Commenced in January 2007
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Developing New Algorithm and Its Application on Optimal Control of Pumps in Water Distribution Network

Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

Abstract:

In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1109231

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References:


[1] O. Yeniay, “A comparative study on optimization methods for the constrained nonlinear programming problems,” Mathematical Problems in Engineering. 2, pp.165–173, 2005.
[2] K. S. Lee, Z.W. Geem, S. H. Lee and K.W. Bae, “The harmony search heuristic algorithm for discrete structural optimization,” Eng. Optim. 37, pp. 663–684, 2005.
[3] H. Afshar and R. Rajabpourr, “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] G. Mackle, D. A. Savic, and G. A. Walters, “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] S. I. Rodin and M. Moradi-Jalal, “Use of genetic algorithm in optimization of irrigation pumping stations. WAPIRRA program, 2002.
[6] M. Moradi-Jalal, M. A. Marino and A. Afshar, “Optimal design and operation of irrigation pumping station,” J. Irrig. Drain. Eng. 129(3): pp. 149-154, 2003.
[7] R. Rajabpourr and M.H. Afshar, “Optimized Operation of Serial Pump Stations Using the PSO Algorithm,” Journal of Water & Wastewater., 66, pp.56-66, 2008 (In Persian).
[8] J. E. Van Zyl, D. A. Savic, and G. A. Walters, “Operational optimization of water distribution systems using a hybrid genetic algorithm,” J. Water Resour. Plann. Manage., 130(2), pp. 160–170, 2004.
[9] M. López-Ibáñez, T. D. Prasad and B. Paechter, “Ant Colony Optimization for Optimal Control of Pumps in Water Distribution Networks,” J. Water Resour. Plann. Manage. 134(4), pp. 337–346, 2008.
[10] O. Bozorg Haddad and, M.A. Marino, “Dynamic penalty function as a strategy in solving water resources combinatorial optimization problems with honey-bee mating optimization (HBMO) algorithm,” Journal of Hydro informatics, 9 (3), pp.233-250, 2007.
[11] Sanda-Carmen, P. Radu, M. Andrei , “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] S. Rasoulzadeh Gharibdosti, O. Bozorghadad, “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 (In Persian).
[13] S.S. Hashemi, M. Tabesh and B. Ataee Kia, “Ant-colony 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] S.S. Hashemi, M. Tabesh and B. Ataee Kia, “Scheduling and operating costs in water distribution networks,” Water Management., 166(8), pp. 432-442, 2012.
[15] J. Kennedy and R. Eberhart, “A discrete binary version of the particle swarm algorithm,” In: IEEE Conference on Systems, Man, and Cybernetics, 5: pp. 4104-4108, 1997.
[16] S. Yang, M. Wang and L. Jiao, “A Quantum Particle Swarm Optimization,” In: Proceedings of CEC2004, the Congress on Evolutionary Computing, 1, pp. 320-324, 2004.
[17] B. Al-kazemi and C.K. Mohan, “Multi-phase Discrete Particle Swarm Optimization,” Fourth International Workshop on Frontiers in Evolutionary Algorithms, Kinsale, Ireland, 2002.
[18] J.A. Moreno-Perez, J.P. Castro-Gutierrez, F.J. Martinez-Garcia, B. Melian, J.M. Moreno-Vega, and J. Ramos, “Discrete Particle Swarm Optimization for the p-median problem”. In: Proceedings of the 7th Meta heuristics International Conference, Montreal, Canada, 2007.
[19] R. Atkinson, J.E. Van Zyl, G.A. Walters and D.A. Savic, “Genetic algorithm optimization of level-controlled pumping station operation. Proc,” Water Network Modeling for Optimal Design and Management, Centre for Water Systems, Exeter, U.K., pp. 79–90, 2000.