Grid Connected PV System with New MPPT Estimation Method Based on Measuring Cells

Morales, Rodrigo; Garbarino, Matías; Muñoz, Javier; Baier, Carlos R.; Rohten, Jaime; Esparza, Vladimir; Dewar, David

doi:10.1109/iecon.2019.8927843

Cited by 9 publications

(8 citation statements)

References 17 publications

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“…The MPPT algorithm gives the voltage reference to the inverter's control, where the voltage reference comes from the measuring cell MPPT based method. This MPPT algorithm is fully detailed in [10], [11] which uses the cell model to estimate the maximum power point and voltage by employing two measuring cells. One cell in open circuit and a second one in short circuit, where two internal PI controllers regulate the variables, based on the model, to reach the temperature and the MPP voltage, which provides the dc voltage reference for the power control.…”

Section: Bpv Array Modelmentioning

confidence: 99%

“…In order to maximize the production of photovoltaic systems, several MPPT algorithms have been developed to find the maximum power point. The most used algorithms are incremental conductance (InC) [8], disturbance and observation (P&O) [9], and measuring cell based (MCB) [10], [11]. These MPPTs have been implemented in dc/dc converters [7], directly in the inverter control strategy [12], where the MPPT imposes the dc link voltage, eliminating the additional dc/dc stage and, therefore, the total efficiency is increased.…”

Section: Introductionmentioning

confidence: 99%

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A Novel Simplified Implementation of Finite-Set Model Predictive Control for Power Converters

et al. 2021

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This paper presents a novel simplified method to implement the finite set -model predictive control technique for photovoltaic generation systems connected to the ac network. This method maintains the advantages of the conventional finite set -model predictive control, such as fast response, simple implementation, and easy understanding; but it also eliminates the use of a cost function and hence the weighting factors, instead, it finds the optimal operating state directly from the model and the discrete number of valid states of the converter. Although the proposed algorithm does not compute a cost function, it is able to select the inverter state that minimizes the tracking error by using a hexagonal convergence region. The main advantage of this technique is to reduce the computational cost in 43% of the algorithm that selects the best state, presenting a simple and complete algorithm without compromising the predictive control performance. The proposed algorithm properly operates under various conditions such as changes in the network frequency and changes in the system parameters.INDEX TERMS Predictive control, Solar power generation, ac-dc power converters, Fast MPC.

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Section: Bpv Array Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Simplified Implementation of Finite-Set Model Predictive Control for Power Converters

et al. 2021

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“…The BPV solar array is connected directly to the NPC inverter, and to follow the maximum power point, the MPPT algorithm of [7] is implemented. This algorithm is based on measuring cells that together with the cell model estimate the M PP voltage which is set to be the DC-link voltage reference.…”

Section: DC Link Controlmentioning

confidence: 99%

“…To increase the efficiency of the photovoltaic systems, several MPPT algorithms have been proposed and the most used ones are perturb and observe (P&O) [3], incremental conductance (InC) [4] and measuring cells based (MCB) [5]. These MPPT algorithms have been implemented in (i) DC/DC converters [6], where the inverter DC link voltage is controlled and independent of the PV MPPT voltage, or (ii) directly on the inverters control strategy [7], where the DC link voltage is imposed by the MPPT, but the additional DC/DC stage is removed and therefore the total efficiency increases.…”

Section: Introductionmentioning

confidence: 99%

MPC Algorithm With Reduced Computational Burden and Fixed Switching Spectrum for a Multilevel Inverter in a Photovoltaic System

et al. 2020

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Renewable energy has gained significant attention of researchers in the last years, mainly due to the importance of using unlimited energy sources to supply homes, industries, cities and countries. In this context, this document focuses on the solar injection by employing a neutral point clamped (NPC) topology together with utilization of a maximum power point tracking (MPPT) and space vector modulation (SVM) techniques. Model predictive control (MPC) is employed to manage the currents and track their references. The proposed algorithms do not employ a cost function to decide which voltage to apply resulting in a spread frequency spectrum, and instead, a concentrated SVM spectrum is imposed. Notwithstanding, the DC link capacitors voltage balance is ensured and the computational burden is notably reduced as compared to traditional Finite Set Model Predictive Control (FS-MPC). Nevertheless, the consistent results are a consequence of the critical analysis that shows the feasibility of the proposal and guarantees the good performance of the entire system in simulated and experimental platforms.

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“…On the other hand, in [19]- [21] the MPPT is obtained through an algorithm that does not use the P-V curve to determine the next step. This algorithm is based on the equations that model a photovoltaic cell, so it uses two measurement cells, one in short-circuit (SC) to obtain the current isc, and another in open-circuit (OC) to obtain the voltage voc, to compute the internal variables and therefore estimate the MPP.…”

Section: Introductionmentioning

confidence: 99%

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

Morales¹,

Rohten²,

Garbarino³

et al. 2022

IEEE Access

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Solar power generation has become a solution to mitigate the severe effects on the everyday higher prices of fossil fuels. Additionally, renewable energies operation -as solar-results in a non-polluting way to supply energy, being of special interest into highly contaminated cities and/or countries. The solar energy efficiency injection system is known to be high and mainly due to the power converters effectiveness, which is over of 95% for low and medium voltage. However, this efficiency is reduced when the solar array is partially shaded because traditional maximum power point tracking (MPPT) algorithms are not able to find the maximum power point (MPP) under irregular radiation. This work presents a new algorithm to find the global MPP (GMPP) based upon two MPPTs algorithms used regularly in uniform solar condition (USC), these are the Measuring Cell (MC) and the Perturb and Observe (P&O) methods. The MC ensures to find the surroundings of every local MPP (LMPP) faster and then choose among them the surroundings of the GMPP. Once the surroundings of GMPP are found, the P&O is used to get closer to the GMPP but reducing the DC voltage oscillation to zero hence overcoming the main issue of the P&O. Thus, the proposed algorithm finds the GMPP in two main steps and eliminates the oscillations around the GMPP in steady state, despite the utilization of the P&O. The algorithm is detailed mathematically, illustrated by means of a block diagram, and validated in simulated and experimental results.

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Grid Connected PV System with New MPPT Estimation Method Based on Measuring Cells

Cited by 9 publications

References 17 publications

A Novel Simplified Implementation of Finite-Set Model Predictive Control for Power Converters

A Novel Simplified Implementation of Finite-Set Model Predictive Control for Power Converters

MPC Algorithm With Reduced Computational Burden and Fixed Switching Spectrum for a Multilevel Inverter in a Photovoltaic System

A Novel Global Maximum Power Point Tracking Method Based on Measurement Cells

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