General Algebraic Modelling Systems (Gams) A Case Study of Fentale-Qawa Pump Station

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Addis Ababa University


Traditionally, design engineers tend to be conservative in calculating pump station decision variables by focusing on peak demands that occur about1% of the time. On the other hand, optimal design and operation of pumping stations are mathematically large-scale non-linear problems. Consequently, there is a possibility of using an optimum operation schedule on a set of non-optimum pump combinations that are selected narrowly based on peak discharge of system demand. Thus, optimization model is developed in this thesis work to tackle optimization problems in pump stations. Optimal design and operation of irrigation pump station system is carried out with a help of a computer model developed in a General Algebraic Modeling Systems (GAMS). The model makes use of the latest advances in optimization techniques that utilize in-built solvers in GAMS to solve optimization problems with lots of decision variables and constraints. It is based upon one major objective function to find optimized solutions of equations. Automatically generated model outputs include selected pump type, capacity, number of pumps and optimum schedule of pump operation for problems involving design phase. For existing pump stations, it simply generates a preliminary optimum operation schedule. The developed optimization model was tested on previously optimized problem by different researchers and then implemented on a case study, Fentale-Qawa Pump Station, to optimize the annualized investment cost of the pumping station and its annual operating cost. GAMS results were presented and compared with five other well-known optimization techniques. The results were unique and stood second to Lagrange multipliers (LM) method in minimizing Annual Total Cost (ATC) of the sample problem. Implementation of the model would have saved 35% of Initial Investment Cost in pumps had it been used during design phase. The savings occurred in the annual operation cost is 11% compared to the optimized operation cost of the existing pump station. It is clear that the developed optimization model provides the designer and the operator with optimized combination of design variables and operation parameters. (Key words: GAMS, Optimum design variables, Optimum operation schedule, Pump)



Gams, Optimum Design Variables, Optimum Operation Schedule, Pump