Abstract
Photovoltaic (PV) technology is gaining much interest as a clean, sustainable, noise-free source of energy. However, the non-linear behavior of PV modules and their dependency on varying environmental conditions require thorough study and analysis. Many PV modeling techniques have been introduced in the literature, yet they exhibit several complexity levels for parameter extraction and constants estimation for PV power forecast. Comparatively, a simple, accurate, fast, and user friendly PV modeling technique is proposed in this paper featuring the least computational time and effort. Based on function representation of PV curves’ available in PV datasheets, an empirical mathematical equation is derived. The proposed formula is considered a generic tool capable of modeling any PV device under various weather conditions without either parameter estimation nor power prediction. The proposed model is validated using experimental data of commercial PV panels’ manufacturers under various environmental conditions for different power levels. The obtained results verified the effectiveness of the proposed PV model.
Highlights
With the increasing world-wide demand for renewable energy resources, photovoltaic (PV) systems are gaining much interest
In order to maximize the PV source efficiency under varying environmental conditions, it should be followed by a pulse width modulation (PWM) converter for continuous maximum power point tracking (MPPT) [4]
This model is able to produce characteristic curves for any PV device at any condition based only on four electrical terms found in any practical PV datasheet at standard testing condition (STC)
Summary
With the increasing world-wide demand for renewable energy resources, photovoltaic (PV) systems are gaining much interest. Equivalent circuit-based PV models, applying the Shockley diode equation for solar cell mathematical representation, have been developed and validated using the experimental data given in manufacturers’ datasheets [10]. This equation represents the non-linear characteristics of the PV cell, yet it includes several parameters that are not available in commercial manufacturers’ datasheets, have to be estimated [7,11]. Different mathematical procedures for estimating the unknown PV parameters required are elaborated with different levels of implementation complexity, computational time, and accuracy [24,25,26] These procedures can be analytical, numerical, artificial intelligence-based, evolutionary algorithms-based, or hybrid ones. – Analytical [27,28,29,30,31,32,33,34,35,36,37,38,39,40,41] – Numerical [42,43,44] – Artificial Intelligence [45,46,47] – Evolutionary algorithms [48,49,50,51,52,53] – Hybrid [54,55]
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