Modelling the economic trade-offs of irrigation pipeline investments for improved energy management

Abstract

Higher electricity tariffs have accentuated the importance of the trade-off between lowering investment cost by buying pipes with smaller diameters and the higher operating costs that result from the increased power requirement to overcome the higher friction losses of the thinner pipes. The Soil Water Irrigation Planning and Energy Management (SWIP-E) mathematical programming model was developed and applied in this paper to provide decision support regarding the optimal mainline pipe diameter, irrigation system delivery capacity and size of the irrigation system. SWIP-E unifies the interrelated linkages between mainline pipe diameter choice and the timing of irrigation events in conjunction with time-of-use electricity tariffs. The results showed that the large centre pivot resulted in higher net present values than the smaller centre pivot and the lower delivery capacities were more profitable than higher delivery capacities. More intense management is, however, necessary for delivery capacities lower than 12 mm∙d−1 to minimise irrigation during peak timeslots. Variable electricity costs are highly dependent on the interaction between kilowatt requirement and irrigation hours. For the large centre pivot the interaction is dominated by changes in kilowatt whereas the effect of irrigation hours in relation to kilowatts is more important for smaller pivots. Optimised friction loss expressed as a percentage of the length of the pipeline was below 0.6%, which is much lower than the design norm of 1.5% that is endorsed by the South African Irrigation Institute. The main conclusion is that care should be taken when applying the friction loss norm when sizing irrigation mainlines because the norm will result in pipe diameters that are too small, consequently resulting in increased lifecycle operating costs. A clear need for the revision of the friction loss design norm was identified by this research.

Keywords: Non-linear programming, economic trade-off, electricity costs, irrigation system investment costs, water management, net present value