Rehabilitating pressurized irrigation networks for an increased energy efficiency

This paper presents a methodology aimed at assisting irrigation district managers in the optimal rehabilitation of pressurized irrigation networks. The methodology uses a multi-objective approach and finds optimal trade-off between investments and long term operational costs. The approach is based on two steps: 1—application of two alternative optimization algorithms to determine optimal trade-offs between installation costs and pump power absorption; 2—post-processing of the optimal solutions in terms of long term costs under various possible scenarios generated featuring various values of the useful construction life and of the capital recovery factor. Applications were carried out on a real case study, considering a pre-fixed electricity tariff and the on-demand operation of the network.

[1]  M. T. Carrillo Cobo,et al.  Low energy consumption seasonal calendar for sectoring operation in pressurized irrigation networks , 2011, Irrigation Science.

[2]  E. Camacho Poyato,et al.  Methodology for Detecting Critical Points in Pressurized Irrigation Networks with Multiple Water Supply Points , 2014, Water Resources Management.

[3]  Dragan Savic,et al.  Genetic Algorithms for Least-Cost Design of Water Distribution Networks , 1997 .

[4]  Enrico Creaco,et al.  Fast network multi-objective design algorithm combined with an a posteriori procedure for reliability evaluation under various operational scenarios , 2012 .

[5]  José Maria Tarjuelo,et al.  Energy efficiency of pressurised irrigation networks managed on-demand and under a rotation schedule. , 2010 .

[6]  Raziyeh Farmani,et al.  Optimum Design and Management of Pressurized Branched Irrigation Networks , 2007 .

[7]  Zoran Kapelan,et al.  Comparing Low and High-Level Hybrid Algorithms on the Two-Objective Optimal Design of Water Distribution Systems , 2014, Water Resources Management.

[8]  Joan Corominas,et al.  Agua y energía en el riego, en la época de la sostenibilidad , 2010 .

[9]  Jared L. Cohon,et al.  Multiobjective programming and planning , 2004 .

[10]  Tiku T. Tanyimboh,et al.  Penalty-Free Feasibility Boundary Convergent Multi-Objective Evolutionary Algorithm for the Optimization of Water Distribution Systems , 2012, Water Resources Management.

[11]  D van der Leer,et al.  An assessment, by computational simulation, of random daytime sampling for the optimisation of plumbosolvency control treatment measures , 2005 .

[12]  Juan Ignacio Córcoles,et al.  Methodology to Minimize Energy Costs in an On-Demand Irrigation Network Based on Arranged Opening of Hydrants , 2015, Water Resources Management.

[13]  E. Camacho Poyato,et al.  Detecting Critical Points in On-Demand Irrigation Pressurized Networks – A New Methodology , 2012, Water Resources Management.

[14]  M.A. Moreno,et al.  Development of a new methodology to obtain the characteristic pump curves that minimize the total cost at pumping stations. , 2008 .

[15]  Ezio Todini,et al.  Looped water distribution networks design using a resilience index based heuristic approach , 2000 .

[16]  César González-Cebollada,et al.  Recursive Design of Pressurized Branched Irrigation Networks , 2011 .

[17]  E. Camacho Poyato,et al.  Energy cost optimization in pressurized irrigation networks , 2015, Irrigation Science.

[18]  Nicola Lamaddalena,et al.  Performance analysis of on-demand pressurized irrigation systems , 2000 .

[19]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[20]  Mohammed Ali,et al.  Optimal Design of Water Distribution Systems Using Genetic Algorithms , 2000 .

[21]  C. Rocamora,et al.  Strategy for Efficient Energy Management to solve energy problems in modernized irrigation: analysis of the Spanish case , 2012, Irrigation Science.

[22]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[23]  Nicola Lamaddalena,et al.  Efficiency-driven pumping station regulation in on-demand irrigation systems , 2011, Irrigation Science.

[24]  Consolación Gil,et al.  Implementation of scatter search for multi-objective optimization: a comparative study , 2009, Comput. Optim. Appl..

[25]  M T Carrillo Cobo,et al.  New model for sustainable management of pressurized irrigation networks. Application to Bembézar MD irrigation district (Spain). , 2014, The Science of the total environment.