Water distribution networks often exhibit excess pressure that could lead to extensive leakage and infrastructure damages. While this problem can be mitigated with pressure reducing valves, the use of micro-turbines offers the additional benefit of harnessing the excess energy for electricity production. However, the efficient placement of turbines in a water distribution network constitutes a complicated optimization problem. The addition of a turbine in a water distribution network induces additional head losses and redistribution of the discharge within the network. This study considers the discharge redistribution as a key process for the maximization of power generation and presents a heuristic methodology based on nonlinear programming. Through an iterative process, pumps as turbines (PATs) are placed in pipes where the discharge has been increased due to previous placements of PATs elsewhere in the network. The suggested heuristic methodology is implemented in a synthetic network and the results are compared to the maximum power production from all possible combinations of PAT positionings in the network. Results show that the suggested methodology reduces considerably the number of combinations to be tested and it approaches satisfactorily the maximum possible power generation. In the synthetic network, the suggested methodology is able to predict almost the maximum possible power production with up to four PATs in the network and at least 87% of the maximum power production when five PATs are in the network. Finally, the suggested methodology is applied successfully to a real-world network, where it is able to identify the optimal location of one and two PATs.
<p>In the research project Iot.H2O, which is funded under the Water JPI Joint Call 2017 IC4WATER, the potential of the Internet of Things concept is investigated for monitoring and controlling water distribution systems. Smart sensors are used which send data via LoraWAN to gateways which are connected to the Internet. The aim of the project is to use low-cost sensors and open-source software.</p><p>In the presentation, a prototype on a laboratory scale will be shown. The design of the monitoring system will be explained in detail and compared to the design of standard SCADA systems. Results on a pump test rig based on a laboratory scale will be shown as well as first results of field tests in a real water distribution system in Germany.</p><p>The presentation will also detail how data gathered through the smart sensors will be integrated into software modelling and optimization of water distribution systems. Combined with the new data, such tools offer a range of applications of practical relevance, such as the identification of optimal locations of micro-turbines for energy recovery in water distribution networks and the estimation of water demand throughout the network.</p>
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