Design of Photovoltaic System for IoT Devices

Zungeru, Adamu Murtala; Chuma, Joseph; Duncan, Dauda; Diarra, Birama; Mosalaosi, Modisa; Mtengi, Bokani; Gaboitaolelwe, Jwaone

doi:10.1007/978-3-030-54983-1_4

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…In this paper, the idea of peak solar hours is introduced, in accordance with [37], and preliminary work reported in [38], for the temperature of the cells at 25 0 𝐶, equal to the average temperature of the Palapye in the central district of Botswana. Let's now consider the actual irradiance profile for a particular day as X(t) at which the irradiance of the equivalent x9t) is 1 KW/m 2 during a time of peak solar radiation hours (PSRH).…”

Section: Solar Radiation Hours and Photovoltaic Array Sizingmentioning

confidence: 98%

A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability

Prabaharan

Zungeru

Mtengi

et al. 2023

IJECE

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<span lang="EN-US">In a photovoltaic system, a stable voltage and of tolerable power equilibrium is needed. Hence, a dedicated analog charge controller for a storage system which controls energy flow to impose power equilibrium, and therefore, voltage stability on the load is required. We demonstrate here our successful design considerations employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system, incorporating a dedicated supercapacitor charge controller for the first time. Firstly, we demonstrated a photovoltaic system employing supercapacitors as main energy storage as well as a buffer in a standalone photovoltaic system. Secondly, we design a constant voltage maximum power point tracker (MPPT) for peak power extraction from the photovoltaic generator. Thirdly, we incorporated a supercapacitor charge controller for power equilibrium and voltage stability through a dedicated analog charge controller in our design, the first of its kind. Fourthly, we analyzed the use of supercapacitor storage to mitigate disequilibrium between power supply and demands, which, in turn, causes overvoltage or under voltage across the load. Lastly, we then went ahead to demonstrate the control of the energy flow in the system so as to maintain rated voltage across a variant demand load.</span>

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Section: Solar Radiation Hours and Photovoltaic Array Sizingmentioning

confidence: 98%

A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability

Prabaharan

Zungeru

Mtengi

et al. 2023

IJECE

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“…As a main power source for the departmental greenhouse. The limitations of this system design, as mentioned earlier, and as reported in [5], are:…”

Section: Design Specificationsmentioning

confidence: 99%

“…Meanwhile, several MPPT approaches improve PV systems' efficiency, but MPPT based neural network algorithm has low power losses and complexities compared to other techniques. Preliminary of the work is reported and published in [5]. The past approaches to track maximum power under varying inputs of DC converters are shown in Table 1.…”

Section: Figure 1: Solar Energy Harvesting and Storage System Block D...mentioning

confidence: 99%

“…A solar cell exhibits non-linear characteristics towards ambient irradiance and temperature inputs, its current and voltage curve presents only one maximum power point to track. A maximum Power Point Tracking algorithm is required to interface between the solar panel and the DC-DC converter to deliver maximum power at any point in time [5]. Figure 9…”

Section: Design Of Photovoltaic System and Mpptmentioning

confidence: 99%

“…Off-Grid Power System is a stand-alone source and alternative to conventional sources of power supply. Recent work [1][2][3][4][5][6] has proven that photovoltaic systems could be better in delivering routing cost compared to conventional power generators. Among the energy harvesting methods, photovoltaic has rapidly developed due to its relatively abundant energy source and inexpensive routine cost of operations [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

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Design and Simulation of an Off-Grid Photovoltaic System with Duty Cycle Prediction Using Neural Network Controller

Zungeru

Duncan

Diarra

et al. 2021

JERA

Self Cite

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Global concerns over the inappropriate utilization of abundant renewable energy sources, the damages due to instability of fuel prices, and fossil fuels' effect on the environment have led to an increased interest in green energy (natural power generation) from renewable sources. In renewable energy, photovoltaic is relatively the dominant technique and exhibits non-linearities, leading to inefficiencies. Maximum Power Point is required to be tracked rapidly and improve the power output levels. The target is to use a Neural network controller by training historical data of ambient irradiance and temperature levels as inputs and voltage levels as output for the photovoltaic module to predict duty cycles across the DC-DC converter. The DC-DC converter is the electrical power conditioner at the Botswana International University of Science and Technology, Palapye Off-Grid photovoltaic system. Perturb and Observe algorithm on PSIM environment is only implemented to acquire the historical data for the training and Matlab for the modeling of the network. Relatively long period ambient irradiance and temperature data of Palapye were acquired from the Southern African Science Service Centre for Climate Change and Adaptive Land Management (SASSCAL) WeatherNet in Botswana. Matlab environment was used for the simulation of the backpropagation algorithm for training. The Neural network's feedforward to optimize the non-linear nature of the PV module input and output relationship with relatively fewer processes is required. The results show promising, and the Mean Errors appear to be typically about 0.1 V, and the best performance is 193.5812 at Epoch 13, while the regression delivered a relatively low measured error. The maximum power delivered by the duty cycles from the model with 90 % prediction accuracy. The article demonstrates Neural Network controller is more efficient than the conventional Perturb and Observe Maximum Power Point algorithm.

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Empirical Characterization of Solar Panel Outlay and Dimension for Net-Zero Energy IoT System

Banotra

Mishra

Modem

2022

2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall)

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Design of Photovoltaic System for IoT Devices

Cited by 4 publications

References 15 publications

A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability

A photovoltaic system using supercapacitor energy storage for power equilibrium and voltage stability

Design and Simulation of an Off-Grid Photovoltaic System with Duty Cycle Prediction Using Neural Network Controller

Empirical Characterization of Solar Panel Outlay and Dimension for Net-Zero Energy IoT System

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