Buchumschlag

Computational Intelligence in Photovoltaic Systems

Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant produc...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Ogliari , Emanuele, Leva, Sonia
Format: Online
Sprache:Englisch
Veröffentlicht: MDPI - Multidisciplinary Digital Publishing Institute 2021
Schlagworte:
TA1-2040
T1-995
artificial neural network
online diagnosis
genetic algorithm
renewable energy
unit commitment
photovoltaic panel
power forecasting
metaheuristic
monitoring system
embedded systems
firefly algorithm
tracking system
MPPT algorithm
integrated storage
day-ahead forecast
solar radiation
prototype model
artificial neural networks
parameter extraction
thermal image
thermal model
solar cell
PV cell temperature
evolutionary algorithms
uncertainty
battery
harmony search meta-heuristic algorithm
single-diode photovoltaic model
symbiotic organisms search
photovoltaics
tilt angle
smart photovoltaic system blind
orientation
photovoltaic
particle swarm optimization
analytical methods
computational intelligence
statistical errors
ensemble methods
solar photovoltaic
electrical parameters
demand response
metaheuristic algorithm
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues::TBX History of engineering and technology
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Zusammenfassung:Photovoltaics, among the different renewable energy sources (RES), has become more popular. In recent years, however, many research topics have arisen as a result of the problems that are constantly faced in smart-grid and microgrid operations, such as forecasting of the output of power plant production, storage sizing, modeling, and control optimization of photovoltaic systems. Computational intelligence algorithms (evolutionary optimization, neural networks, fuzzy logic, etc.) have become more and more popular as alternative approaches to conventional techniques for solving problems such as modeling, identification, optimization, availability prediction, forecasting, sizing, and control of stand-alone, grid-connected, and hybrid photovoltaic systems. This Special Issue will investigate the most recent developments and research on solar power systems. This Special Issue “Computational Intelligence in Photovoltaic Systems” is highly recommended for readers with an interest in the various aspects of solar power systems, and includes 10 original research papers covering relevant progress in the following (non-exhaustive) fields: Forecasting techniques (deterministic, stochastic, etc.); DC/AC converter control and maximum power point tracking techniques; Sizing and optimization of photovoltaic system components; Photovoltaics modeling and parameter estimation; Maintenance and reliability modeling; Decision processes for grid operators.

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