Development of photovoltaic cell models using fundamental modeling approaches

Aidoud, Mohammed; Feraga, Chams-Eddine; Bechouat, Mohcene; Sedraoui, Moussa; Kahla, Sami

doi:10.1016/j.egypro.2019.04.028

Cited by 21 publications

(15 citation statements)

References 20 publications

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“…There are many methods for fine-tuning the PI controller parameters [22] and in this study, the optimal PI controller calculates the best Kp and Ki while taking into account PI parameter tuning to produce a better responsiveness and reference voltage following. The suggested controller structure is shown in Figure 11, and an algorithm to change the parameters Kp and Ki is built using fuzzy logic.…”

Section: Optimal Pi Controllermentioning

confidence: 99%

A robust fuzzy logic PI controller for solar system battery charging

Zerouali¹,

Ougli

Tidhaf³

2023

IJPEDS

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This article discusses a design of a photovoltaic (PV) system that allow charging a battery under variable climatic circumstances. The system under study is composed of two DC-DC converters a boost and Buck converter. The first one is used to extract the maximum power from the PV array through a novel variable step size P&O based MPPT offering a high tracking accuracy compared to classical approaches such PO and INC. The second converters aim at regulating the output voltage and current that feeds the battery using a robust optimal PI (O-PI) which has a faster time response and high accuracy compared to classical PI and PID controllers. The overall system and thecontrol strategies are tested and validated in MATLAB/Simulink environment. The simulations results show the effectiveness and the robustness of the system.

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Section: Optimal Pi Controllermentioning

confidence: 99%

A robust fuzzy logic PI controller for solar system battery charging

Zerouali¹,

Ougli

Tidhaf³

2023

IJPEDS

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“…The photocurrent I ph depends mainly on the irradiance and the temperature 38

{I}_{\mathrm{ph}}=\frac{S}{{S}_{\mathrm{ref}}}[{I}_{\mathrm{sc},\mathrm{ref}}+{K}_{i}(T-{T}_{\mathrm{ref}})],

where S is the solar irradiance; S ref , the reference solar irradiance (1000 W/m 2 ); I sc,ref , the cell's short‐circuit current under the standard test condition (STC); K i , the temperature coefficient of short circuit current; T ref , the reference temperature (298 K).…”

Section: Mathematical Modeling Of Pv Cell and Arraymentioning

confidence: 99%

“…Assuming that the numbers in series and in parallel are defined as N s and N p , the output current and voltage generated by a PV array can be expressed by 38

{I}_{\mathrm{pv}}={N}_{p}\bullet I,

{V}_{\mathrm{pv}}={N}_{s}\bullet V.

…”

Section: Mathematical Modeling Of Pv Cell and Arraymentioning

confidence: 99%

Hybrid photovoltaic‐liquid air energy storage system for deep decarbonization

Chen

Feng

et al. 2022

Energy Science & Engineering

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Nowadays most photovoltaic (PV) plants usually use battery energy storage technology to smooth fluctuant power, but batteries have the drawbacks of a short lifetime and environmental pollution. The existing renewable power networks have serious problems with decarbonizing electricity on the end-user side. This paper investigates a new hybrid photovoltaic-liquid air energy storage (PV-LAES) system to provide solutions for the low-carbon transition for future power and energy networks. In this article, a local PV power plant cooperates with its maximum power point tracking (MPPT)-based boost converter, to generate low-carbon electricity with some uncertain fluctuations.Then a zero-emission-air-based LAES unit is used to absorb the surplus power from the PV plant, and also compensate power for the local load with inadequate power level. This makes the new system save a large proportion of power from main grids, which can also indirectly reduce greenhouse gas emissions. For the MW-class PV-LAES case, results show that the surplus renewable electricity (6.73 MWh) generates 27.12 tons of liquid air for energy backups during the day time, and then the LAES unit has a round-trip efficiency of 47.4% that can discharge a flexible power compensation to the load in the night. Accordingly, the grid power demand reduces significantly from 12.78 to 3.33 MWh in a day. In this way, the annual power savings is estimated to be 3449.25 MWh, and the corresponding carbon emission can be reduced by 2607.63 tons. Regarding the economic performance, the PV-LAES system presents a dynamic payback period of 9.33 years and an accumulated life-cycle net profit of $2,260,011. Overall, the proposed PV-LAES scheme is economically feasible from a life-cycle perspective, and can potentially realize flexible energy interaction with local renewables to achieve an integrated lowcarbon power generation and storage system.

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“…2 and Eqn. 3 express the current ID through the diode D, IP being the current through RP and the generated current at the terminal IPV [3], where IPV could be equally expressed in Eqn. 4.…”

Section: Photovoltaic Energy Harvesting Systemmentioning

confidence: 99%

Optimal Photovoltaic Energy Harvesting System at Remote Seismic Node

Duncan

Zungeru

Mangwala

et al. 2021

Preprint

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We have developed an optimal Photovoltaic Energy Harvesting System at the remote seismic node to sustain the remote seismic node. This node is a continuous application for monitoring the geodynamics of the earth for long-term and persistent. However, due to the constraints of solar cells and low funding of seismic installations, a simple and optimal energy harvesting system is required at the remote seismic node. So, this novel design focuses on using fitting curve equations as models to extract parameters of the photovoltaic module. This is to predict instantaneous duty cycle levels across synchronous buck DC-DC converter for optimal energy conversion. The converter regulates the supercapacitor as energy storage to deliver longer runtime at the remote seismic node. The conventional techniques concentrate on improving the hardware and charging to sustain power at the remote seismic node. Yet, energy is lost by the DC-DC converter, and the lead-acid battery usually used exhibits energy leakage and a shorter lifecycle. Thus, the contribution of this work is to design a relatively less computational maximum power point tracking based on a simple curve fitting technique to sustain the lifecycle of the node. In this proposed design, selected light-dependent resistors to mimic a pyranometer and formulate equations from specific photovoltaic module characteristics are considered. This correlates the optimal duty cycle levels with the ambient irradiance and temperature variables, while validation was done with an experimental setup of Computer Controlled Photovoltaic System. The non-linear characteristics relationship between the irradiance, temperature, and voltage levels is linearized with the selected PV module parameters in curve fitting equation models. These models are implemented in C programming as an algorithm to be processed by 8-bit microcontroller and deliver duty cycle levels across pulse width modulation to drive the converter. The performance of our approach is evaluated with the Computer Controlled Photovoltaic System with a deviation between 2.5 % to 5 % based on tabulated results and graphs.

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Development of photovoltaic cell models using fundamental modeling approaches

Cited by 21 publications

References 20 publications

A robust fuzzy logic PI controller for solar system battery charging

A robust fuzzy logic PI controller for solar system battery charging

Hybrid photovoltaic‐liquid air energy storage system for deep decarbonization

Optimal Photovoltaic Energy Harvesting System at Remote Seismic Node

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