THE RELEVANCE OF ENHANCED HYDRAULIC MODELLING FOR ASSET MANAGEMENT AND RELATED PERFORMANCE INDICATORS ABSTRACT

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1 THE RELEVANCE OF ENHANCED HYDRAULIC MODELLING FOR ASSET MANAGEMENT AND RELATED PERFORMANCE INDICATORS Perrone G. 1, Palma F. 2, Laucelli D. 3, Berardi L. 3, Simone, A. 3, Giustolisi O. 3* 1 IA. Ing Srl, v.le M. Chiatante, 60, Lecce, Italy 2 Acquedotto Pugliese S.p.A., via S. Cognetti, 36, Bari, Italy 3 Technical University of Bari, Dept. of Civil Engineering and Architecture via Orabona n.4, 70125, Bari, Italy * orazio.giustolisi@poliba.it ABSTRACT Water distribution networks (WDNs) in urban areas are public infrastructures whose management requires planning effective investments on complex, large and aged systems. In the last decade ineffective decisions supported by inappropriate analysis tools caused the increasing rate of water losses and service interruptions observed in many countries worldwide. This is the case of Italy, where a novel regulatory framework has introduced reward/penalties rules aimed at improving the quality of investments based on measurable performance indicators. As a consequence, water companies seek for advanced analyses procedures suited for supporting management decisions that might overcome the limitations of existing tools. This contribution shows the implementation of advanced hydraulic modeling in one of the largest water company in Europe, i.e. Acquedotto Pugliese s.p.a., to support complex decision-making process, as part of novel integrated and structured asset management process. Keywords: Water Distribution Network, Asset Management, Advanced Hydraulic Simulation, Background Leakages 1 Introduction Around the world, comprehensive asset management of water distribution networks (WDNs) is a relevant issue for technical-scientific research since the growing urban development has produced increasingly large, complex and old water distribution networks (WDNs) for which new management issues have arisen with respect to water quality, water loss, reliability, energy optimization, rehabilitation, etc. For instance, in Italy, data from 2015 show that in Southern regions the average rate of water losses is over 50%, compared with a national average of about 41%. In this context, the Italian Authority for Regulation of Energy, Networks and Environment (ARERA, former AEEGSI) introduced [1] a new water regulation framework aimed at improving the technical quality of the integrated water systems. Starting from January 2018, the management of WDNs is undergoing a stricter control aimed at improving the quality of investments on such public infrastructures. In more details, the management performance will be measured using macroindicators encompassing water losses (M1), water supply reliability (M2) and water quality (M3), that will trigger rewards and penalties mechanisms having direct impact on water tariff and, definitively, on revenues for companies. Such new regulatory framework is motivating Italian water utilities towards a change of approach in WDN management, where complex decisions on investments from short to long time horizons should be substantiated by reliable feasibility analyses.

2 In Southern Italy, Acquedotto Pugliese S.p.A. (AQP) is in charge of the water cycle management on the whole territory of Apulia region and some municipalities of Campania and Basilicata regions. The regional water conveyance system managed by AQP is one of the longest in Europe and the water distribution networks include 450 water tanks serving the municipalities, km of distribution pipelines and km of water connections. In the last decade, AQP, started with a massive campaign to collect data form about 300 urban WDNs in the entire Apulian Region. Such information created one the largest database of water distribution networks in Europe and represent the base information to implement hydraulic models for every single urban WDN. This is just one of the actions that AQP is undertaking aimed at improving the knowledge of these infrastructure systems as an essential pre-requisite to take effective management decisions. Over the last year AQP started a process for introducing a rational, structured and scalable engineering procedure to support asset management exploiting the design of district metering areas (DMAs) as of strategic importance for monitoring hydraulic status, operating pressure control and planning asset rehabilitation works. One primary objective of all such actions is to improve WDN performance in terms of water losses reduction, as required by the new Italian regulation. To this end AQP required technical consultants to propose innovative and reliable analyses tools that might proof the effectiveness of planned actions with flexible and verifiable procedures, thus overcoming previous heuristic approaches. In this context, advanced hydraulic models play a key role in overcoming the limitations of mostly adopted commercial software, mainly developed to support the design of new systems ex-novo rather than the management of aged WDNs. IA.Ing s.r.l., working as consultant company for AQP, decided to exploit the advanced hydraulic model implemented in WDNetXL system [2] as the base element to provide a customized and integrated asset management process matching the abovementioned requirements. IDEA-RT s.r.l., as a unique innovation provider in the areas of WDN asset and management, set-up the procedure and tools to be used by consultants and AQP. This contribution discusses the relevance of the advanced hydraulic modelling in this context, demonstrating its application for analysing a WDN serving the second largest Apulian city. 2 From classic to advanced hydraulic modelling for WDN management Hydraulic modelling of modern WDNs started at the beginning of the last century to support design solutions aimed at delivering water to increasing population in urban areas and/or for fire protection. As such, models were used to verify sufficient pressure at model nodes under assumed values of pipe hydraulic resistances, fixed water demands (i.e. statistical water requests of various types of users) and assumed firefighting requirements. The hydraulic verification was ultimately the assessment of pressure at nodes with respect to the minimum values required for a correct service to users and, with respect to fire protection, in the evaluation of the flow rates and minimum residual pressures for a correct hydraulic performance of hydrants. With the advent of computers, in 1988 Todini [3] introduced the Global Gradient Algorithm (GGA) that was implemented in EPANET [4]. Many commercial software packages are based on EPANET hydraulic model, while others derive from the linear theory with different performance in terms of accuracy and convergence rate [5]. Since nodal pressures come from fixed water demands, such models are known as demand-driven. In 2003 Todini [6] posed the problem of accounting for pressure deficient conditions, when actual demand supplied is lower than the statistical water requests, which is a typical abnormal condition that might happen in a real aged WDN. The same work introduced a modification of the original GGA including the Wagner s [7] pressure-demand model. The Wagner s model [7] returns a

3 demand value equal to the statistical water requests for pressure higher than the minimum value for a correct service, while the actual demand for intermediate pressures, i.e. in pressure-deficient condition, is calculated consistently with the Torricelli s law [8]. Giustolisi et al. [9] included in the same solving algorithm the representation of the demand component entailing leakages along pipes [10]. Such model proved to be useful especially for WDN management purposes since the adopted leakage model is consistent with the classification of real water losses developed so far. In fact, technical literature (e.g. [11]) discriminates between bursts and background leakages. Pipe bursts are large water outflows that might cause severe disruptions; major burst leaks with relevant impact on pressure and water supply service are usually reported to water utilities and suddenly repaired. Viceversa, unreported bursts run until detected through active leakage control actions (e.g. [12][13][14][15]). Background leakages consist of small outflows from joints, fittings or cracks along the pipes and private connections that cannot be detected using normal inspections and do not cause abrupt changes in WDN hydraulic functioning. For this reason, they can run for long time, accelerating pipe deterioration (e.g. [16]) and, ultimately, evolving into major bursts. Both unreported and background leakages are pressure-dependent components of real water losses that have major volumetric effects on global WDN mass balance (e.g. on annual operating cycle), thus should be accounted for while supporting management decisions. The same model was modified [17] to include private in-line tanks in pressure-driven analysis. It is worth noting that, unlike other geographic areas, in Apulian region customers bring water from private storage tanks that fill up and empty over the daily cycle. This circumstance, in turns, makes most of the existing models (both commercial and not) inadequate to represent the complexity of the real hydraulic behaviour. 3 Performance indicators based on advanced hydraulic modelling The leakage model in [9], which is part of the advanced model implemented in the WDNetXL system, assigns each k-th pipe a factor βk, which is a global indicator of deterioration, therefore very useful at the management level. The volumetric losses qk leakage along the k-th trunk are computed as: q Ae,D,Pr,..., P L (1) leakage k k k t k Leakage rates per unit of length, qk/lk, represents an indicators for asset management as it encompasses the effects of average pipe pressure, Pk,t, changing over time (e.g. hourly) and asset deterioration through parameter βk and exponent α. In general, setting α =1 is a good technical assumption especially for models aimed at planning, while the deterioration parameter βk can be expressed as function of the age of the pipe (Ae), the diameter (D) and the number of properties supplied (Pr), as an indicator of leakage propensity due to connections. Actually, the parameter βk is a function of other stress factors related to the service life of the WDN such as thermal stress, traffic, pressure heads, unsteady flow stresses, etc., which are in some way correlated to Ae, D and Pr, which are the easiest asset factors to find in real WDN management contexts. It is worth noting that the model in Eq. (1) integrated within the WDN hydraulic model allows the direct assessment of two macro indicators that was introduced by ARERA [1], namely the linear water losses (M1a) as the volume of water losses per unit length per year (i.e. qk/lk per one year) and the water losses percentage (M1b) as the ratio between the volume of water losses and total inlet water volume. As such, the advanced hydraulic model enables to evaluate the expected impact of asset management actions, including pressure control and asset rehabilitation works, directly in terms of the regulatory performance indicators.

4 On pressure control side, previous works (e.g. [18]) showed the relevance of using such advanced model in comparing alternative schemes for pressure management trough real-time remote controlled and classic pressure control valves. Considering that pressure control is recommended as the cheapest short-medium term best practice to reduce volumetric real losses (e.g. [19]), it is of direct relevance for water utilities. On asset rehabilitation planning, this model is of preeminent importance to avoid that the replacement of some pipes causes the increase of water losses. In fact, it is well known to water utilities that the increase of nodal pressure caused by the reduction of the hydraulic resistance of new pipes is generally not compensated by the effect of reduction of qk along the replaced pipes. This, in turn, causes the increase of water losses and consequent raise of burst rate downstream the replaced pipes. The hydraulic model allows the identification of those pipes that, because of their hydraulic and plano-altimetric location, result into an effective global leakage reduction. 4 Case study The case study analyzed in this work concerns a large network located in the south of Apulia region, Italy, and currently managed by AQP. The network was composed of links and node, as shown in Figure 1. It can be noted that the network model reports three water sources feeding the systems placed at different elevations, and located outside the built-up area, towards the north and east, in zones raised above the inhabited area. They supply water to the city center that is characterized by low elevations, decreasing towards the sea, with small reliefs in the South-East area of the municipal territory. Figure 1. Topology of Taranto WDN in WDNetXL 4.1 Performance indicators on volumetric leakages The city supplied by WDN has about 200,000 inhabitants, some public utilities and a large industrial area. The total average daily demand considered in the hydraulic model is m 3, of

5 which 45,467 m 3 are customer demands and 22,736 m 3 are volumetric leakages, i.e. about the 33% of the inlet volume of the network and about 58 m 3 /km per day. Figure 2. Volume of water supplied to customers and volumetric leakages from WDNetXL Figure 3. Pressure at nodes in Taranto WDN from WDNetXL analysis. As specified above, the volumetric leakages are an indicator of asset management, and for their evaluation the model used was that in Eq. (1), which represents the leakage model implemented in WDNetXL. In this phase, βk was calibrated considering the inverse proportionality of leakages with the pipe diameter. Therefore, for each pipe a different βk was assumed, leading to an average value for β equal to x 10-8 with an average network pressure of 40.5 m. Figures 2 reports the total water volumes supplied to customers and the volumetric leakages for each hour of a typical daily operating cycle; total volumes enable computing the current water losses percentage (M1b) indicator.

6 Figures 3 shows the layout of pressure at nodes while Figure 4 reports the linear water losses indicator (M1a) in terms of km 3 /(km*year) for each single pipe, that sum up to m 3 /year for the entire network. Comparing Figure 3 and 4, it is evident that areas showing different pressure might result into similar linear water losses indicator values because of different deterioration values. Coupling linear water losses and pressure through the system might provide useful information about critical areas where asset management action should be carried out. Figure 4. Distribution of linear water losses from WDNetXL analysis 4.2 Supporting pressure management In order to demonstrate the usefulness of advanced hydraulic modelling to support asset management decisions, this section shows volumetric leakage reduction achievable implementing a pressure control strategy. Figure 5. Pressure at nodes in Taranto WDN from WDNetXL analysis.

7 Figure 6. Volume of water supplied to customers and volumetric leakages from WDNetXL In more details, it is assumed a DMA design solution among those obtained by applying the methodology in [20] where the setting of pressure reduction valves at three points of the network are simultaneously optimized, reported as circles in Figure 5. The same figure shows the location of closed gate valves as red crosses. Figure 6 reports the volume of water supplied to customers and the volumetric leakages, showing a reduction of about 5000 m 3 /day. 5 Conclusions In recent years effective planning of investments on asset management is becoming an urgent need for water companies. Past heuristic approaches, supported by inappropriate analysis tools, resulted into increase of leakage rate and reduction of service reliability. In Italy, the latest regulation of public utilities is imposing the achievement of WDN performances in terms of macro-indicators including, among others, water losses. In order to cope with this regulation, Acquedotto Pugliese s.p.a. in southern Italy is introducing rational, structured and verifiable decision making procedures, supported by advanced analysis tools developed to overcome the limitations of existing software. In this innovation process, consultant companies play a key role in bringing novel tools and procedures from technical-scientific innovation providers to water companies. This work shows key features of the advanced hydraulic modelling tool, implemented in the WDNetXL system, and its customization for supporting WDN asset management. Pressure driven simulation of all water demand components, including leakages having volumetric impact on global water balance, provides water utilities with direct assessment of macro-indicators on water losses. This information, in turns, enables to compare various asset management options, reducing the risk for ineffective investments. 6 Acknowledgements Data and pictures from WDNetXL provided by IDEA-RT s.r.l. ( Work partially funded by the Development and Cohesion Fund APQ Research Apulia Region Regional program FutureInResearch.

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