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Stefano Alvisi   Professor  Senior Scientist or Principal Investigator 
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Stefano Alvisi published an article in July 2018.
Top co-authors See all
D. Savic

210 shared publications

Full Professor, Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, Univ. of Exeter, North Park Rd., Exeter EX4 4QF, UK

Zoran Kapelan

148 shared publications

Professor, College of Engineering, Mathematics and Physical Sciences, Univ. of Exeter, Harrison Bldg., North Park Rd., Exeter EX4 4QF, U.K.

Marco Franchini

133 shared publications

University of Ferrara, Ferrara, Italy

Mauro Venturini

90 shared publications

Dipartimento di Ingegneria, Università degli Studi di Ferrara, Ferrara 44122, Italy

Enrico Creaco

67 shared publications

Assistant Professor, Dept. of Civil Engineering and Architecture, Univ. of Pavia, Via Ferrata 3, Pavia 27100, Italy; Adjunct Senior Lecturer, School of Civil, Environmental, and Mining Engineering, Univ. of Adelaide, Adelaide 5005, Australia; Honorary Senior Research Fellow, College of Engineering, Mathematics, and Physical Sciences, Univ. of Exeter, Exeter EX4 4QD, UK (corresponding author)

Publication Record
Distribution of Articles published per year 
(2006 - 2018)
Total number of journals
published in
Publications See all
Article 0 Reads 0 Citations From Water Consumption Smart Metering to Leakage Characterization at District and User Level: The GST4Water Project Chiara Luciani, Francesco Casellato, Stefano Alvisi, Marco F... Published: 30 July 2018
Proceedings, doi: 10.3390/proceedings2110675
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This paper presents some of the results achieved within the framework of the GST4Water project concerning the development of a real time monitoring and processing system for water consumption at individual user level. The system is based on the most innovative technologies proposed by the ICT sector and allows for receiving consumption data sent by a generic smart-meter installed in an user’s house and transfer them to a cloud platform. Here, the consumption data are stored and processed in order to characterize leakage at district meter area (DMA) and at individual user level. Finally, the processed data, on the one hand, are returned to the Water Utility and can be used for billing, on the other hand, they provide frequent feedback to the user thus gaining full awareness of his consumption behaviour.
Article 0 Reads 0 Citations Comparison of Different Approaches to Predict the Performance of Pumps As Turbines (PATs) Mauro Venturini, Stefano Alvisi, Silvio Simani, Lucrezia Man... Published: 21 April 2018
Energies, doi: 10.3390/en11041016
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This paper deals with the comparison of different methods which can be used for the prediction of the performance curves of pumps as turbines (PATs). The considered approaches are four, i.e., one physics-based simulation model (“white box” model), two “gray box” models, which integrate theory on turbomachines with specific data correlations, and one “black box” model. More in detail, the modeling approaches are: (1) a physics-based simulation model developed by the same authors, which includes the equations for estimating head, power, and efficiency and uses loss coefficients and specific parameters; (2) a model developed by Derakhshan and Nourbakhsh, which first predicts the best efficiency point of a PAT and then reconstructs their complete characteristic curves by means of two ad hoc equations; (3) the prediction model developed by Singh and Nestmann, which predicts the complete turbine characteristics based on pump shape and size; (4) an Evolutionary Polynomial Regression model, which represents a data-driven hybrid scheme which can be used for identifying the explicit mathematical relationship between PAT and pump curves. All approaches are applied to literature data, relying on both pump and PAT performance curves of head, power, and efficiency over the entire range of operation. The experimental data were provided by Derakhshan and Nourbakhsh for four different turbomachines, working in both pump and PAT mode with specific speed values in the range 1.53–5.82. This paper provides a quantitative assessment of the predictions made by means of the considered approaches and also analyzes consistency from a physical point of view. Advantages and drawbacks of each method are also analyzed and discussed.
Article 0 Reads 0 Citations Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems Manuel Herrera, Silvia Meniconi, Stefano Alvisi, Joaquín Izq... Published: 08 April 2018
Water, doi: 10.3390/w10040440
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This document is intended to be a presentation of the Special Issue “Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems”. The final aim of this Special Issue is to propose a suitable framework supporting insightful hydraulic mechanisms to aid the decision-making processes of water utility managers and practitioners. Its 18 peer-reviewed articles present as varied topics as: water distribution system design, optimization of network performance assessment, monitoring and diagnosis of pressure pipe systems, optimal water quality management, and modelling and forecasting water demand. Overall, these articles explore new research avenues on urban hydraulics and hydroinformatics, showing to be of great value for both Academia and those water utility stakeholders.
Article 4 Reads 1 Citation Energy Production by Means of Pumps As Turbines in Water Distribution Networks Mauro Venturini, Stefano Alvisi, Silvio Simani, Lucrezia Man... Published: 20 October 2017
Energies, doi: 10.3390/en10101666
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This paper deals with the estimation of the energy production by means of pumps used as turbines to exploit residual hydraulic energy, as in the case of available head and flow rate in water distribution networks. To this aim, four pumps with different characteristics are investigated to estimate the producible yearly electric energy. The performance curves of Pumps As Turbines (PATs), which relate head, power, and efficiency to the volume flow rate over the entire PAT operation range, were derived by using published experimental data. The four considered water distribution networks, for which experimental data taken during one year were available, are characterized by significantly different hydraulic features (average flow rate in the range 10–116 L/s; average pressure reduction in the range 12–53 m). Therefore, energy production accounts for actual flow rate and head variability over the year. The conversion efficiency is also estimated, for both the whole water distribution network and the PAT alone.
PREPRINT 1 Read 0 Citations Overview of Modelling and Control Strategies for Wind Turbines and Hydroelectric Systems: Comparisons and Contrasts Silvio Simani, Stefano Alvisi, Mauro Venturini Published: 09 August 2017
ENGINEERING, doi: 10.20944/preprints201708.0034.v1
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Increasingly, there is a focus on utilising renewable energy resources in a bid to fulfil increasing energy requirements and mitigate the climate change impacts of fossil fuels. While most renewable resources are free, the technology used to usefully convert such resources is not and there is an increasing focus on improving the conversion economy and efficiency. To this end, advanced control technologies can have a significant impact and is already a relatively mature technology for wind turbines. Though hydroelectric plants can use simple regulation systems, significant benefits have been shown to accrue from the appropriate use of the same control methods designed for wind turbine plants. This represents the key point of the paper. In fact, to date, the application communities connected with wind and hydraulic energies have had little communication, resulting in little cross fertilisation of control ideas and experience, particularly from the more mature wind area to hydrodynamic systems. Therefore, this paper examines the models and the application of control technology across both domains, both from a comparative and contrasting point of view, with the aim of identifying commonalities in models and control objectives, as well as potential solutions. Key comparative reference points include the articulation of the exployed models, specification of control objectives, development of high--fidelity simulators, and development of solution concepts. Not least, in terms of realistic system requirements are the set of physical and constraints under which such renewable energy systems must operate, and the need to provide reliable and robust control solutions, which respect the often remote and relatively inaccessible location of many onshore and offshore deployments.
Article 3 Reads 4 Citations A Probabilistic Short-Term Water Demand Forecasting Model Based on the Markov Chain Francesca Gagliardi, Stefano Alvisi, Zoran Kapelan, Marco Fr... Published: 12 July 2017
Water, doi: 10.3390/w9070507
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This paper proposes a short-term water demand forecasting method based on the use of the Markov chain. This method provides estimates of future demands by calculating probabilities that the future demand value will fall within pre-assigned intervals covering the expected total variability. More specifically, two models based on homogeneous and non-homogeneous Markov chains were developed and presented. These models, together with two benchmark models (based on artificial neural network and naïve methods), were applied to three real-life case studies for the purpose of forecasting the respective water demands from 1 to 24 h ahead. The results obtained show that the model based on a homogeneous Markov chain provides more accurate short-term forecasts than the one based on a non-homogeneous Markov chain, which is in line with the artificial neural network model. Both Markov chain models enable probabilistic information regarding the stochastic demand forecast to be easily obtained.