A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions

Gil-Velasco, Alfredo; Aguilar-Castillo, Carlos

doi:10.3390/en14092521

Cited by 21 publications

(6 citation statements)

References 27 publications

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“…The authors carried out their research work on different phyllotaxy patterns like 1/3, 2/5, 3/8, etc., and compared the results with conventional arrangements for harnessing the energy from the sun. Gil-Velasco and Aguilar-Castillo [29] studied the harvesting of energy from PV systems using the P&O method and reported that the experimental results were in line with the simulation results. Angadi et al [30] investigated the performance optimization of solar PV systems by applying a perturbation-based MPPT algorithm.…”

Section: Introductionsupporting

confidence: 61%

Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm

Nagadurga

Narasimham²,

Vakula

et al. 2021

Energies

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This paper proposes the application of a metaheuristic algorithm inspired by the social behavior of chimps in nature, called Chimp Optimization Algorithm (ChOA), for the maximum power point tracking of solar photovoltaic (PV) strings. In this algorithm, the chimps hunting process is mathematically articulated, and new mechanisms are designed to perform the exploration and exploitation. To evaluate the ChOA, it is applied to some fixed dimension benchmark functions and engineering problem application of tracking maximum power from solar PV systems under partial shading conditions. Partial shading condition is a common problem that appears in the solar PV modules installed in domestic areas. This shading alters the power developed by the solar PV panel, and exhibits multiple peaks on the power variation with voltage (P-V) characteristic curve. The dynamics of the solar PV system have been considered, and the mathematical model of a single objective function has been framed for tuning the optimal control parameter with the suggested algorithm. Implementing various practical shading patterns of solar PV systems with the ChOA algorithm has shown improved solar power point tracking performance compared to other algorithms in the literature.

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Section: Introductionsupporting

confidence: 61%

Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm

Nagadurga

Narasimham²,

Vakula

et al. 2021

Energies

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“…The concept of a Fractional Characteristic Curve (FCC) derived from a two-diode model has been proposed for estimating GMPP reference values 33 . Mathematical models specifically designed for partial shading scenarios have been studied to calculate voltage reference values, both LMPP and GMPP 34 . Utilizing a parabolic curve to approximate the partial I–V characteristic curve between the MPP and the open-circuit voltage point has been applied to determine the GMPP reference value 35 .…”

Section: Related Workmentioning

confidence: 99%

An adapted model predictive control MPPT for validation of optimum GMPP tracking under partial shading conditions

Siddique,

Zhao,

Rehman

et al. 2024

Sci Rep

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The energy generation efficiency of photovoltaic (PV) systems is compromised by partial shading conditions (PSCs) of solar irradiance with many maximum power points (MPPs) while tracking output power. Addressing this challenge in the PV system, this article proposes an adapted hybrid control algorithm that tracks the global maximum power point (GMPP) by preventing it from settling at different local maximum power points (LMPPs). The proposed scheme involves the deployment of a 3 × 3 multi-string PV array with a single modified boost converter model and an adapted perturb and observe-based model predictive control (APO-MPC) algorithm. In contrast to traditional strategies, this technique effectively extracts and stabilizes the output power by predicting upcoming future states through the computation of reference current. The boost converter regulates voltage and current levels of the whole PV array, while the proposed algorithm dynamically adjusts the converter's operation to track the GMPP by minimizing the cost function of MPC. Additionally, it reduces hardware costs by eliminating the need for an output current sensor, all while ensuring effective tracking across a variety of climatic profiles. The research illustrates the efficient validation of the proposed method with accurate and stable convergence towards the GMPP with minimal sensors, consequently reducing overall hardware expenses. Simulation and hardware-based outcomes reveal that this approach outperforms classical techniques in terms of both cost-effectiveness and power extraction efficiency, even under PSCs of constant, rapidly changing, and linearly changing irradiances.

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“…Then, the P&O tracker did not precisely attain the MPP, but it fluctuated around that point undefined. To remedy this common problem, several improved P&O-based MPPT methods have been proposed in the literature for several renewable energy converters [32,33].…”

Section: Perturb and Observe Mppt Methodsmentioning

confidence: 99%

A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System

2021

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Thermoelectric generators (TEGs) are equipment for transforming thermal power into electricity via the Seebeck effect. These modules have gained increasing interest in research fields related to sustainable energy. The harvested energy is mostly reliant on the differential temperature between the hot and cold areas of the TEGs. Hence, a reliable maximum power point tracker is necessary to operate TEGs too close to their maximum power point (MPP) under an operational and climate variation. In this paper, an optimized fractional incremental resistance tracker (OF-INRT) is suggested to enhance the output performance of a TEG. The introduced tracker is based on the fractional-order PIλDμ control concepts. The optimal parameters of the OF-INRT are determined using a population-based sine cosine algorithm (SCA). To confirm the optimality of the introduced SCA, experiments were conducted and the results compared with those of particle swarm optimization- (PSO) and whale optimization algorithm (WOA) -based techniques. The key goal of the suggested OF-INRT is to overcome the two main issues in conventional trackers, i.e., the slow dynamics of traditional incremental resistance trackers (INRT) and the high steady-state fluctuation around the MPP in the prevalent perturb and observe trackers (POTs). The main findings prove the superiority of the OF-INRT in comparison with the INRT and POT, for both dynamic and steady-state responses.

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A Modification of the Perturb and Observe Method to Improve the Energy Harvesting of PV Systems under Partial Shading Conditions

Cited by 21 publications

References 27 publications

Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm

Enhancing Global Maximum Power Point of Solar Photovoltaic Strings under Partial Shading Conditions Using Chimp Optimization Algorithm

An adapted model predictive control MPPT for validation of optimum GMPP tracking under partial shading conditions

A Sine Cosine Algorithm-Based Fractional MPPT for Thermoelectric Generation System

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