Appraising the Impact of Pressure Control on Leakage Flow in Water Distribution Networks

Abstract

Water losses in Water Distribution Networks (WDNs) are inevitable. This is due to joints interconnections, ageing infrastructure and excessive pressure at lower demand. Pressure control has been showing promising results as a means of minimising water loss. Furthermore, it has been shown that pressure information at critical nodes is often adequate to ensure effective control in the system. In this work, a greedy algorithm for the identification of critical nodes is presented. An emulator for the WDN solution is put forward and used to simulate the dynamics of the WDN. A model-free control scheme based on reinforcement learning is used to interact with the proposed emulator to determine optimal pressure reducing valve settings based on the pressure information from the critical node. Results show that flows through the pipes and nodal pressure heads can be reduced using this scheme. The reduction in flows and nodal pressure leads to reduced leakage flows from the system. Moreover, the control scheme used in this work relies on the current operation of the system, unlike traditional machine learning methods that require prior knowledge about the system.

Leakages in Water Distribution Networks: Estimation Methods, Influential Factors, and Mitigation Strategies—A Comprehensive Review

“…While it is not technically possible to completely eliminate leakages (see [19,24]), one effective method for reducing them is to divide the water distribution networks (WDN) into district metered or pressure management areas (DMAs and PMAs, respectively). This is followed by reducing the inlet pressures to the lowest acceptable limit that still meets the consumption/demand requirements [24,45,92,105,.…”

“…Elimination of leakages, apart from being not technically possible due to their nature [19,24,25], it is also not cost-effective due to diminishing returns (i.e., the more the investment on leakage reduction, the less the additional benefit; see, e.g., [26][27][28][29]). Therefore, water supply agencies seek to determine the economic level of leakages, below which any further investment is not cost-effective (see, e.g., [30][31][32][33]), while applying the appropriate leakage reduction strategies proposed in the international literature.…”

Combining Statistical Clustering with Hydraulic Modeling for Resilient Reduction of Water Losses in Water Distribution Networks: Large Scale Application Study in the City of Patras in Western Greece

“…As nodal pressures directly affect the leakage flow rates (see [21,90,91]), as well as the crack expansion rates (see [10]), we use the zero-order estimates of nodal pressures obtained from the first set of hydraulic simulations (see above) to re-distribute the total leakages (RL) to the computational nodes of the network. We do so by borrowing concepts from Torricelli's Law, assuming that the distribution of RL to computational nodes is proportional to the square root of the excesses of the simulated nodal pressures above the minimum pressure required to meet the consumption standards.…”

“…Water losses are the sums of apparent losses (i.e., unauthorized consumption and metering errors) and real losses (i.e., leaks and tank overflows) through the pipeline grid [8,9]. As the complete elimination of leakages Water 2022, 14, 3493 2 of 18 is not technically achievable (see [9,10]), one of the most widely used methods for their reduction is that of WDN partitioning into district metered or pressure management areas (DMAs and PMAs, respectively) followed by the decrease of the inlet pressures to the lowest permissible limit that meets the needs of the consumption/demand [10][11][12][13][14][15][16][17][18][19][20][21][22].…”

Probabilistic Minimum Night Flow Estimation in Water Distribution Networks and Comparison with the Water Balance Approach: Large-Scale Application to the City Center of Patras in Western Greece

“…Elimination of WL, apart from being not technically possible due to their nature [2,17], is also not cost-effective due to diminishing returns (i.e., the more the investment on WL reduction, the less the additional benefits [18][19][20][21]. Therefore, water supply agencies seek to determine the economic level of WL, below which any further investment is not cost-effective [22][23][24][25].…”