PROJECT TITLE :
Energy Rationalization in Water Supply Networks via Stochastic Programming
This paper presents a 2-stage stochastic programming model applied to energy rationalization in urban networks. The proposed model encompasses choices concerning assortment, transfer and storage of water, whereas minimizing the electricity prices associated to the pumping operations. To cope with the uncertainty nature of water-demands, we use the state of affairs-based approach among the 2-stage stochastic paradigm. So as to mitigate both the variability of the recourse choices and also the infeasible solutions in the presence of multiple eventualities, we have a tendency to conjointly analyze risk averse and robust policies. Numerical results show that it is possible to improve energy consumption by reducing water assortment in crucial periods, furthermore by polishing off optimal levels of water in reservoirs before critical periods. Moreover, the analysis of EVPI and VSS proof the importance of using the stochastic model over less complicated expected approaches.
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