Assessing the Impact of Asset Management on Energy Recovery: The ENERGIDRICA Project ^†

Abstract

The ENERGIDRICA project was born in 2017 at a time of transformation in the “management of water infrastructure” in Italy due to socioeconomic and technological events that have determined the current operational context, in which the “digital transition” represents an opportunity to make the processes related to the management and planning activities for these systems more effective and efficient. The concept of the water–energy nexus is the basis of ENERGIDRICA because an efficient use of energy in aqueducts has positive hydraulic and CO₂-related impacts.

1. Introduction

Energy efficiency plays a key role in aqueducts, encompassing the treatment, pumping, and transportation of water from the sources to the end users. The “Energidrica: energy efficiency in the management of water networks” project aims to develop innovative tools and methodologies for the energy-efficient management of water systems, featuring the creation of decision-support tools and processes. The ongoing digital transition offers a chance to enhance conventional operations through the collection and analysis of data, transforming them into useful information for the efficient management of these systems. Advanced hydraulic modeling of water networks, including the development of a digital twin, enables analyses using Digital Water Services (DWSs) [1]. DWSs allow for the evaluation of different management and operational scenarios [2], incorporating strategies like optimal pump control, pressure management, pipe rehabilitation, reduction in pumping energy consumption, and use of power recovery systems. This approach aims at assisting water service providers in selecting the best solutions to meet their technical, managerial, and economic requirements, crucial for effective management and planning.

This document presents the outcomes of a project related to a water network in Apulia, managed by Acquedotto Pugliese S.p.A. (AQP), a project partner. Asset management strategies developed in collaboration with AQP and their implications for energy efficiency are discussed, including the assessment of energy consumption for pumping and potential recovery through the installation of microturbines at pressure control points.

2. Materials and Methodology

2.1. Advanced Hydraulic Modeling

The advanced hydraulic modeling of water networks is implemented in the WDNetGIS-XL platform, developed by IDEA-RT s.r.l., as stakeholders of the project [3]. Differently from traditional software (e.g., based on EPANET) aimed at designing and verifying water networks, the implemented model incorporates features that are essential for supporting management decisions. Some of the key attributes of the advanced hydraulic model include (i) pressure-driven simulations to evaluate volumetric water losses based on deterioration and average pressure on each pipe; (ii) detailed analysis of hydraulic data (demand and pressure) for individual users (meters at private connections); (iii) accurate simulation of water levels in tanks, allowing for their feeding from the top; (iv) inclusion of several control devices and valves with customizable rules in the hydraulic simulation; (v) assessments of energy consumption and CO₂ production in pumps; (vi) assessment of energy recovery potential through the integration of pressure control and Banki–Mitchell turbines [3]. The WDNetGIS-XL platform’s functionalities are fully interoperable in GIS, supporting the use of DWSs [1]. In line with the evolving concept of digital transformation in the water sector, this model is the bedrock of an advanced approach assisting water network managers, supporting operations focused on water/energy efficiency, combined with integrated data analysis strategies, multi-objective optimization, and complex network theory.

2.2. Methodology to Support the Efficiency of Water Networks

The methodology developed by the project is based on two complementary perspectives, focused on water and energy efficiency, which are considered integrated. In this context, advanced hydraulic modeling via the WDNetGIS-XL platform serves as a bridge between these two areas of efficiency. It provides insights into the hydraulic state of the system across various efficiency scenarios, jointly defined by researchers and AQP technicians based on operational, technical, and economic constraints. Figure 1 illustrates the sequence of technical steps undertaken for this study’s water network.

The process begins with a preliminary phase of analysis of the topological and monitoring data of the network, available to the water company, to construct and validate the network’s geometric model. This model, along with measured data on key hydraulic parameters (e.g., supply flow rate, users’ water consumption, pressure levels, and tank levels), is used to calibrate the water network model [2]. This calibrated model acts as a phenomenological twin of the system under study, enabling the analysis of the main components at which efficiency improvements are targeted, including water losses, energy consumption by pumping systems, and the characteristics and functionality of pressure control devices. In this study, we determine crucial decision variables for six water efficiency scenarios—that include reducing losses through the optimization of pressure control and replacing damaged pipes—and energy efficiency scenarios, such as optimizing pump operations and energy recovery via micro-turbines.

2.3. Case Study

The case study selected by AQP focuses on the network that provides water to the municipalities of Sternatia, Martignano, and Zollino in southern Apulia (Figure 2). Currently, the system operates with two reservoirs: the Corigliano Alto and the Galugnano Vecchio reservoirs. In the proposed efficiency scenarios, the Galugnano Vecchio reservoir will be excluded. The Corigliano Alto reservoir receives water from a group of four wells, of which only one is in constant operation. Additionally, the system includes three pressure control valves (PCVs), one at the entry point of each municipality.

3. Results and Discussion

Table 1. Indicators on the use of water resources.

	Scenario
Indicator	0	1	2	3	4	5
Optimized pressure control	NO	NO	YES	YES	YES	YES
Replacement (%)	0	0	0	16	20	25
Average water supplied volume (m3/year)	626	699	699	555	543	530
Average raised capacity (L/s)	20.3	21.4	20.2	17.1	17.3	17
Average energy consumption (kWh/year)	416	436	413	352	355	348
Average CO2 emissions (kg CO2/m3)	0.69	0.65	0.69	0.66	0.68	0.68
Average CO2 emissions in 24 h (kg CO2/day)	1183.5	1238.4	1174	999.1	1009.3	988.7
Average volume of water losses (m3/year)	426	413	339	269	257	24.5
Energy recovery potential (MWh/year)	30.3	32.3	34.4	31.4	30.9	30.3

presents key indicators related to water resource use, implemented asset management actions, energy consumption, CO₂ emissions, and potential energy recovery through micro-turbines on an annual basis.

These indicators are based on an analysis conducted over a 120 h operational cycle (selecting 5 days from the data provided by AQP). Figure 3a,b visualize the different alternative scenarios regarding water savings achievable through asset management actions, associated energy consumption for pumping, and total recovery potential. The scenarios depicted in the figure are exclusively related to pipeline replacement. It is noted that optimizing pressure control alone can lead to the recovery of more than 75,000 cubic meters of water per year. When this optimization is combined with replacing pipes at a rate exceeding 16% (as seen in scenario 3), the water savings increase to more than 140,000 cubic meters per year. Note that water saving decreases energy recovery. Using the data in

Table 2. Summary of results for each optimal rehabilitation plan.

Scenario	Replacement [%]	Cost [EUR]	# Pipes	Replaced Pipes [m]	Reduction in Losses [m3/day]	Efficiency [-]
3	16%	2294	81	8128	964	2.35
4	20%	2860	100	10,096	1124	2.20
5	25%	3586	135	12,678	1303	2.04

, managers can assess the budget required to implement asset management actions and estimate impact in terms of water and energy savings for each scenario.

4. Conclusions

This paper summarizes alternative strategies based on advanced hydraulic modeling, highlighting their potential to reduce energy consumption, enhance energy recovery, decrease water losses, and improve the efficiency of water networks. Consequently, managers and technicians are equipped with technical and quantitative tools for applying realistic and operational solutions to enhance network performance and ensure superior service quality. In the wider context of the digital transition in the water sector, the outcomes of the Energidrica project contribute by using advanced hydraulic modeling to enrich the knowledge base, realistically simulate system operations, and strengthen the decision-making process, aligned with the current digital transformation efforts.