| dc.description.abstract | A considerable portion of costs and greenhouse gas (GHG) emissions associated with the transmission of fresh water is related to energy usage. Optimising the costs and GHG emissions of energy consumption by scheduling the pumping cycle and by the use of storage areas is a multi-objective mixed integer nonlinear programming (MINLP) problem that contains multiple constraints. The solution space and running time of this type of problem can be very large. To solve this problem and to improve the operational sustainability of a water transmission scheme (WTS) as profitable as possible and by fulfilling to the demand of water, a mixed integer linear programming (MILP) model is made with the software OpenModelica and RTC-Tools. The model is made and analysed for a WTS located in the emirate Abu Dhabi, United Arab Emirates (UAE), but can be applied to other portions of a WTS. Multiple scenarios are conducted related to electricity prices (flat rate versus Time of Use (ToU) rates), GHG emissions factors (average (AV) versus time-dependent (TD) GHG emissions factors), carbon taxes and the influence of the infrastructure of the WTS on the pump schedule. The results show that when switching to ToU electricity tariffs and/or TD GHG emissions factors and thereby using the capacity of the storage areas, remarkable costs and/or GHG emissions savings are possible. Also, including a carbon tax has a positive effect on switching the pump schedule to day time (solar availability in UAE). However, when the proportion of solar power is small compared to the other power sources, the necessary carbon tax is disproportional high. Furthermore, a sensitivity analysis is performed to test the robustness of the GHG emissions intensities and the water flow speed through the system. Finally, recommendations are made to shift the model to a continuous model to further reduce the solution space. | |
