• Energy Research

While pressure reducing valves (PRVs) have been widely used in water distribution networks (WDNs) to reduce water leakage, research in recent years has focused on the use of turbines instead of PRVs as the means for enabling both pressure reduction and energy production. However, in WDNs daily continuous variability of flow discharge and upstream head make PAT selection a challenging issue. The present paper describes an innovative approach for optimal PAT selection in systems with hydraulic and/or electrical regulation. The methodology was also applied to a district of the Benevento, Italy, WDN, showing the effectiveness of the proposed approach. The findings showed the optimal pumps lie in the vicinity of the maximum of the produced energy. Furthermore, considering weekday pattern instead of long-period pattern gives reliable results only if the PAT system operated with hydraulic regulation.

While pressure reducing valves (PRVs) have been widely used in water distribution networks (WDNs) to reduce water leakage, research in recent years has focused on the use of turbines instead of PRVs as the means for enabling both pressure reduction and energy production. However, in WDNs daily continuous variability of flow discharge and upstream head make PAT selection a challenging issue. The present paper describes an innovative approach for optimal PAT selection in systems with hydraulic and/or electrical regulation. The methodology was also applied to a district of the Benevento, Italy, WDN, showing the effectiveness of the proposed approach. The findings showed the optimal pumps lie in the vicinity of the maximum of the produced energy. Furthermore, considering weekday pattern instead of long-period pattern gives reliable results only if the PAT system operated with hydraulic regulation.

In the present paper, different clustering techniques were applied to detect significant patterns describing single-household water consumption in a residential neighborhood of the City of Naples, basing on hourly time series aggregated at the monthly scale. Comparisons among results were performed by means of a selection of Clustering Validity Indices, that were adjusted to overcome a bias caused by sparsely populated clusters. The most performant cluster solution proved to be the one resulting from the application of a mixed strategy, namely a Self-Organized Map followed by K-means performed on first level cluster centroids.

In the present paper, different clustering techniques were applied to detect significant patterns describing single-household water consumption in a residential neighborhood of the City of Naples, basing on hourly time series aggregated at the monthly scale. Comparisons among results were performed by means of a selection of Clustering Validity Indices, that were adjusted to overcome a bias caused by sparsely populated clusters. The most performant cluster solution proved to be the one resulting from the application of a mixed strategy, namely a Self-Organized Map followed by K-means performed on first level cluster centroids.

AbstractThis paper analyses and compares different layouts for the installation of pumps used as turbines (PATs) to advantageously couple pressure regulation with hydropower generation in water dis...

AbstractThis paper analyses and compares different layouts for the installation of pumps used as turbines (PATs) to advantageously couple pressure regulation with hydropower generation in water dis...