D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Engineering and Technology D-index 35 Citations 6,402 229 World Ranking 5172 National Ranking 170

Overview

What is she best known for?

The fields of study she is best known for:

  • Electrical engineering
  • Mechanical engineering
  • Artificial intelligence

Sonia Leva mainly investigates Photovoltaic system, Renewable energy, Artificial neural network, Maximum power point tracking and Control engineering. Her Photovoltaic system research includes elements of Automotive engineering, Electronic engineering and Grid-connected photovoltaic power system. Her Renewable energy research incorporates themes from Electrical network, Production, Simulation and Systems design.

Her Artificial neural network study combines topics from a wide range of disciplines, such as Real-time computing and Smart grid. Her Maximum power point tracking research is multidisciplinary, incorporating perspectives in Solar irradiance and Nonlinear system. Her studies deal with areas such as Systems engineering, Global Positioning System, Energy management and Benchmark as well as Control engineering.

Her most cited work include:

  • Energy comparison of MPPT techniques for PV Systems (317 citations)
  • Modeling Guidelines and a Benchmark for Power System Simulation Studies of Three-Phase Single-Stage Photovoltaic Systems (273 citations)
  • MPPT techniques for PV Systems: Energetic and cost comparison (204 citations)

What are the main themes of her work throughout her whole career to date?

Her primary scientific interests are in Photovoltaic system, Renewable energy, Control theory, Electronic engineering and Automotive engineering. Her study in Photovoltaic system is interdisciplinary in nature, drawing from both Artificial neural network, Reliability engineering, Maximum power point tracking, Grid-connected photovoltaic power system and Control engineering. The study incorporates disciplines such as Solar irradiance, Solar energy and Nonlinear system in addition to Maximum power point tracking.

Her studies examine the connections between Renewable energy and genetics, as well as such issues in Electric power system, with regards to Electrical engineering and Voltage drop. Sonia Leva has researched Control theory in several fields, including Power factor, Wind power, Induction generator, Converters and AC power. Her Electronic engineering research also works with subjects such as

  • Harmonic together with Harmonics and Track circuit,
  • Topology that intertwine with fields like Transformation.

She most often published in these fields:

  • Photovoltaic system (33.48%)
  • Renewable energy (21.59%)
  • Control theory (16.30%)

What were the highlights of her more recent work (between 2016-2021)?

  • Photovoltaic system (33.48%)
  • Renewable energy (21.59%)
  • Artificial neural network (10.57%)

In recent papers she was focusing on the following fields of study:

Her scientific interests lie mostly in Photovoltaic system, Renewable energy, Artificial neural network, Grid and Reliability engineering. She is interested in Photovoltaics, which is a branch of Photovoltaic system. Her Renewable energy study integrates concerns from other disciplines, such as Simulation and Industrial engineering.

Her studies in Artificial neural network integrate themes in fields like Bidding, Weather forecasting, Smart grid and Sensitivity. Her Grid study incorporates themes from Islanding, Distributed generation, Electricity, Control engineering and Mathematical optimization. Her research investigates the connection between Reliability engineering and topics such as Electricity generation that intersect with problems in Production, Fault, Track, Solar micro-inverter and Benchmark.

Between 2016 and 2021, her most popular works were:

  • Analysis and validation of 24 hours ahead neural network forecasting of photovoltaic output power (122 citations)
  • Physical and hybrid methods comparison for the day ahead PV output power forecast (72 citations)
  • Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques (40 citations)

In her most recent research, the most cited papers focused on:

  • Electrical engineering
  • Mechanical engineering
  • Artificial intelligence

Her primary areas of study are Photovoltaic system, Renewable energy, Artificial neural network, Reliability engineering and Real-time computing. Sonia Leva combines Photovoltaic system and Range in her studies. In general Renewable energy study, her work on Microgrid often relates to the realm of Management system, thereby connecting several areas of interest.

Her Artificial neural network research is multidisciplinary, relying on both Bidding, Simulation and Smart grid. Her work in Reliability engineering covers topics such as Electricity generation which are related to areas like Solar micro-inverter, Track, Fault, Electricity market and Operations research. The Real-time computing study combines topics in areas such as Field, Series, Micro grid and Constant.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Energy comparison of MPPT techniques for PV Systems

Roberto Faranda;Sonia Leva;Piazza Leonardo da Vinci.
(2008)

710 Citations

Modeling Guidelines and a Benchmark for Power System Simulation Studies of Three-Phase Single-Stage Photovoltaic Systems

A Yazdani;A R Di Fazio;H Ghoddami;M Russo.
IEEE Transactions on Power Delivery (2011)

399 Citations

MPPT techniques for PV Systems: Energetic and cost comparison

R. Faranda;S. Leva;V. Maugeri.
power and energy society general meeting (2008)

369 Citations

Energy Comparison of Seven MPPT Techniques for PV Systems

Alberto Dolara;Roberto Sebastiano Faranda;Sonia Leva.
Journal of Electromagnetic Analysis and Applications (2009)

277 Citations

Comparison of different physical models for PV power output prediction

Alberto Dolara;Sonia Leva;Giampaolo Manzolini.
Solar Energy (2015)

270 Citations

Analysis and validation of 24 hours ahead neural network forecasting of photovoltaic output power

S. Leva;A. Dolara;F. Grimaccia;M. Mussetta.
Mathematics and Computers in Simulation (2017)

247 Citations

EXPERIMENTAL INVESTIGATION OF PARTIAL SHADING SCENARIOS ON PV (PHOTOVOLTAIC) MODULES

Alberto Dolara;George Cristian Lazaroiu;Sonia Leva;Giampaolo Manzolini.
Energy (2013)

216 Citations

Light Unmanned Aerial Vehicles (UAVs) for Cooperative Inspection of PV Plants

Paolo Bellezza Quater;Francesco Grimaccia;Sonia Leva;Marco Mussetta.
IEEE Journal of Photovoltaics (2014)

208 Citations

Day-Ahead Photovoltaic Forecasting: A Comparison of the Most Effective Techniques

Alfredo Nespoli;Emanuele Ogliari;Sonia Leva;Alessandro Massi Pavan.
Energies (2019)

164 Citations

A Physical Hybrid Artificial Neural Network for Short Term Forecasting of PV Plant Power Output

Alberto Dolara;Francesco Grimaccia;Sonia Leva;Marco Mussetta.
Energies (2015)

160 Citations

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