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Giuseppe M Tina

Università di Catania, Department of Electrical, Electronics and Computer Science Engineering, Faculty Member

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MS, Electrotechnics Engineering, 1988 University of Catania (UdC) Italy; Ph.D., Electrotechnics Engineering, 1992, UdC. Currently he is associate Professor of Electric Energy Systems at UdC. National Academic Qualification as Full Professor in 2013. Guest staff member in Newcastle University (U.K.) in 1992. From 1993 to 1996 he was in the industry with Agip Refineries and ST Microelectronics in Italy, as electrical engineer responsible for electrical facilities operation and maintenance. Associate researcher for INFN ( National Institute for Nuclear Physics), sited in Catania, Italy in 2002. Responsible of Erasmus agreements: Universitè de Corse Pascal Paoli (France); University of Jules Verne (France); TEI of Western Greece (Greece); University of Jaén, Spain. Keynote speaker at 2012 IEEE EPE conference in Iasi Romania. Invited speaker at ICEEAC (Algeria, 2013), WREC (UK, 2014), Splitech (HR 2016). Awarded in 2012 of the Diploma di Excelentia in teaching and research in power system from University “Stefan cel Mare”, Suceava, Romania; best paper regular session in SEB 2014. Member of the Editorial Board of International Journal of Sustainable Energy (from 2015) and Helyion (from 2016). Speaker in international conferences (43). Co-author of 189 scientific papers: International journals (68), conference proceedings (118) and chapter of books (3), on the subject of electrical power systems and, in particular, on: analysis and modelling of Wind and Photovoltaic generation systems, DGSs (Dispersed Generation Systems), Energy and Ancillary Services Market, Stationary applications of Hydrogen Technology, photovoltaic/thermal (PV/T) systems, monitoring and diagnostic of photovoltaic systems. Responsible of power system research group and lab at UdC (6 y). He is a Member of the IEEE (20 y) and Power and Energy Society (12 y). Vice-president of the section of Catania of the Italian Federation AEIT ( 2010-2015). Coordinator of regional and national research grants.

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Papers by Giuseppe M Tina

A radial basis function neural network based approach for the electrical characteristics estimation of a photovoltaic module

by Giuseppe M Tina and Christian Napoli

Applied Energy, 2012

Technical and Economic Perspective for Repowering of Micro Hydro Power Plants: a Case Study of an Early XX Century Power Plant

by francesco nocera and Giuseppe M Tina

Nowadays many countries have dramatically cut the incentives for solar photovoltaic and wind farm... more Nowadays many countries have dramatically cut the incentives for solar photovoltaic and wind farms; consequently many new investors and entrepreneurs pay more attention to small and mini hydro power plants. Hydropower currently respect to other renewable sources has not negligible benefits as lower cost of installation to equal installed capacity, higher reliability, higher energy production and more intensity and consistency over time. Many aspects as well as the sensibility to environmental issues related to civil works and the introduction of incentives for the production of renewable energy from small plants (< 1 MW) drive the attention to small Hydro Power Plants (HPPs). The thousands of historic mills, water wheels, inoperative hydropower stations or unrealized potential offer an interesting opportunity for small and micro hydropower generation. This article evaluates technical and economic feasibility of the repowering of one of the oldest Sicilian hydro power plant currently abandoned and disused. The reactivation of the Catarrate hydropower plant allows producing energy from renewable source contributing to the energy independence of the local community, with an energy yearly production of about 220 MW. Moreover, this study demonstrates the attractiveness of small hydropower as a local investment vehicle and at same time an occasion to preserve the historical industrial heritage of disused hydro plants.

Intelligent sun-tracking system based on multiple photodiode sensors for maximisation of photovoltaic energy production

by Antonio Gagliano and Giuseppe M Tina

Mathematics and Computers in Simulation, 2013

Photovoltaic Glazing: Analysis of Thermal Behavior and Indoor Comfort

by Giuseppe M Tina, Antonio Gagliano, and Francesco Patania

Energy Procedia, 2013

Technical and Economic Perspective for Repowering of Micro Hydro Power Plants: A Case Study of an Early XX Century Power Plant

by Giuseppe M Tina, Antonio Gagliano, and Francesco Patania

Energy Procedia, 2014

Short-term scheduling of a wind generation and hydrogen storage in the electricity market

SUMMARY Intermittent renewable energy sources (RES) are promising to be the future of electricity... more SUMMARY Intermittent renewable energy sources (RES) are promising to be the future of electricity generation. In particular wind generation, owing to its stochastic behaviour, has to be carefully managed. Its lack of sufficient predictability decreases the energy value in the current framework of electrical markets, therefore, beyond a certain threshold; this kind of generation into the electrical system represents a problem for the transmission system operator (TSO) during its despatching service. The coupling of wind energy conversion system (WECS) with a storage medium (i.e. hydrogen) could improve the programmability of such generation plants in electrical markets. In this paper, an economical optimization tool has been developed in order to find the short-term scheduling so as to maximize the economic revenues in the day-ahead electricity market of a storage plant coupled with a wind farm. This tool needs as input the forecasts of both wind generation power and market prices, obtained with the adoption of pre-processing input data algorithm based on different methods that involve both statistical and probabilistic approaches.

Experimental validation of a probabilistic model for estimating the double axis PV tracking energy production

by Giorgio Graditi and Giuseppe M Tina

This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright a b s t r a c t This work aims to study the impact of different models for the evaluation of the efficiency of a double axis PV tracking system on the monthly probability distribution function of the AC power. Two components of the global efficiency are analysed, that is: the effect of PV cells temperature on the module efficiency and the DC/AC converter efficiency. In particular, the temperature efficiency model combines basic parameters characterizing the array, with the local monthly average temperature and the monthly clearness index to yield a monthly average efficiency. The simulation results are compared with experimental data related to a 9.6 kW p PV plant installed in ENEA research centre located in Portici, Naples (Italy). The tuning of the model is performed by both system measurements and environmental data.

Web interactive non intrusive load disaggregation system for active demand in smart grids

Probability analysis of weather data for energy assessment of hybrid solar/wind power system

4-Phase Interleaved Boost Converter With IC Controller for Distributed Photovoltaic Systems

Ieee Transactions on Circuits and Systems I Regular Papers, Nov 1, 2013

Storage sizing procedure and experimental verification of stand-alone photovoltaic systems

by Valeria Cocina, Paolo Di Leo, Giuseppe M Tina, and Filippo Spertino

2012 IEEE International Energy Conference and Exhibition (ENERGYCON), 2012

Multi-layer thermal models of PV modules for monitoring applications

2012 38th IEEE Photovoltaic Specialists Conference, 2012

ABSTRACT An essential task in devising photovoltaic power plant energy production capacities is b... more ABSTRACT An essential task in devising photovoltaic power plant energy production capacities is based on the evaluation of a PV module thermal behavior from meteorological conditions in a given place. In this context up to 5 °C error in the operating temperature can be acceptable and so simplified (one-layer) models can be adopted. Multi-layer models (three layers) allow not only to calculate more precisely the PV cell temperature but also to evaluate both front and back layer temperatures. The presented five-layer model is useful to evaluate also the front and back cover superficial temperatures. These two temperatures, especially the back temperature, can be measured during the operation of a PV module, so it is likely to tune on-line the thermal model and calculate very precisely the inner temperature. In this paper five multi-layer models, that differ for the modeling of the convective terms into the heat balance equations, are described and checked against measured data on a glass to glass PV module equipped with temperature sensors. The dynamic models have been compared by means of a numerical code implemented in Matlab environment. The numerical results put also in evidence the uncertainties introduced by the environmental variables (ambient temperature, irradiance, wind speed) measurements.

Evaluation and Validation of an Electrical Model of Photovoltaic Module Based on Manufacturer Measurement

Smart Innovation, Systems and Technologies, 2013

SENTINELLA: A WSN for a smart monitoring of PV systems at module level

2013 IEEE International Workshop on Measurements & Networking (M&N), 2013

ABSTRACT Monitoring a PV plant has a remarkable impact on its efficiency. In this context, Wirele... more ABSTRACT Monitoring a PV plant has a remarkable impact on its efficiency. In this context, Wireless Sensor Networks (WSNs) can be a low cost, but reliable solution to perform the real-time monitoring task. The main objective of this work is the realization of a WSN that allows to monitor at panel level the efficiency of Photovoltaic (PV) panels, to provide data useful to investigate on causes of efficiency losses and to detect inertial events possibly related to attempts of theft or tampering but also to mechanical striking events. Nodes of the WSN, which are installed on each PV module, are equipped with voltage, current, irradiance, temperature and inertial sensors. Acquired data are then transferred to a management center which is in charge of estimating efficiency losses and correlated causes, tampering and inertial events at the level of the single module. In particular, this paper is focused on a solution for the automatic estimation of efficiency losses of a PV module and related causes.

Thermal parameter identification of photovoltaic module using genetic algorithm

IET Conference Publications, 2011

Web interactive non intrusive load disaggregation system for energy consumption awareness

AEIT Annual Conference 2013, 2013

Intelligent sun-tracking system based on multiple photodiode sensors for maximisation of photovoltaic energy production

Mathematics and Computers in Simulation, 2013

4-Phase Interleaved Boost Converter With IC Controller for Distributed Photovoltaic Systems

IEEE Transactions on Circuits and Systems I: Regular Papers, 2000

Case study of a grid connected with a battery photovoltaic system: V-trough concentration vs. single-axis tracking

Energy Conversion and Management, 2012

ABSTRACT Photovoltaic systems (PVSs) combined with either some form of storage, such as a battery... more ABSTRACT Photovoltaic systems (PVSs) combined with either some form of storage, such as a battery energy storage system (BESS), or direct load control, can play a crucial role in achieving a more economical operation of the electric utility system while enhancing its reliability with additional energy sources. At the same time, it is also important to use cost-effective PV solutions. In this context, a low-concentration PVS (CPVS) is analysed as a feasible alternative. This paper, present a case study of a complex PVS, composed of two PVSs, a storage system (BEES) and an inverter that allows the system to operate in both the island and grid-connected modes. The first PVS, is a 2.76-kWp single-axis tracking system (azimuth) with modules facing south and tilted 30°, while the second PVS is a dual-axis tracking system, rated 860 Wp, consisting of a concentrator at the flat mirrors (DoubleSun® Four). The system is installed on the roof of the main building of the “ITIS Marconi” school (Italy). A detailed description of the system is provided, and preliminary operating data are presented and discussed. The efficiencies of the PV systems are calculated and measured to evaluate the cost effectiveness of a low-concentration system.

Analysis of forecast errors for irradiance on the horizontal plane

Energy Conversion and Management, 2012

ABSTRACT A major challenge of the next years in global development will be the large scale introd... more ABSTRACT A major challenge of the next years in global development will be the large scale introduction of renewable non-programmable (wind and solar) energy sources into existing energy supply structures. Due mainly to the variability of weather and shadow conditions, the total power production coming from photovoltaic plants in a specified future time period cannot be determined precisely, as it is a nondeterministic and stochastic process. This instability is caused by the dependence of PV generation on meteorological conditions: irradiance and temperature. If meteorological conditions can be forecasted with sufficient precision, it will be possible to estimate the energy a PV system will produce, making photovoltaic a more reliable electricity source. For this reason, in this paper, forecast solar radiation data, provided by two weather providers, have been analyzed. In order to verify their effectiveness, these forecast data have been compared with the measured ones and the errors have been calculated by means of the normalized Root Mean Square Error (nRMSE). Then an algorithm, that allows to classify a day as variable, cloudy, slightly cloudy or clear, has been implemented. Based on this classification, a maximum forecast error is determined. In this context, a neural network has been implemented, it allows to predict the nRMSE of a specific day knowing the percentages of the variable, cloudy, slightly cloudy or clear intervals (considered in that day) calculated on forecast data. Referring to Catania (Italy), experimental data are reported to demonstrate the potentiality of the adopted solutions.

A radial basis function neural network based approach for the electrical characteristics estimation of a photovoltaic module

by Giuseppe M Tina and Christian Napoli

Applied Energy, 2012

Technical and Economic Perspective for Repowering of Micro Hydro Power Plants: a Case Study of an Early XX Century Power Plant

by francesco nocera and Giuseppe M Tina

Nowadays many countries have dramatically cut the incentives for solar photovoltaic and wind farm... more Nowadays many countries have dramatically cut the incentives for solar photovoltaic and wind farms; consequently many new investors and entrepreneurs pay more attention to small and mini hydro power plants. Hydropower currently respect to other renewable sources has not negligible benefits as lower cost of installation to equal installed capacity, higher reliability, higher energy production and more intensity and consistency over time. Many aspects as well as the sensibility to environmental issues related to civil works and the introduction of incentives for the production of renewable energy from small plants (< 1 MW) drive the attention to small Hydro Power Plants (HPPs). The thousands of historic mills, water wheels, inoperative hydropower stations or unrealized potential offer an interesting opportunity for small and micro hydropower generation. This article evaluates technical and economic feasibility of the repowering of one of the oldest Sicilian hydro power plant currently abandoned and disused. The reactivation of the Catarrate hydropower plant allows producing energy from renewable source contributing to the energy independence of the local community, with an energy yearly production of about 220 MW. Moreover, this study demonstrates the attractiveness of small hydropower as a local investment vehicle and at same time an occasion to preserve the historical industrial heritage of disused hydro plants.

Intelligent sun-tracking system based on multiple photodiode sensors for maximisation of photovoltaic energy production

by Antonio Gagliano and Giuseppe M Tina

Mathematics and Computers in Simulation, 2013

Photovoltaic Glazing: Analysis of Thermal Behavior and Indoor Comfort

by Giuseppe M Tina, Antonio Gagliano, and Francesco Patania

Energy Procedia, 2013

Technical and Economic Perspective for Repowering of Micro Hydro Power Plants: A Case Study of an Early XX Century Power Plant

by Giuseppe M Tina, Antonio Gagliano, and Francesco Patania

Energy Procedia, 2014

Short-term scheduling of a wind generation and hydrogen storage in the electricity market

SUMMARY Intermittent renewable energy sources (RES) are promising to be the future of electricity... more SUMMARY Intermittent renewable energy sources (RES) are promising to be the future of electricity generation. In particular wind generation, owing to its stochastic behaviour, has to be carefully managed. Its lack of sufficient predictability decreases the energy value in the current framework of electrical markets, therefore, beyond a certain threshold; this kind of generation into the electrical system represents a problem for the transmission system operator (TSO) during its despatching service. The coupling of wind energy conversion system (WECS) with a storage medium (i.e. hydrogen) could improve the programmability of such generation plants in electrical markets. In this paper, an economical optimization tool has been developed in order to find the short-term scheduling so as to maximize the economic revenues in the day-ahead electricity market of a storage plant coupled with a wind farm. This tool needs as input the forecasts of both wind generation power and market prices, obtained with the adoption of pre-processing input data algorithm based on different methods that involve both statistical and probabilistic approaches.

Experimental validation of a probabilistic model for estimating the double axis PV tracking energy production

by Giorgio Graditi and Giuseppe M Tina

This article appeared in a journal published by Elsevier. The attached copy is furnished to the a... more This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues. Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: http://www.elsevier.com/copyright a b s t r a c t This work aims to study the impact of different models for the evaluation of the efficiency of a double axis PV tracking system on the monthly probability distribution function of the AC power. Two components of the global efficiency are analysed, that is: the effect of PV cells temperature on the module efficiency and the DC/AC converter efficiency. In particular, the temperature efficiency model combines basic parameters characterizing the array, with the local monthly average temperature and the monthly clearness index to yield a monthly average efficiency. The simulation results are compared with experimental data related to a 9.6 kW p PV plant installed in ENEA research centre located in Portici, Naples (Italy). The tuning of the model is performed by both system measurements and environmental data.

Web interactive non intrusive load disaggregation system for active demand in smart grids

Probability analysis of weather data for energy assessment of hybrid solar/wind power system

4-Phase Interleaved Boost Converter With IC Controller for Distributed Photovoltaic Systems

Ieee Transactions on Circuits and Systems I Regular Papers, Nov 1, 2013

Storage sizing procedure and experimental verification of stand-alone photovoltaic systems

by Valeria Cocina, Paolo Di Leo, Giuseppe M Tina, and Filippo Spertino

2012 IEEE International Energy Conference and Exhibition (ENERGYCON), 2012

Multi-layer thermal models of PV modules for monitoring applications

2012 38th IEEE Photovoltaic Specialists Conference, 2012

ABSTRACT An essential task in devising photovoltaic power plant energy production capacities is b... more ABSTRACT An essential task in devising photovoltaic power plant energy production capacities is based on the evaluation of a PV module thermal behavior from meteorological conditions in a given place. In this context up to 5 °C error in the operating temperature can be acceptable and so simplified (one-layer) models can be adopted. Multi-layer models (three layers) allow not only to calculate more precisely the PV cell temperature but also to evaluate both front and back layer temperatures. The presented five-layer model is useful to evaluate also the front and back cover superficial temperatures. These two temperatures, especially the back temperature, can be measured during the operation of a PV module, so it is likely to tune on-line the thermal model and calculate very precisely the inner temperature. In this paper five multi-layer models, that differ for the modeling of the convective terms into the heat balance equations, are described and checked against measured data on a glass to glass PV module equipped with temperature sensors. The dynamic models have been compared by means of a numerical code implemented in Matlab environment. The numerical results put also in evidence the uncertainties introduced by the environmental variables (ambient temperature, irradiance, wind speed) measurements.

Evaluation and Validation of an Electrical Model of Photovoltaic Module Based on Manufacturer Measurement

Smart Innovation, Systems and Technologies, 2013

SENTINELLA: A WSN for a smart monitoring of PV systems at module level

2013 IEEE International Workshop on Measurements & Networking (M&N), 2013

ABSTRACT Monitoring a PV plant has a remarkable impact on its efficiency. In this context, Wirele... more ABSTRACT Monitoring a PV plant has a remarkable impact on its efficiency. In this context, Wireless Sensor Networks (WSNs) can be a low cost, but reliable solution to perform the real-time monitoring task. The main objective of this work is the realization of a WSN that allows to monitor at panel level the efficiency of Photovoltaic (PV) panels, to provide data useful to investigate on causes of efficiency losses and to detect inertial events possibly related to attempts of theft or tampering but also to mechanical striking events. Nodes of the WSN, which are installed on each PV module, are equipped with voltage, current, irradiance, temperature and inertial sensors. Acquired data are then transferred to a management center which is in charge of estimating efficiency losses and correlated causes, tampering and inertial events at the level of the single module. In particular, this paper is focused on a solution for the automatic estimation of efficiency losses of a PV module and related causes.

Thermal parameter identification of photovoltaic module using genetic algorithm

IET Conference Publications, 2011

Web interactive non intrusive load disaggregation system for energy consumption awareness

AEIT Annual Conference 2013, 2013

Intelligent sun-tracking system based on multiple photodiode sensors for maximisation of photovoltaic energy production

Mathematics and Computers in Simulation, 2013

4-Phase Interleaved Boost Converter With IC Controller for Distributed Photovoltaic Systems

IEEE Transactions on Circuits and Systems I: Regular Papers, 2000

Case study of a grid connected with a battery photovoltaic system: V-trough concentration vs. single-axis tracking

Energy Conversion and Management, 2012

ABSTRACT Photovoltaic systems (PVSs) combined with either some form of storage, such as a battery... more ABSTRACT Photovoltaic systems (PVSs) combined with either some form of storage, such as a battery energy storage system (BESS), or direct load control, can play a crucial role in achieving a more economical operation of the electric utility system while enhancing its reliability with additional energy sources. At the same time, it is also important to use cost-effective PV solutions. In this context, a low-concentration PVS (CPVS) is analysed as a feasible alternative. This paper, present a case study of a complex PVS, composed of two PVSs, a storage system (BEES) and an inverter that allows the system to operate in both the island and grid-connected modes. The first PVS, is a 2.76-kWp single-axis tracking system (azimuth) with modules facing south and tilted 30°, while the second PVS is a dual-axis tracking system, rated 860 Wp, consisting of a concentrator at the flat mirrors (DoubleSun® Four). The system is installed on the roof of the main building of the “ITIS Marconi” school (Italy). A detailed description of the system is provided, and preliminary operating data are presented and discussed. The efficiencies of the PV systems are calculated and measured to evaluate the cost effectiveness of a low-concentration system.

Analysis of forecast errors for irradiance on the horizontal plane

Energy Conversion and Management, 2012

ABSTRACT A major challenge of the next years in global development will be the large scale introd... more ABSTRACT A major challenge of the next years in global development will be the large scale introduction of renewable non-programmable (wind and solar) energy sources into existing energy supply structures. Due mainly to the variability of weather and shadow conditions, the total power production coming from photovoltaic plants in a specified future time period cannot be determined precisely, as it is a nondeterministic and stochastic process. This instability is caused by the dependence of PV generation on meteorological conditions: irradiance and temperature. If meteorological conditions can be forecasted with sufficient precision, it will be possible to estimate the energy a PV system will produce, making photovoltaic a more reliable electricity source. For this reason, in this paper, forecast solar radiation data, provided by two weather providers, have been analyzed. In order to verify their effectiveness, these forecast data have been compared with the measured ones and the errors have been calculated by means of the normalized Root Mean Square Error (nRMSE). Then an algorithm, that allows to classify a day as variable, cloudy, slightly cloudy or clear, has been implemented. Based on this classification, a maximum forecast error is determined. In this context, a neural network has been implemented, it allows to predict the nRMSE of a specific day knowing the percentages of the variable, cloudy, slightly cloudy or clear intervals (considered in that day) calculated on forecast data. Referring to Catania (Italy), experimental data are reported to demonstrate the potentiality of the adopted solutions.

Photovoltaic glazing: analysis of thermal behavior and indoor comfort

by francesco nocera and Giuseppe M Tina

The integration of photovoltaic systems into buildings is one of the best ways to exploit effecti... more The integration of photovoltaic systems into buildings is one of the best ways to exploit effectively solar energy and to realize the distributed generation inside urban and suburban environmental. BIPV can be installed in a wide variety of applications such as skylights, roofing, walls and windows but, glazing is perhaps the most promising application. In this context the development of products with the best compromise between electrical efficiency and control of transparency will see the most competition between competing companies and those that win this battle will inevitably come to be successful in the market. Most BIPV glass today uses crystalline silicon absorber layers which are inherently opaque, whereas better transparency could be achieved at a reasonable level of efficiency using other absorber layers such as very thin layers of CIGS or dye sensitive cells. Specifically in this research the thermal behavior of a BIPV glass product using c-Si by means of one-layer model is performed. The PV module temperature is then used to evaluate the thermal radiant field in a sample room. An application to a typical thermal comfort computation is finally presented.