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Stefano Alvisi   Professor  Senior Scientist or Principal Investigator 
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Stefano Alvisi published an article in February 2019.
Top co-authors See all
Dragan A. Savic

277 shared publications

Centre for Water Systems, University of Exeter, North Park Road, Exeter EX4 4QF, UK

Tommaso Moramarco

117 shared publications

IRPI, Consiglio Nazionale delle Ricerche, via Madonna Alta 126, 06128 Perugia, Italy

Zoran Kapelan

104 shared publications

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

Mauro Venturini

101 shared publications

Dipartimento di Ingegneria, Università degli Studi di Ferrara, Ferrara 44121, Italy Via Giuseppe Saragat, 1

Silvio Simani

99 shared publications

Dipartimento di Ingegneria, Università degli Studi di Ferrara, Via Saragat 1E, 44122 Ferrara (FE), Italy

66
Publications
87
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220
Citations
Publication Record
Distribution of Articles published per year 
(2006 - 2019)
Total number of journals
published in
 
22
 
Publications See all
Article 0 Reads 0 Citations Data-Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants Silvio Simani, Stefano Alvisi, Mauro Venturini Published: 20 February 2019
Electronics, doi: 10.3390/electronics8020237
DOI See at publisher website ABS Show/hide abstract
The interest in the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this end, data-driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes of working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Therefore, the paper aims at providing some guidelines on the design and the application of different data-driven control strategies to a wind turbine benchmark and a hydroelectric simulator. They rely on self-tuning PID, fuzzy logic, adaptive and model predictive control methodologies. Some of the considered methods, such as fuzzy and adaptive controllers, were successfully verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some details of the implementation of the proposed control strategies to these energy conversion systems. The simulations will highlight that the fuzzy regulators are able to provide good tracking capabilities, which are outperformed by adaptive and model predictive control schemes. The working conditions of the considered processes will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many plants.
Article 0 Reads 0 Citations A Comparison of Short-Term Water Demand Forecasting Models E. Pacchin, F. Gagliardi, S. Alvisi, M. Franchini Published: 19 February 2019
Water Resources Management, doi: 10.1007/s11269-019-02213-y
DOI See at publisher website
Article 0 Reads 0 Citations Development of a physics-based model to predict the performance of pumps as turbines Mauro Venturini, Lucrezia Manservigi, Stefano Alvisi, Silvio... Published: 01 December 2018
Applied Energy, doi: 10.1016/j.apenergy.2018.09.054
DOI See at publisher website
PREPRINT 0 Reads 0 Citations Self--Tuning Control Techniques for Wind Turbine and Hydroelectric Plant Systems Silvio Simani, Stefano Alvisi, Mauro Venturini Published: 24 October 2018
doi: 10.20944/preprints201810.0572.v1
DOI See at publisher website ABS Show/hide abstract
The interest on the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this aim, self--tuning control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Some of the considered methods were already verified on wind turbine systems, and important advantages may thus derive from the appropriate implementation of the same control schemes for hydroelectric plants. This represents the key point of the work, which provides some guidelines on the design and the application of these control strategies to these energy conversion systems. In fact, it seems that investigations related with both wind and hydraulic energies present a reduced number of common aspects, thus leading to little exchange and share of possible common points. This consideration is particularly valid with reference to the more established wind area when compared to hydroelectric systems. In this way, this work recalls the models of wind turbine and hydroelectric system, and investigates the application of different control solutions. The scope is to analyse common points in the control objectives and the achievable results from the application of different solutions. Another important point of this investigation regards the analysis of the exploited benchmark models, their control objectives, and the development of the control solutions. The working conditions of these energy conversion systems will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many installations.
PROCEEDINGS-ARTICLE 0 Reads 0 Citations Preliminary GIS Elaborations to Apply Rapid Flood Spreading Models Giulia Farina, Anna Bernini, Stefano Alvisi, Marco Franchini Published: 20 September 2018
doi: 10.29007/wdn6
DOI See at publisher website
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
DOI See at publisher website ABS Show/hide abstract
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.
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