algorithms to pump scheduling for water supply", GALESIA, 95. London: Institute of Electrical Engineers Conference Publication, 4(4), pp. 400{405 (1995). 5. Rodin, S.I. and Moradi-Jalal, M. Use of genetic algorithm in optimization of irrigation pumping stations", WAPIRRA program. [Online]. <http://stullia.t-k. ru/waterpump/waterpump.htm>. (June 10, 2002). 6. Moradi-Jalal, M., Marino, M.A., and Afshar, A. Optimal design and operation of irrigation pumping station", J. Irrig. Drain. Eng., 129(3), pp. 149{154 (2003). 7. Rajabpour, R. and Afshar, M.H. Optimized operation of serial pump stations using the PSO algorithm", Journal of Water & Wastewater, 66, pp. 56{66 (2008). 8. Van Zyl, J.E., Savic, D.A., and Walters, G.A. Operational optimization of water distribution systems using a hybrid genetic algorithm", J. Water Resour. Plann. Manage., 130(2), pp. 160{170 (2004). 9. L_opez-Ib_a~nez, M., Prasad, T.D., and Paechter, B. Ant colony optimization for optimal control of pumps in water distribution networks", J. Water Resour. Plann. Manage., 134(4), pp. 337{346 (2008). 10. Bozorg Haddad, O. and Marino, M.A .Dynamic penalty function as a strategy in solving water resources combinatorial optimization problems with honey-bee mating optimization (HBMO) algorithm", Journal of Hydroinformatics, 9(3), pp. 233{250 (2007). 11. Sanda-Carmen, G., Radu, P., and Andrei-Mugur, G. Pumping stations scheduling for a water supply system with multiple tanks", U.P.B. Sci. Bull., Series D, 72(3), pp. 129{140 (2010). 12. Rasoulzadeh Gharibdosti, S. and Bozorghadad, O. Development and application of NLP-GA hybrid algorithm to optimize the design and operation of pumping stations", Iranian Journal of Soil and Water Research, 43(2), pp. 129{137 (2012). 13. Hashemi, S.S., Tabesh, M., and Ataee Kia, B. Antcolony optimization of energy cost in water distribution systems using variable speed pumps", In Proceedings of 4th ASCE-EWRI International Perspective on Water Resources and The Environment, 4{6 January, National University of Singapore, Singapore (2011). 14. Hashemi, S.S., Tabesh, M., and Ataee Kia, B. Scheduling and operating costs in water distribution networks", Water Management, 166(8), pp. 432{442 (2012). 15. Mehzad, N., Tabesh, M., and Hashemi, S.S. Reliability of water distribution networks due to pumps failure: comparison of VSP and SSP application", Drinking Water Engineering and Science, 5, pp. 351{373 (2012). 16. Hashemi, S.S., Tabesh, M., and Ataee Kia, B. Antcolony optimization of pumping schedule to minimize the energy cost using variable-speed pumps in water distribution networks", Urban Water Journal, 11(5), pp. 335{347 (2014). 17. Abdelmeguid, H. and Ulanicki, B. Feedback rules for operation of pumps in a water supply system considering electricity tari_s", In Water Distribution Systems Analysis, pp. 1188{1205 (2010). 18. Skworcow, P., Ulanicki, B., AbdelMeguid, H., and Paluszczyszyn, D. Model predictive control for energy and leakage management in water distribution systems", In UKACC International Conference on Control, Coventry, UK (2010). 19. Fiorelli, D., Schutz, G., Metla, N., and Meyers, J. Application of an optimal predictive controller for a small water distribution network in Luxembourg", Journal of Hydroinformatics, 15(3), p. 625 (2013). DOI: 10.2166/hydro.2012.117 R. Rajabpour et al./Scientia Iranica, Transactions A: Civil Engineering 27 (2020) 68{79 79 20. Paluszczyszyn, D., Skworcow, P., and Ulanicki, B. Online simpli_cation of water distribution network models for optimal scheduling", Journal of Hydroinformatics, 15(3), pp. 652{665 (2013). DOI: 10.2166/hydro. 2012.029 21. Kennedy, J. and Eberhart, R. Adiscrete binary version of the particle swarm algorithm", In IEEE Conference on Systems, Man, and Cybernerics, 5, pp. 4104{4108 (1997). 22. Yang, S., Wang, M., and Jiao, L. A quantum particle swarm optimization", In Proceedings of CEC2004, the Congress on Evolutionary Computing, 1, pp. 320{324 (2004). 23. Al-Kazemi, B. and Mohan, C.K. Multi-phase discrete particle swarm optimization", In Fourth International Workshop on Frontiers in Evolutionary Algorithms, Kinsale, Ireland (2002). 24. Moreno-Perez, J.A., Castro-Gutierrez, J.P, Martinez- Garcia F.J., Melian, B., Moreno-Vega, J.M., and Ramos, J. Discrete particle swarm optimization for the p-median problem", In Procceedings of the 7th Metaheuristics International Conference, Montreal, Canada (2007). 25. Sami Kashkoli, B. and Monem, J. Development and application of pressure irrigation systems using integrated optimization model JPSO / LIDM", 8th Iranian Hydraulic Conference, Azar, Tehran (2009). 26. Gen, M. and Cheng, R.W., Genetic Algorithm and Engineering Design, John Wiley and Sons, Inc (1997). 27. Jalali, M.R. and Afshar, A. Optimum design and operation of hydrosystem by ant colony optimization algorithm; A New Metaheuristic Approach", Ph.D. Dissertation of Water Engineering, Iran University of Science and Technology (2005). 28. Lansey, K.E. and Awumah, K. Optimal pump operations considering pump switches", J. Water Resour. Plann. Manage., 120(1), pp. 17{35 (1994). 29. Atkinson, R., van Zyl, J.E., Walters, G.A., and Savic, D.A. Genetic algorithm optimization of levelcontrolled pumping station operation", Proc., Water Network Modelling for Optimal Design and Management, Centre for Water Systems, Exeter, U.K., pp. 79{90 (2000).