Yousef Mahmoud

A Parameterization Approach for Enhancing PV Model Accuracy

Reliable and accurate photovoltaic (PV) models are essential for simulation of PV power systems. A solar cell is typically represented by a single diode equivalent circuit. The circuit parameters need to be estimated accurately to get an accurate model. However, one circuit parameter was assumed because of the limited information provided by commercial manufacturing datasheets, and thus the model accuracy is affected. This paper proposes a parameterization approach for PV models to improve modeling accuracy and reduce implementation complexity. It develops a method to accurately estimate circuit parameters, and thus improving the overall accuracy, relying only on the points provided by all commercial modules datasheet. The proposed modeling approach results in two simplified models demonstrating the advantage of fast simulation. The effectiveness of the modeling approach is thoroughly evaluated by comparing the simulation results with experimental data of solar modules made of mono-crystalline, multi-crystalline, and thin film.

A Simple Approach to Modeling and Simulation of Photovoltaic Modules

An accurate model is essential when designing photovoltaic (PV) systems. PV models rely on a set of transcendental nonlinear equations which add to the model complexity. This letter proposes a simple and easy-to-model approach for implementation in simulations of PV systems. It takes advantage of the simplicity of ideal models and enhances the accuracy by deriving a mathematical representation, capable of extracting accurate estimates of the model parameters, directly related to manufacturer datasheets. Experimental measurements proved the effectiveness of the proposed approach.

A Photovoltaic Model With Reduced Computational Time

Modeling partially shaded photovoltaic (PV) systems for online applications such as model-based MPPTs requires a PV circuit model with low computational time to simulate the large number of connected PV units within a reasonable amount of time. Unfortunately, the accurate PV models available in the literature are complex and suffer from high computational time due to their dependence on a transcendental implicit equation. This paper proposes a photovoltaic circuit model featuring lower computational time and comparable accuracy. The model utilizes the accuracy of the practical PV model and reduces the computational time by replacing the model series resistance with a third-degree-polynomial voltage-dependent source. The proposed model mimics the accurate characteristics of the practical model without being dependent on a transcendental implicit equation, thus providing low computational time. The model also introduces a new parameter to enhance the models accuracy at low irradiance. The effectiveness of the model is shown by comparing the computational time and accuracy of the proposed model with those of the available models. A case study of partially shaded PV systems shows that the percentage of reduction in computational time improves with increases in the number of PV units in a simulated PV system, providing a clear advantage when simulating large PV systems.

An Enhanced MPPT Method Combining Model-Based and Heuristic Techniques

An MPPT approach combining model-based and heuristic techniques has recently appeared in the literature for accelerating the tracking speed of the maximum power point (MPP) of PV systems. Despite the improved tracking speed, it requires an accurate temperature measurement that increases the cost and complexity of the implementation in comparison to the nonmodel-based maximum power point trackers (MPPTs). This paper proposes an MPPT method, which eliminates the need for temperature measurement. The proposed approach relies on a new set of equations capable of estimating the PV module temperature through utilizing the current and voltage measurements. It combines the well-known heuristic P&O and model-based techniques to ensure an accurate and high speed tracking. The proposed method also uniquely adopts a recently developed simple nontranscendental PV model featuring reduced computational time to reduce the computational complexity of the implementation. The effectiveness of the proposed approach is verified using real-time simulation and experimentally.

Fast Power-Peaks Estimator for Partially Shaded PV Systems

Model-based maximum power point tracking (MPPT) techniques have been developed recently to improve the dynamic and steady-state performance of MPPT. Although they are successfully implemented in homogeneous photovoltaic (PV) systems, there is still no model-based MPPT for partially shaded PV systems, mainly because the available models are complex and time consuming. This paper develops a fast modeling approach for partially shaded PV systems. By utilizing three developed rules that govern the formation of power peaks in partially shaded PV systems, the proposed approach can quickly find the power peaks of these systems without simulating the entire power curve. The effectiveness of the proposed approach in finding the power peaks of PV systems quickly and accurately is verified using MATLAB-Simulink and real-time simulator in hardware in the loop application. Moreover, a model-based MPPT is developed utilizing the proposed modeling method. The developed MPPT successfully improves the dynamic performance of power extraction, guarantees the operation on the global maximum power peak, and eliminates oscillating steady-state power losses.

Accuracy Improvement of the Ideal PV Model

The only photovoltaic (PV) model in the literature featuring low computational effort is the ideal PV circuit model because it uniquely relies on a simple nontranscendental equation. Unfortunately, it suffers from a deteriorated accuracy at low irradiance levels. This letter enhances the accuracy of the ideal PV model at low irradiance levels without affecting its simplicity. The proposed approach modifies the equation of the saturation current such that it takes the irradiance variations into consideration. The effect of the proposed modification on the complexity of the model is shown to be negligible. The accuracy improvement is also demonstrated by comparing the proposed and existing ideal models to the measurements provided by the manufacturing datasheet of a monocrystalline PV module.

A Novel MPPT Technique Based on an Image of PV Modules

PV modules operating under partially shaded conditions exhibit multiple peaks in their output power curves, which cause the majority of the maximum power point tracking (MPPT) techniques to become trapped in a local power peak. This unfortunately leads to additional energy losses that could otherwise be harvested if the global maximum power peak (GMPP) were correctly tracked. The available MPPT methods that are able to track the GMPP require periodic scanning of the PV curve, which disturbs the operation of the system and causes energy losses. A new MPPT technique is proposed in this paper that is distinguished by its ability to find the GMPP without the need for periodic curve scanning. The proposed method utilizes the mathematical model of the PV module, as well as the irradiances received by its PV cells, to analytically calculate the location of the GMPP. The required irradiances are innovatively estimated using an image of the PV module captured by an optical camera. The proposed method is also combined with the perturb and observe method to compensate for errors in the model or irradiance estimation. Experimental verifications are conducted to validate the effectiveness of the proposed MPPT method under various shading scenarios.

Fast reconfiguration algorithm for improving the efficiency of PV systems

Photovoltaic power systems lose significant amount of energy due to partial shading which occurs when a part of a PV system is shaded while the rest is fully illuminated. These losses appear in the form of mismatch power losses. Minimizing these losses is fortunately possible through reconfiguring the connections of PV modules in a PV system, as reported recently in the literature. However, the available reconfiguration methods are based on biological optimization which needs long computational time to search for the optimal configuration. Unfortunately, this hinders their practical implementation in large PV systems. A reconfiguration technique that finds the optimal configuration in a reduced computational time is proposed in this paper. Simple rules are developed that can determine the best PV configuration without the need to solve heavy optimization problems. The validity and superiority of the proposed method is verified by comparing its performance to the existing methods under various shading scenarios.

Computational time quantification of the single diode PV models

A range of photovoltaic (PV) models of different accuracy and complexity are available in the literature. The proper PV model for a particular study is selected based on the desired accuracy and computational time. Although the accuracy of the single diode models is well studied, there is still no available quantification for the computational time needed to simulate a certain PV model. This paper studies the computational time of the single diode models and derives empirical formulas quantifying the computational time needed to model PV arrays. This will enable users to calculate the expected simulation time for running their simulation. The results of this paper will help PV researchers and designers select the suitable PV model for simulating a specific PV system.

Toward a long-term evaluation of MPPT techniques in PV systems

Maximum power point tracking (MPPT) is required to extract the maximum available power in PV systems. Wide variety of methods exist in literature, with range of complexity and effectiveness. The features of these diverse methods are usually evaluated at specific environmental conditions for a tiny period, and then the evaluations are generalized for PV systems working under long-term environmental conditions. This makes it unclear which method is better in a location where a certain mixture of environmental conditions could occur. This paper shows that the MPPT evaluations may change under actual environmental conditions for a long period. The paper first provides a classification for the environmental conditions of PV systems. It then tests the most commonly used MPPT methods at long term environmental conditions for evaluating their performance.