Data from a photovoltaic system using fuzzy logic and the P&O algorithm under sudden changes in solar irradiance and
Carlos Robles Algarín1,2, Omar Rodríguez Álvarez1,2, Adalberto Ospino Castro1,2
1Universidad del Magdalena, Facultad de Ingeniería, Carrera 32 No 22 - 08, Santa Marta, Colombia.
Data in Brief
|November 28, 2018
Summary
This study compares fuzzy logic and Perturb and Observe (P&O) algorithms for photovoltaic (PV) systems. Data shows how these maximum power point tracking (MPPT) controllers perform under varying solar irradiance and temperature conditions.
Area of Science:
- Renewable Energy Engineering
- Control Systems
Background:
- Photovoltaic (PV) systems require efficient maximum power point tracking (MPPT) to optimize energy harvest.
- Sudden environmental changes (solar irradiance, temperature) challenge MPPT controller performance.
Purpose of the Study:
- To present and analyze performance data of fuzzy logic and Perturb and Observe (P&O) MPPT algorithms for a PV system.
- To evaluate controller responses under standard and dynamic operating conditions.
Main Methods:
- Mathematical modeling of PV module and DC-DC converter (from prior work).
- Simulation and data presentation for six cases: standard test conditions and five scenarios with sudden irradiance/temperature changes.
- Comparison of fuzzy logic and P&O controllers.
Main Results:
- Data generated for standard test conditions (1000 W/m², 25°C).
- Performance data under five cases of sudden solar irradiance and temperature variations.
- Theoretical data provided as a reference for controller analysis.
Conclusions:
- The presented data serves as a benchmark for evaluating MPPT controller efficiency.
- The study facilitates analysis of fuzzy logic and P&O controllers under dynamic PV system conditions.
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