Improved MPPT method to increase accuracy and speed in photovoltaic systems under variable atmospheric conditions

Yılmaz, Ünal; Turksoy, Omer; Teke, Ahmet

doi:10.1016/j.ijepes.2019.05.074

Cited by 82 publications

(55 citation statements)

References 44 publications

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“…where R 1 is a small leakage current loss (high‐value kΩ). R 2 is metal grid loss (about 1 Ω), the diode is current associated with p‐n junction

I_{o} = I_{s} - I_{d 1} - I_{R 1},

where I o represents load current, I s is the lossless PV current, I R1 represents parallel resistance leakage current, I d1 is the diode current …”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…R 2 is metal grid loss (about 1 Ω), the diode is current associated with p‐n junction

I_{o} = I_{s} - I_{d 1} - I_{R 1},

where I o represents load current, I s is the lossless PV current, I R1 represents parallel resistance leakage current, I d1 is the diode current

I_{d} = I_{0} \cdot ((), e^{q \cdot \frac{(V + {italicIR}_{S})}{nKT}} - 1),

where n is diode factor, q is the electron charge, I o is reverse saturation current, K is the Boltzmann constant (1.38 × 10 −23 J / K ).…”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…

I_{d} = I_{0} \cdot ((), e^{q \cdot \frac{(V + {italicIR}_{S})}{nKT}} - 1),

where n is diode factor, q is the electron charge, I o is reverse saturation current, K is the Boltzmann constant (1.38 × 10 −23 J / K ). T is the p‐n junction temperature.

I_{ph} = \frac{G}{G_{italicstc}} ((), I_{italicsc, italicref} + μ_{sc} \cdot ((), T - T_{stc})),

where μ sc is the temperature coefficient (short‐circuit current), I sc , ref is the reference short circuit current …”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…where μ sc is the temperature coefficient (short-circuit current), I sc, ref is the reference short circuit current. 18…”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…Temperature, PV panel terminal voltage, and irradiance are utilized as inputs for the proposed method. The effects of the inputs on the MPP voltage were calculated with the following Equations (18).…”

Section: Mppt Methodsmentioning

confidence: 99%

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Improving a battery charger architecture for electric vehicles with photovoltaic system

2020

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Summary In this study, a two‐stage battery charger architecture with high‐efficiency, multi‐input, and output half‐bridge LLC (HBLLC) resonance converter that performs a wide load range is proposed. The first input of the HBLLC is provided by the photovoltaic (PV) panel assembly on the vehicle. A high efficiency and fast maximum power point tracking (MPPT) algorithm has been developed for the PV panel to operate at the maximum power point. The other input is supplied by a grid‐connected AC‐DC bridgeless power factor correction (PFC) converter, which is controlled with the average current mode (ACM) control method. The most important feature that distinguishes the designed topology from previous studies is that it charges the low‐voltage battery through the PV panel. In previous studies, the low‐voltage battery was being charged via the high‐voltage battery. This allowed the high‐voltage battery to transfer power to the low‐voltage battery even when it was not charged. However, in the proposed architecture, the low‐voltage battery is fed by a PV panel. This condition allows the electric vehicle to take more miles with a single charge process. Furthermore, the proposed architecture reduces energy costs in the long term by providing some of the energy demanded from the grid. In addition, the proposed integrated battery charging circuit is intended to reduce the cost of additional cables. The system is designed as 3.1 kW power and operated under no load to full load. As for the performance of the proposed architecture, the peak efficiency of the LLC resonant converter is 95.3%. In addition, peak efficiency of the AC‐DC bridgeless PFC converter is 97.3%, while the power factor is higher than 0.99, input current total harmonic distortion (THD) is less than 5%, MPPT method accuracy is higher than 99%, and output voltage ripples (ΔV) is less than 1 V.

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“…where R 1 is a small leakage current loss (high‐value kΩ). R 2 is metal grid loss (about 1 Ω), the diode is current associated with p‐n junction

I_{o} = I_{s} - I_{d 1} - I_{R 1},

where I o represents load current, I s is the lossless PV current, I R1 represents parallel resistance leakage current, I d1 is the diode current …”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…R 2 is metal grid loss (about 1 Ω), the diode is current associated with p‐n junction

I_{o} = I_{s} - I_{d 1} - I_{R 1},

where I o represents load current, I s is the lossless PV current, I R1 represents parallel resistance leakage current, I d1 is the diode current

I_{d} = I_{0} \cdot ((), e^{q \cdot \frac{(V + {italicIR}_{S})}{nKT}} - 1),

where n is diode factor, q is the electron charge, I o is reverse saturation current, K is the Boltzmann constant (1.38 × 10 −23 J / K ).…”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…

I_{d} = I_{0} \cdot ((), e^{q \cdot \frac{(V + {italicIR}_{S})}{nKT}} - 1),

where n is diode factor, q is the electron charge, I o is reverse saturation current, K is the Boltzmann constant (1.38 × 10 −23 J / K ). T is the p‐n junction temperature.

I_{ph} = \frac{G}{G_{italicstc}} ((), I_{italicsc, italicref} + μ_{sc} \cdot ((), T - T_{stc})),

where μ sc is the temperature coefficient (short‐circuit current), I sc , ref is the reference short circuit current …”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

“…where μ sc is the temperature coefficient (short-circuit current), I sc, ref is the reference short circuit current. 18…”

Section: Pv Panels and Mppt Methodsmentioning

confidence: 99%

Section: Mppt Methodsmentioning

confidence: 99%

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Improving a battery charger architecture for electric vehicles with photovoltaic system

2020

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System identification‐based MPPT algorithm for PV systems under variable atmosphere conditions using current sensorless approach

Çelikel

Gündoğdu

2020

Int Trans Electr Energ Syst

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Summary In photovoltaic power systems operating under variable atmospheric conditions, the success of maximum power point tracking (MPPT) methods is very important for efficiency. Therefore, many different MPPT methods have been developed in the literature. The voltage‐controlled MPPT method is one of the oldest methods that is easy to implement but operates with low efficiency in variable weather conditions. At variable radiation and temperature values, the voltage value that the system must generate in order to capture the MPP point was obtained by modeling the PV system by the system identification. Thus, using only system input and output information, a model was created without the need for system parameters. In this study, system modeling was performed using the Wavenet nonlinear function. The output of the system model gives the reference voltage required to capture the MPP point. Thus, the reference input voltage of the MPPT was made adaptive against changing weather conditions. By using the proposed voltage controlled MPPT method and the other conventional methods such as Incremental Conductance (IC), Perturb and Observe (PO), and Constant Voltage Controller(CVC) methods, various simulations (3 different scenario) were performed in Matlab/Simulink environment. The results obtained from simulations carried out for three different weather conditions were given comparatively. The performance of the proposed method was analyzed in detail at the change points of the temperature and radiation values, and at some other regions.

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Study of the Most Commonly Utilized Maximum Power Point (MPP) Tracking (MPPT) Schemes for SPV Systems

Pathak

Yadav

Alvi

2021

Electrical and Electronic Devices, Circuits, and Materials

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Improved MPPT method to increase accuracy and speed in photovoltaic systems under variable atmospheric conditions

Cited by 82 publications

References 44 publications

Improving a battery charger architecture for electric vehicles with photovoltaic system

Improving a battery charger architecture for electric vehicles with photovoltaic system

System identification‐based MPPT algorithm for PV systems under variable atmosphere conditions using current sensorless approach

Study of the Most Commonly Utilized Maximum Power Point (MPP) Tracking (MPPT) Schemes for SPV Systems

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