Harvesting solar energy as a renewable energy source has received significant attention through serious studies that could be applied massively. However, the nonlinear nature of photovoltaic (PV) concerning the surrounding environment, especially irradiation and temperature, affects the resulting output. Therefore, the correlation between environmental parameters and PV's energy needs to be studied. This paper presents a design for measuring solar PV parameters monitored on a laboratory scale. The monitoring is based on internet of things (IoT) technology analyzed in realtime. The system was tested in various weather conditions for 18 hours. The results obtained indicate that the output voltage was influenced by the lighting factor of the PV and the surrounding temperature.
This article describes the design of a data system to integrate energy conversion from photovoltaic measurements connected to the power grid. The software used is visual studio, while the hardware uses polycrystalline photovoltaic (PV) with a capacity of 2.08 kW and several sensors that have been integrated into Arduino. Parameter data in measuring the performance of this PV system consists of temperature and humidity sensors to measure the panel surface, direct current (DC) current sensor, DC voltage sensor.
To measure the current and voltage sourced from the electricity network, the module (PZEM-004T) is used. Measurements are designed using a graphical user interface (GUI) on a Visual Studio application that has been interfaced through Arduino programming. The data output on the sensor measurement will simultaneously record the circuit that has been connected to the solar panel and then display it visually in the form of tables and graphs in real time with a delay of 1 minute. The results of PV on grid measurements in sunny weather conditions obtained the maximum value of all measurements with a DC voltage of 221 V, while for an alternating current (AC) voltage of 231.60 V, the DC value reached 1827.17 W while the AC power was 1681 W.
This article presents the system design and prediction performance of a 1kW capacity grid-tied photovoltaic inverter applicable for low or medium-voltage electrical distri-bution networks. System parameters, for instance, the longitude and latitude of the solar plant location, panel orientation, tilt and azimuth angle calculation, feasibility testing, optimal sizing of installment are analyzed in the model and the utility is sim-ulated precisely to construct an efficient solar power plant for residential applications. In this paper, meteorological data are computed to discuss the impact of environmen-tal variables. As regards ensuring reliability and sustenance, a simulation model of the system of interest is tested in the PVsyst software package. Simulation results yield that the optimum energy injected to the national grid from the solar plant, specific pro-duction, and performance ratio are 1676kWh/year, 1552kWh/kWp/year, and 79.29% respectively. Moreover, the predicted carbon footprint reduction is 23.467 tons during the 30 years lifetime of the system. Therefore, the performance assessments affirm the effectiveness of the proposed research.
Sensitivity of solar panel energy conversion at sunrise and sunset on three w...IJECEIAES
The high sunlight intensity in tropical and equatorial regions makes the potential for installing photovoltaic (PV) panels. However, the initial design of PV installations must be analyzed. Their implementation is carried out in buildings with load power for household electricity scale. For this reason, the panel reliability system could be efficient by designing the initial PV requirements using systematic measurements. Collecting data on fluctuating sunlight intensity (unpredictable weather) conditions needs the use of manual measuring tools, namely digital light meters and PV data with sensor integration. The research sample consists of three fluctuating hot weather conditions, namely hot-sunny, hot-cloudy and hot-rainy conditions. These weather conditions were taken because the climate of West Sumatra tends to shift clouds which sometimes cover the sun's rays. The peak PV output for direct current (DC) power generated during hot- sunny conditions reaches 1827.17 W, in sunny-cloudy weather it reaches around 1626.85 W and during sunny-rainy weather conditions the resulting output is 1161.81 W. From daily measurements, the results show that the efficiency of the PV system is strongly influenced by the prevailing weather climate.
Performance of low-cost solar radiation loggerIJECEIAES
In solar power systems, irradiance value data are among the most important parameters. Such data can be used in installing photovoltaic (PV) modules, such as determining the exact location, tilt angle, and required area, for optimal power efficiency. In this study, the comprehensive simulation and implementation of a solar radiation meter with a PV cell and temperature sensor are presented. The irradiance measurement value is based on the power reading generated by the small capacity of the PV cell at a specific load converted into a digital value in the microcontroller using the implicit Newton polynomial interpolation (NPI) equation as a low-cost alternative method. The effect of temperature is included in the conversion to obtain precise measurement results. Firstly, the structure and characteristics of the PV cell are discussed. Secondly, the parameters, measuring method, and conversion of the measurement reading data using the NPI equation are presented to assess the results. Finally, the simulation of the solar radiation meter using the PSIM and implementation of the hardware are conducted to validate the concepts and compare their results. The proposed hardware has an average error of 2.72% in the implementation of the measurement test.
Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
Load frequency control of a two area hybrid system consisting of a grid conne...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
This article describes the design of a data system to integrate energy conversion from photovoltaic measurements connected to the power grid. The software used is visual studio, while the hardware uses polycrystalline photovoltaic (PV) with a capacity of 2.08 kW and several sensors that have been integrated into Arduino. Parameter data in measuring the performance of this PV system consists of temperature and humidity sensors to measure the panel surface, direct current (DC) current sensor, DC voltage sensor.
To measure the current and voltage sourced from the electricity network, the module (PZEM-004T) is used. Measurements are designed using a graphical user interface (GUI) on a Visual Studio application that has been interfaced through Arduino programming. The data output on the sensor measurement will simultaneously record the circuit that has been connected to the solar panel and then display it visually in the form of tables and graphs in real time with a delay of 1 minute. The results of PV on grid measurements in sunny weather conditions obtained the maximum value of all measurements with a DC voltage of 221 V, while for an alternating current (AC) voltage of 231.60 V, the DC value reached 1827.17 W while the AC power was 1681 W.
This article presents the system design and prediction performance of a 1kW capacity grid-tied photovoltaic inverter applicable for low or medium-voltage electrical distri-bution networks. System parameters, for instance, the longitude and latitude of the solar plant location, panel orientation, tilt and azimuth angle calculation, feasibility testing, optimal sizing of installment are analyzed in the model and the utility is sim-ulated precisely to construct an efficient solar power plant for residential applications. In this paper, meteorological data are computed to discuss the impact of environmen-tal variables. As regards ensuring reliability and sustenance, a simulation model of the system of interest is tested in the PVsyst software package. Simulation results yield that the optimum energy injected to the national grid from the solar plant, specific pro-duction, and performance ratio are 1676kWh/year, 1552kWh/kWp/year, and 79.29% respectively. Moreover, the predicted carbon footprint reduction is 23.467 tons during the 30 years lifetime of the system. Therefore, the performance assessments affirm the effectiveness of the proposed research.
Sensitivity of solar panel energy conversion at sunrise and sunset on three w...IJECEIAES
The high sunlight intensity in tropical and equatorial regions makes the potential for installing photovoltaic (PV) panels. However, the initial design of PV installations must be analyzed. Their implementation is carried out in buildings with load power for household electricity scale. For this reason, the panel reliability system could be efficient by designing the initial PV requirements using systematic measurements. Collecting data on fluctuating sunlight intensity (unpredictable weather) conditions needs the use of manual measuring tools, namely digital light meters and PV data with sensor integration. The research sample consists of three fluctuating hot weather conditions, namely hot-sunny, hot-cloudy and hot-rainy conditions. These weather conditions were taken because the climate of West Sumatra tends to shift clouds which sometimes cover the sun's rays. The peak PV output for direct current (DC) power generated during hot- sunny conditions reaches 1827.17 W, in sunny-cloudy weather it reaches around 1626.85 W and during sunny-rainy weather conditions the resulting output is 1161.81 W. From daily measurements, the results show that the efficiency of the PV system is strongly influenced by the prevailing weather climate.
Performance of low-cost solar radiation loggerIJECEIAES
In solar power systems, irradiance value data are among the most important parameters. Such data can be used in installing photovoltaic (PV) modules, such as determining the exact location, tilt angle, and required area, for optimal power efficiency. In this study, the comprehensive simulation and implementation of a solar radiation meter with a PV cell and temperature sensor are presented. The irradiance measurement value is based on the power reading generated by the small capacity of the PV cell at a specific load converted into a digital value in the microcontroller using the implicit Newton polynomial interpolation (NPI) equation as a low-cost alternative method. The effect of temperature is included in the conversion to obtain precise measurement results. Firstly, the structure and characteristics of the PV cell are discussed. Secondly, the parameters, measuring method, and conversion of the measurement reading data using the NPI equation are presented to assess the results. Finally, the simulation of the solar radiation meter using the PSIM and implementation of the hardware are conducted to validate the concepts and compare their results. The proposed hardware has an average error of 2.72% in the implementation of the measurement test.
Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.
This study investigates experimentally the performance of two-dimensional solar tracking systems with reflector using commercial silicon based photovoltaic module, with open and closed loop control systems. Different reflector materials were also investigated. The experiments were performed at the Hashemite University campus in Zarqa at a latitude of 32⁰, in February and March. Photovoltaic output power and performance were analyzed. It was found that the modified photovoltaic module with mirror reflector generated the highest value of power, while the temperature reached a maximum value of 53 ̊ C. The modified module suggested in this study produced 5% more PV power than the two-dimensional solar tracking systems without reflector and produced 12.5% more PV power than the fixed PV module with 26⁰ tilt angle.
Load frequency control of a two area hybrid system consisting of a grid conne...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Monitoring and remote control of a hybrid photovoltaic microgridIJERA Editor
The search of new alternatives for energy supply in island communities has always been a challenge in scientific
and social context. In order to attend these communities, in January 2013 a photovoltaic hybrid microgrid project
had its beginning at Universidade do Vale do Rio dos Sinos (UNISINOS). This paper presents the
characterization and the development of such microgrid, monitored remotely via internet, which allows
visualizing the electrical measurements, energy production and performing remote control actions. This work
also aims increasing the interaction between students of universities to perform laboratory practices. The system
consists of two photovoltaic modules technologies, mono and multicrystalline, totaling 570 Wp, connected to an
energy storage bank of 200 Ah in 24 V and a pure sinusoidal inverter of 1 kW to supply AC voltage loads of 220
V. All acquisition components of data, conversion and management system are located in a control cabinet.
Currently, the microgrid uses the utility grid as an auxiliary generator, simulating an alternative source of energy,
which can be further replaced by fuel cell, biodiesel generator, etc.
Power output from a small solar panel can be affected by its power consumption when it consumes power from the solar panel. There has been a lack of proper research and experiment in the use of small solar panel with tracking systems. Its significance was detailed in this paper where the voltage output are compared with those which were externally powered. The solar trackers and a microcontroller have been designed and fabricated for this research. Due to the use of the tracking system (single axis and dual axis), the power consumption varies from one to another and its effect on the voltage output. Several experiments have been conducted and it was concluded that small solar panels are not efficient enough to utilize with tracking capabilities due to an increase in power consumption. The externally powered system was found to generate 18% more output compared to a selfsustaining system and that the increase in average power consumptions compared to a fixed panel were 31.7% and 82.5% for single-axis and dualaxis tracker respectively. A concrete evidence was made that utilizing solar tracking capabilities for low power rated solar panel is unfeasible.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
Micropower system optimization for the telecommunication towers based on var...IJECEIAES
This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.
An efficient optical inspection of photovoltaic modules deploying edge detec...IJECEIAES
With the enhanced industrial and domestic energy needs, there is a great urge for renewable energy sources because of their eco-friendly nature. Solar energy is crucial among renewable energy sources and there is a great need to optimize and enhance the performance of solar energy usage that is mainly dependent on the system components. The current work has been aimed to discuss the fault detection of photovoltaic (PV) modules by evaluating an efficient, facile inspection algorithm electrical analysis for real-time applications. The paper presents a real-time experimental model for infrared thermography using a thermal imager mounted on a tripod at a suitable distance from the PV modules to capture the images in the best possible way. A novel hybrid algorithm has been proposed and the fault detection along with the electrical parameter analysis has been accurately performed on the PV modules to analyze and process various externally induced faults in the PV systems.
Optimized design of an extreme low power datalogger for photovoltaic panels IJECEIAES
The paper focuses on the design and implementation of a low cost and compact data logger prototype using an extreme low power (XLP) and low pin count programmable interface controllers (PIC) microcontroller using its own flash memory for the periodic data acquisition storage, while many other works focus in the Arduino Eco-system. It is planned to pick four important analog measures from the photovoltaic system, and store them directly as 10-bit numerical counts, this yields to faster data acquisition and storage (no time consuming for mathematical computation to convert each numerical count of raw data to meaningful real-world data). Avoiding the use of any kind of display and keypad, and keeping the ratio run time over sleep time as low as possible, has a maximum impact on lowering the power consumption. This prototype can be serially linked to a personal computer (PC) to view the acquisition of measurements in real time, and to retrieve all collected data through a terminal application. The experimental results are stored in commaseparated values (CSV) files to ease post data analysis with any spread sheet software, for statistical calculations and graphs drawing, in order for instance, to find the faults of the photovoltaic system and optimize its management and its performance.
Design and simulation of stand alone integrated renewable energy system for r...eSAT Journals
Abstract
Present day guided weapon systems, especially tactical class missiles use RF seeker, for target tracking towards terminal engagement. The seeker system including its antenna assembly will be onboard the missile. Due to the missile trajectory corrections, the seeker antenna pointing to the target may get disturbed resulting in track loss. To avoid this track loss, it becomes necessary to stabilize the antenna system in two planes. The fundamental role of stabilization loop in seeker application is to precisely follow the angular rate of the target. In order to achieve this requirement, it is essential to highly isolate the gimbaled antenna from the missile body motion due to the maneuvering of target or low frequency vibration during flight. However, the isolation ratio and stability margin of stabilization loop adopting the gimbaled platform with both low stiffness and heavy inertia are limited by mechanical characteristic such as low resonance frequency and its high magnitude. The selection of proper feedback sensors, modeling of the total system are key features of this project. In the end, the performance and the stability of designed stabilization loop are demonstrated using simulation in both frequency and time domain. The Hardware for the system is under realization by the Industry. The whole scheme is simulated in MATLAB off-line for this project.
Keywords: Missile, RF seeker, Track loss, Stabilization loop, Angular Rate Command, Bore-Sight Error, Maneuvering and Gimbaled Platform.
Design and simulation of stand alone integrated renewable energy system for r...eSAT Journals
Abstract
The availability of energy plays an important role in the development of a country.Electricity availability is essential for economical growth and improvementin quality of life of rural and semi-urban population. In order to achieve this, rural electrification should gain importance. Rural electrification requiresgrid extensionofthe existing power systemto remote areas which is difficult and costly. Impact of burning fossil fuels on environment andrapid depletion increases the supply demand gap. Development of Integrated Renewable Energy System for isolated load is a promisingway outfor rural electrification. Integrated renewable energy systems generate power making use of renewable energy sources that are available regionally which can electrify rural households. In this paper, an attempt has been made to develop an Integrated renewable energy system for power generation using solar and wind resources.Integration of solar and wind systems has been done for supplying isolated load and the model has been implemented in MATLAB/SIMULINK and the results are summarized.
Various Methods are used to Improve the Capacity and Performance of Solar and...ijtsrd
Photovoltaic PV and wind turbine as a renewable form of energy play an important role in the generation of electricity in the sector. So, its marketed to consumers. The output forces of these systems are highly non linear and are dependent on the systems I P and V P characteristics, as well as on the conditions of irradiation. As a consequence, a number of research projects have been carried out to increase performance and produce maximum capacity from PV and wind turbines. This paper provides a brief literature study of the Maximal Power Point Tracker MPPT for these systems. For this purpose, the PV circuit layout with its mathematical model is introduced. The new papers on the various methodologies of design are then reviewed. Gaurav Chilhate | Manish Kethoriya "Various Methods are used to Improve the Capacity and Performance of Solar and Wind Power Systems - A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-5 , August 2022, URL: https://www.ijtsrd.com/papers/ijtsrd50459.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/50459/various-methods-are-used-to-improve-the-capacity-and-performance-of-solar-and-wind-power-systems--a-review/gaurav-chilhate
A vertical wind turbine monitoring system using commercial online digital das...IJECEIAES
The output of a green energy generator is required to be monitor continuously. The monitoring process is important because the performance of the energy gen- erator needs to be known and evaluate. However, monitoring the generator manu- ally and efficiently is troublesome. Moreover, when most of the energy generator located at uneasy to reach or at a very remote place. Added to the cost, human intervention for the monitoring process contributes to the unnecessary bill. All the highlighted limitations can be overcome using an internet cloud base system and application. Most of the existing data logging instruments use a memory card or personal computer in their operation. The stored data is accessible only at a dedicated computer alone. This work presented a complete energy generator interface with a commercial online digital dashboard. The digital dashboard, parameters of the wind turbine, such as the amount of power generates and the magnitude of instantaneous voltage can be monitored, and the recorded data can be accessed quickly, at any time and anyplace.
A Passive Islanding Detection Method for Neutral point clamped Multilevel Inv...IJECEIAES
Presently renewable energies have taken a special place in the world and most of the Distributed Generations (DGs) used in the interconnected power system are utilized, renewable energy resources. Due to the DG‟s advantages, including use of renewable energy such as, clean nature, does not pollute environment and having endless nature the use of these renewable resources to produce electrical energy in the world are increasing in day to day life. One problem with such Distributed generators is an unintentional islanding phenomenon. Islanding occurs when a Distributed Generation continues to energize an isolated part of a power system even after it was disconnected from the main grid, which is surrounded by unpowered lines. Since islanding can cause hazardous conditions for people and equipment which is connected to it. As per IEEE 1547 DG Interconnection standards, islanding should be quickly detected within 2 seconds, by protective relays and inverters that are part of the DG system. In this paper, a new passive method to identify islanding states has been proposed, based on the rate of change of frequency analysis (ROCOF) for a multilevel inverter based solar distributed generation systems. This method is efficient for both connecting DGs to the network with or without the Inverter. This method is more efficient than the existing methods and reducing the Non Detection Zone (NDZ), which is the disadvantage of existing passive methods and also clearly differentiating between the Islanding and Non-islanding events. The simulation results, which are carried on the MATLAB/Simulink environment shows the performance of the proposed method
To tackle the widespread challenges encountered during the management of power flow in electrical networks, the integration of smart grid (S.G)is proposed as a viable solution to address the environmental and economic concerns. In order to enhance overall functionality of the electric power delivery system, operation of the smart grid is governed by data-driven algorithms where various sensors and smart meters are used to collect this data. On other hand, the fluctuating cost of fossil fuels and its negative impact on the environment has incentivized the exploitation of renewable energies in the smart grid. In the present paper, a hybrid Photovoltaic/Wind (PV/Wind) is suggested to supply a smart grid. The objective of this study is to asses the feasibility of a smart grid supplied solely by renewable energy sources. Conceptual standings of this newly suggested model are validated by simulations.
Data quality processing for photovoltaic system measurementsIJECEIAES
The operation and maintenance activities in photovoltaic systems use meteo- rological and electrical measurements that must be reliable to check system performance. The International Electrotechnical Commission (IEC) standards have established general criteria to filter erroneous information; however, there is no standardized process for the evaluation of measurements. In the present work we developed 3 procedures to detect and correct measurements of a pho- tovoltaic system based on the single diode model. The performance evaluation of each criterion was tested with 6 groups of experimental measurements from a 3 kWp installation. Based on the error of the 3 procedures performed, the most unfavorable case has been prioritized. Then, the reduction of errors between the estimated and measured value has been achieved, reducing the number of measurements to be corrected. For the clear sky categories, the coefficient of determination is 0.9975 and 0.9961 for the high irradiance profile. Although an increase of 2.5% for coefficient of determination has been achieved, the overcast sky categories should be analyzed in more detail. Finally, the different causes of measurement error should be analyzed, associated with calibration errors and sensor quality.
This project aims to develop dual axis solar tracker with IOT monitoring system using Arduino. Generally, solar energy is the technology to get useful energy from sunlight. Solar energy has been used in many traditional technologies over the centuries and has been widely used in the absence of other energy supplies. Its usefulness is widespread when awareness of the cost of the environment and the supply is limited by other energy sources such as fuel. The solar tracking system is the most effective technology to improve the efficiency of solar panels by tracking and following the sun's movement. With the help of this system, solar panels can improve the way of sunlight detection so that more electricity can be collected as solar panels can maintain a sunny position. Thus the project discusses the development of two-axis solar-tracking developers using Arduino Uno as main controller the system. For develops this project, four light-dependent resistors (LDRs) have been used for sunlight detection and a maximum light intensity. Two servo motors have been used to rotate the solar panel according to the sun's light source detected by the LDR. Next a WIFI ESP8266 device is used as an intermediary between device and IOT monitoring system. The IOT monitoring system is a website that functions to store data. The efficiency of this system has been tested and compared with a single axial solar tracker. As a result, the two-axis solar tracking system generates more power, voltage and current.
Because of the rapid growth in technology breakthroughs, including
multimedia and cell phones, Telugu character recognition (TCR) has recently
become a popular study area. It is still necessary to construct automated and
intelligent online TCR models, even if many studies have focused on offline
TCR models. The Telugu character dataset construction and validation using
an Inception and ResNet-based model are presented. The collection of 645
letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34×16
Guninthamulu, and 10 Ankelu. The proposed technique aims to efficiently
recognize and identify distinctive Telugu characters online. This model's main
pre-processing steps to achieve its goals include normalization, smoothing,
and interpolation. Improved recognition performance can be attained by using
stochastic gradient descent (SGD) to optimize the model's hyperparameters.
Scientific workload execution on a distributed computing platform such as a
cloud environment is time-consuming and expensive. The scientific workload
has task dependencies with different service level agreement (SLA)
prerequisites at different levels. Existing workload scheduling (WS) designs
are not efficient in assuring SLA at the task level. Alongside, induces higher
costs as the majority of scheduling mechanisms reduce either time or energy.
In reducing, cost both energy and makespan must be optimized together for
allocating resources. No prior work has considered optimizing energy and
processing time together in meeting task level SLA requirements. This paper
presents task level energy and performance assurance-workload scheduling
(TLEPA-WS) algorithm for the distributed computing environment. The
TLEPA-WS guarantees energy minimization with the performance
requirement of the parallel application under a distributed computational
environment. Experiment results show a significant reduction in using energy
and makespan; thereby reducing the cost of workload execution in comparison
with various standard workload execution models.
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Monitoring and remote control of a hybrid photovoltaic microgridIJERA Editor
The search of new alternatives for energy supply in island communities has always been a challenge in scientific
and social context. In order to attend these communities, in January 2013 a photovoltaic hybrid microgrid project
had its beginning at Universidade do Vale do Rio dos Sinos (UNISINOS). This paper presents the
characterization and the development of such microgrid, monitored remotely via internet, which allows
visualizing the electrical measurements, energy production and performing remote control actions. This work
also aims increasing the interaction between students of universities to perform laboratory practices. The system
consists of two photovoltaic modules technologies, mono and multicrystalline, totaling 570 Wp, connected to an
energy storage bank of 200 Ah in 24 V and a pure sinusoidal inverter of 1 kW to supply AC voltage loads of 220
V. All acquisition components of data, conversion and management system are located in a control cabinet.
Currently, the microgrid uses the utility grid as an auxiliary generator, simulating an alternative source of energy,
which can be further replaced by fuel cell, biodiesel generator, etc.
Power output from a small solar panel can be affected by its power consumption when it consumes power from the solar panel. There has been a lack of proper research and experiment in the use of small solar panel with tracking systems. Its significance was detailed in this paper where the voltage output are compared with those which were externally powered. The solar trackers and a microcontroller have been designed and fabricated for this research. Due to the use of the tracking system (single axis and dual axis), the power consumption varies from one to another and its effect on the voltage output. Several experiments have been conducted and it was concluded that small solar panels are not efficient enough to utilize with tracking capabilities due to an increase in power consumption. The externally powered system was found to generate 18% more output compared to a selfsustaining system and that the increase in average power consumptions compared to a fixed panel were 31.7% and 82.5% for single-axis and dualaxis tracker respectively. A concrete evidence was made that utilizing solar tracking capabilities for low power rated solar panel is unfeasible.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
Micropower system optimization for the telecommunication towers based on var...IJECEIAES
This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.
An efficient optical inspection of photovoltaic modules deploying edge detec...IJECEIAES
With the enhanced industrial and domestic energy needs, there is a great urge for renewable energy sources because of their eco-friendly nature. Solar energy is crucial among renewable energy sources and there is a great need to optimize and enhance the performance of solar energy usage that is mainly dependent on the system components. The current work has been aimed to discuss the fault detection of photovoltaic (PV) modules by evaluating an efficient, facile inspection algorithm electrical analysis for real-time applications. The paper presents a real-time experimental model for infrared thermography using a thermal imager mounted on a tripod at a suitable distance from the PV modules to capture the images in the best possible way. A novel hybrid algorithm has been proposed and the fault detection along with the electrical parameter analysis has been accurately performed on the PV modules to analyze and process various externally induced faults in the PV systems.
Optimized design of an extreme low power datalogger for photovoltaic panels IJECEIAES
The paper focuses on the design and implementation of a low cost and compact data logger prototype using an extreme low power (XLP) and low pin count programmable interface controllers (PIC) microcontroller using its own flash memory for the periodic data acquisition storage, while many other works focus in the Arduino Eco-system. It is planned to pick four important analog measures from the photovoltaic system, and store them directly as 10-bit numerical counts, this yields to faster data acquisition and storage (no time consuming for mathematical computation to convert each numerical count of raw data to meaningful real-world data). Avoiding the use of any kind of display and keypad, and keeping the ratio run time over sleep time as low as possible, has a maximum impact on lowering the power consumption. This prototype can be serially linked to a personal computer (PC) to view the acquisition of measurements in real time, and to retrieve all collected data through a terminal application. The experimental results are stored in commaseparated values (CSV) files to ease post data analysis with any spread sheet software, for statistical calculations and graphs drawing, in order for instance, to find the faults of the photovoltaic system and optimize its management and its performance.
Design and simulation of stand alone integrated renewable energy system for r...eSAT Journals
Abstract
Present day guided weapon systems, especially tactical class missiles use RF seeker, for target tracking towards terminal engagement. The seeker system including its antenna assembly will be onboard the missile. Due to the missile trajectory corrections, the seeker antenna pointing to the target may get disturbed resulting in track loss. To avoid this track loss, it becomes necessary to stabilize the antenna system in two planes. The fundamental role of stabilization loop in seeker application is to precisely follow the angular rate of the target. In order to achieve this requirement, it is essential to highly isolate the gimbaled antenna from the missile body motion due to the maneuvering of target or low frequency vibration during flight. However, the isolation ratio and stability margin of stabilization loop adopting the gimbaled platform with both low stiffness and heavy inertia are limited by mechanical characteristic such as low resonance frequency and its high magnitude. The selection of proper feedback sensors, modeling of the total system are key features of this project. In the end, the performance and the stability of designed stabilization loop are demonstrated using simulation in both frequency and time domain. The Hardware for the system is under realization by the Industry. The whole scheme is simulated in MATLAB off-line for this project.
Keywords: Missile, RF seeker, Track loss, Stabilization loop, Angular Rate Command, Bore-Sight Error, Maneuvering and Gimbaled Platform.
Design and simulation of stand alone integrated renewable energy system for r...eSAT Journals
Abstract
The availability of energy plays an important role in the development of a country.Electricity availability is essential for economical growth and improvementin quality of life of rural and semi-urban population. In order to achieve this, rural electrification should gain importance. Rural electrification requiresgrid extensionofthe existing power systemto remote areas which is difficult and costly. Impact of burning fossil fuels on environment andrapid depletion increases the supply demand gap. Development of Integrated Renewable Energy System for isolated load is a promisingway outfor rural electrification. Integrated renewable energy systems generate power making use of renewable energy sources that are available regionally which can electrify rural households. In this paper, an attempt has been made to develop an Integrated renewable energy system for power generation using solar and wind resources.Integration of solar and wind systems has been done for supplying isolated load and the model has been implemented in MATLAB/SIMULINK and the results are summarized.
Various Methods are used to Improve the Capacity and Performance of Solar and...ijtsrd
Photovoltaic PV and wind turbine as a renewable form of energy play an important role in the generation of electricity in the sector. So, its marketed to consumers. The output forces of these systems are highly non linear and are dependent on the systems I P and V P characteristics, as well as on the conditions of irradiation. As a consequence, a number of research projects have been carried out to increase performance and produce maximum capacity from PV and wind turbines. This paper provides a brief literature study of the Maximal Power Point Tracker MPPT for these systems. For this purpose, the PV circuit layout with its mathematical model is introduced. The new papers on the various methodologies of design are then reviewed. Gaurav Chilhate | Manish Kethoriya "Various Methods are used to Improve the Capacity and Performance of Solar and Wind Power Systems - A Review" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-5 , August 2022, URL: https://www.ijtsrd.com/papers/ijtsrd50459.pdf Paper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/50459/various-methods-are-used-to-improve-the-capacity-and-performance-of-solar-and-wind-power-systems--a-review/gaurav-chilhate
A vertical wind turbine monitoring system using commercial online digital das...IJECEIAES
The output of a green energy generator is required to be monitor continuously. The monitoring process is important because the performance of the energy gen- erator needs to be known and evaluate. However, monitoring the generator manu- ally and efficiently is troublesome. Moreover, when most of the energy generator located at uneasy to reach or at a very remote place. Added to the cost, human intervention for the monitoring process contributes to the unnecessary bill. All the highlighted limitations can be overcome using an internet cloud base system and application. Most of the existing data logging instruments use a memory card or personal computer in their operation. The stored data is accessible only at a dedicated computer alone. This work presented a complete energy generator interface with a commercial online digital dashboard. The digital dashboard, parameters of the wind turbine, such as the amount of power generates and the magnitude of instantaneous voltage can be monitored, and the recorded data can be accessed quickly, at any time and anyplace.
A Passive Islanding Detection Method for Neutral point clamped Multilevel Inv...IJECEIAES
Presently renewable energies have taken a special place in the world and most of the Distributed Generations (DGs) used in the interconnected power system are utilized, renewable energy resources. Due to the DG‟s advantages, including use of renewable energy such as, clean nature, does not pollute environment and having endless nature the use of these renewable resources to produce electrical energy in the world are increasing in day to day life. One problem with such Distributed generators is an unintentional islanding phenomenon. Islanding occurs when a Distributed Generation continues to energize an isolated part of a power system even after it was disconnected from the main grid, which is surrounded by unpowered lines. Since islanding can cause hazardous conditions for people and equipment which is connected to it. As per IEEE 1547 DG Interconnection standards, islanding should be quickly detected within 2 seconds, by protective relays and inverters that are part of the DG system. In this paper, a new passive method to identify islanding states has been proposed, based on the rate of change of frequency analysis (ROCOF) for a multilevel inverter based solar distributed generation systems. This method is efficient for both connecting DGs to the network with or without the Inverter. This method is more efficient than the existing methods and reducing the Non Detection Zone (NDZ), which is the disadvantage of existing passive methods and also clearly differentiating between the Islanding and Non-islanding events. The simulation results, which are carried on the MATLAB/Simulink environment shows the performance of the proposed method
To tackle the widespread challenges encountered during the management of power flow in electrical networks, the integration of smart grid (S.G)is proposed as a viable solution to address the environmental and economic concerns. In order to enhance overall functionality of the electric power delivery system, operation of the smart grid is governed by data-driven algorithms where various sensors and smart meters are used to collect this data. On other hand, the fluctuating cost of fossil fuels and its negative impact on the environment has incentivized the exploitation of renewable energies in the smart grid. In the present paper, a hybrid Photovoltaic/Wind (PV/Wind) is suggested to supply a smart grid. The objective of this study is to asses the feasibility of a smart grid supplied solely by renewable energy sources. Conceptual standings of this newly suggested model are validated by simulations.
Data quality processing for photovoltaic system measurementsIJECEIAES
The operation and maintenance activities in photovoltaic systems use meteo- rological and electrical measurements that must be reliable to check system performance. The International Electrotechnical Commission (IEC) standards have established general criteria to filter erroneous information; however, there is no standardized process for the evaluation of measurements. In the present work we developed 3 procedures to detect and correct measurements of a pho- tovoltaic system based on the single diode model. The performance evaluation of each criterion was tested with 6 groups of experimental measurements from a 3 kWp installation. Based on the error of the 3 procedures performed, the most unfavorable case has been prioritized. Then, the reduction of errors between the estimated and measured value has been achieved, reducing the number of measurements to be corrected. For the clear sky categories, the coefficient of determination is 0.9975 and 0.9961 for the high irradiance profile. Although an increase of 2.5% for coefficient of determination has been achieved, the overcast sky categories should be analyzed in more detail. Finally, the different causes of measurement error should be analyzed, associated with calibration errors and sensor quality.
This project aims to develop dual axis solar tracker with IOT monitoring system using Arduino. Generally, solar energy is the technology to get useful energy from sunlight. Solar energy has been used in many traditional technologies over the centuries and has been widely used in the absence of other energy supplies. Its usefulness is widespread when awareness of the cost of the environment and the supply is limited by other energy sources such as fuel. The solar tracking system is the most effective technology to improve the efficiency of solar panels by tracking and following the sun's movement. With the help of this system, solar panels can improve the way of sunlight detection so that more electricity can be collected as solar panels can maintain a sunny position. Thus the project discusses the development of two-axis solar-tracking developers using Arduino Uno as main controller the system. For develops this project, four light-dependent resistors (LDRs) have been used for sunlight detection and a maximum light intensity. Two servo motors have been used to rotate the solar panel according to the sun's light source detected by the LDR. Next a WIFI ESP8266 device is used as an intermediary between device and IOT monitoring system. The IOT monitoring system is a website that functions to store data. The efficiency of this system has been tested and compared with a single axial solar tracker. As a result, the two-axis solar tracking system generates more power, voltage and current.
Similar to A laboratory scale IoT-based measuring of the solar photovoltaic parameters (20)
Because of the rapid growth in technology breakthroughs, including
multimedia and cell phones, Telugu character recognition (TCR) has recently
become a popular study area. It is still necessary to construct automated and
intelligent online TCR models, even if many studies have focused on offline
TCR models. The Telugu character dataset construction and validation using
an Inception and ResNet-based model are presented. The collection of 645
letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34×16
Guninthamulu, and 10 Ankelu. The proposed technique aims to efficiently
recognize and identify distinctive Telugu characters online. This model's main
pre-processing steps to achieve its goals include normalization, smoothing,
and interpolation. Improved recognition performance can be attained by using
stochastic gradient descent (SGD) to optimize the model's hyperparameters.
Scientific workload execution on a distributed computing platform such as a
cloud environment is time-consuming and expensive. The scientific workload
has task dependencies with different service level agreement (SLA)
prerequisites at different levels. Existing workload scheduling (WS) designs
are not efficient in assuring SLA at the task level. Alongside, induces higher
costs as the majority of scheduling mechanisms reduce either time or energy.
In reducing, cost both energy and makespan must be optimized together for
allocating resources. No prior work has considered optimizing energy and
processing time together in meeting task level SLA requirements. This paper
presents task level energy and performance assurance-workload scheduling
(TLEPA-WS) algorithm for the distributed computing environment. The
TLEPA-WS guarantees energy minimization with the performance
requirement of the parallel application under a distributed computational
environment. Experiment results show a significant reduction in using energy
and makespan; thereby reducing the cost of workload execution in comparison
with various standard workload execution models.
Investigating human subjects is the goal of predicting human emotions in the
real world scenario. A significant number of psychological effects require
(feelings) to be produced, directly releasing human emotions. The
development of effect theory leads one to believe that one must be aware of
one's sentiments and emotions to forecast one's behavior. The proposed line
of inquiry focuses on developing a reliable model incorporating
neurophysiological data into actual feelings. Any change in emotional affect
will directly elicit a response in the body's physiological systems. This
approach is named after the notion of Gaussian mixture models (GMM). The
statistical reaction following data processing, quantitative findings on emotion
labels, and coincidental responses with training samples all directly impact the
outcomes that are accomplished. In terms of statistical parameters such as
population mean and standard deviation, the suggested method is evaluated
compared to a technique considered to be state-of-the-art. The proposed
system determines an individual's emotional state after a minimum of 6
iterative learning using the Gaussian expectation-maximization (GEM)
statistical model, in which the iterations tend to continue to zero error. Perhaps
each of these improves predictions while simultaneously increasing the
amount of value extracted.
Early diagnosis of cancers is a major requirement for patients and a
complicated job for the oncologist. If it is diagnosed early, it could have made
the patient more likely to live. For a few decades, fuzzy logic emerged as an
emphatic technique in the identification of diseases like different types of
cancers. The recognition of cancer diseases mostly operated with inexactness,
inaccuracy, and vagueness. This paper aims to design the fuzzy expert system
(FES) and its implementation for the detection of prostate cancer. Specifically,
prostate-specific antigen (PSA), prostate volume (PV), age, and percentage
free PSA (%FPSA) are used to determine prostate cancer risk (PCR), while
PCR serves as an output parameter. Mamdani fuzzy inference method is used
to calculate a range of PCR. The system provides a scale of risk of prostate
cancer and clears the path for the oncologist to determine whether their
patients need a biopsy. This system is fast as it requires minimum calculation
and hence comparatively less time which reduces mortality and morbidity and
is more reliable than other economic systems and can be frequently used by
doctors.
The biomedical profession has gained importance due to the rapid and accurate diagnosis of clinical patients using computer-aided diagnosis (CAD) tools.
The diagnosis and treatment of Alzheimer’s disease (AD) using complementary multimodalities can improve the quality of life and mental state of patients.
In this study, we integrated a lightweight custom convolutional neural network
(CNN) model and nature-inspired optimization techniques to enhance the performance, robustness, and stability of progress detection in AD. A multi-modal
fusion database approach was implemented, including positron emission tomography (PET) and magnetic resonance imaging (MRI) datasets, to create a fused
database. We compared the performance of custom and pre-trained deep learning models with and without optimization and found that employing natureinspired algorithms like the particle swarm optimization algorithm (PSO) algorithm significantly improved system performance. The proposed methodology,
which includes a fused multimodality database and optimization strategy, improved performance metrics such as training, validation, test accuracy, precision, and recall. Furthermore, PSO was found to improve the performance of
pre-trained models by 3-5% and custom models by up to 22%. Combining different medical imaging modalities improved the overall model performance by
2-5%. In conclusion, a customized lightweight CNN model and nature-inspired
optimization techniques can significantly enhance progress detection, leading to
better biomedical research and patient care.
Class imbalance is a pervasive issue in the field of disease classification from
medical images. It is necessary to balance out the class distribution while training a model. However, in the case of rare medical diseases, images from affected
patients are much harder to come by compared to images from non-affected
patients, resulting in unwanted class imbalance. Various processes of tackling
class imbalance issues have been explored so far, each having its fair share of
drawbacks. In this research, we propose an outlier detection based image classification technique which can handle even the most extreme case of class imbalance. We have utilized a dataset of malaria parasitized and uninfected cells. An
autoencoder model titled AnoMalNet is trained with only the uninfected cell images at the beginning and then used to classify both the affected and non-affected
cell images by thresholding a loss value. We have achieved an accuracy, precision, recall, and F1 score of 98.49%, 97.07%, 100%, and 98.52% respectively,
performing better than large deep learning models and other published works.
As our proposed approach can provide competitive results without needing the
disease-positive samples during training, it should prove to be useful in binary
disease classification on imbalanced datasets.
Recently, plant identification has become an active trend due to encouraging
results achieved in plant species detection and plant classification fields
among numerous available plants using deep learning methods. Therefore,
plant classification analysis is performed in this work to address the problem
of accurate plant species detection in the presence of multiple leaves together,
flowers, and noise. Thus, a convolutional neural network based deep feature
learning and classification (CNN-DFLC) model is designed to analyze
patterns of plant leaves and perform classification using generated finegrained feature weights. The proposed CNN-DFLC model precisely estimates
which the given image belongs to which plant species. Several layers and
blocks are utilized to design the proposed CNN-DFLC model. Fine-grained
feature weights are obtained using convolutional and pooling layers. The
obtained feature maps in training are utilized to predict labels and model
performance is tested on the Vietnam plant image (VPN-200) dataset. This
dataset consists of a total number of 20,000 images and testing results are
achieved in terms of classification accuracy, precision, recall, and other
performance metrics. The mean classification accuracy obtained using the
proposed CNN-DFLC model is 96.42% considering all 200 classes from the
VPN-200 dataset.
Big data as a service (BDaaS) platform is widely used by various
organizations for handling and processing the high volume of data generated
from different internet of things (IoT) devices. Data generated from these IoT
devices are kept in the form of big data with the help of cloud computing
technology. Researchers are putting efforts into providing a more secure and
protected access environment for the data available on the cloud. In order to
create a safe, distributed, and decentralised environment in the cloud,
blockchain technology has emerged as a useful tool. In this research paper, we
have proposed a system that uses blockchain technology as a tool to regulate
data access that is provided by BDaaS platforms. We are securing the access
policy of data by using a modified form of ciphertext policy-attribute based
encryption (CP-ABE) technique with the help of blockchain technology. For
secure data access in BDaaS, algorithms have been created using a mix of CPABE with blockchain technology. Proposed smart contract algorithms are
implemented using Eclipse 7.0 IDE and the cloud environment has been
simulated on CloudSim tool. Results of key generation time, encryption time,
and decryption time has been calculated and compared with access control
mechanism without blockchain technology.
Internet of things (IoT) has become one of the eminent phenomena in human
life along with its collaboration with wireless sensor networks (WSNs), due
to enormous growth in the domain; there has been a demand to address the
various issues regarding it such as energy consumption, redundancy, and
overhead. Data aggregation (DA) is considered as the basic mechanism to
minimize the energy efficiency and communication overhead; however,
security plays an important role where node security is essential due to the
volatile nature of WSN. Thus, we design and develop proximate node aware
secure data aggregation (PNA-SDA). In the PNA-SDA mechanism, additional
data is used to secure the original data, and further information is shared with
the proximate node; moreover, further security is achieved by updating the
state each time. Moreover, the node that does not have updated information is
considered as the compromised node and discarded. PNA-SDA is evaluated
considering the different parameters like average energy consumption, and
average deceased node; also, comparative analysis is carried out with the
existing model in terms of throughput and correct packet identification.
Drones provide an alternative progression in protection submissions since
they are capable of conducting autonomous seismic investigations. Recent
advancement in unmanned aerial vehicle (UAV) communication is an internet
of a drone combined with 5G networks. Because of the quick utilization of
rapidly progressed registering frameworks besides 5G officialdoms, the
information from the user is consistently refreshed and pooled. Thus, safety
or confidentiality is vital among clients, and a proficient substantiation
methodology utilizing a vigorous sanctuary key. Conventional procedures
ensure a few restrictions however taking care of the assault arrangements in
information transmission over the internet of drones (IOD) environmental
frameworks. A unique hyperelliptical curve (HEC) cryptographically based
validation system is proposed to provide protected data facilities among
drones. The proposed method has been compared with the existing methods
in terms of packet loss rate, computational cost, and delay and thereby
provides better insight into efficient and secure communication. Finally, the
simulation results show that our strategy is efficient in both computation and
communication.
Monitoring behavior, numerous actions, or any such information is considered
as surveillance and is done for information gathering, influencing, managing,
or directing purposes. Citizens employ surveillance to safeguard their
communities. Governments do this for the purposes of intelligence collection,
including espionage, crime prevention, the defense of a method, a person, a
group, or an item; or the investigation of criminal activity. Using an internet
of things (IoT) rover, the area will be secured with better secrecy and
efficiency instead of humans, will provide an additional safety step. In this
paper, there is a discussion about an IoT rover for remote surveillance based
around a Raspberry Pi microprocessor which will be able to monitor a
closed/open space. This rover will allow safer survey operations and would
help to reduce the risks involved with it.
In a world where climate change looms large the spotlight often shines on
greenhouse gases, but the shadow of man-made aerosols should not be
underestimated. These tiny particles play a pivotal role in disrupting Earth's
radiative equilibrium, yet many mysteries surround their influence on various
physical aspects of our planet. The root of these mysteries lies in the limited
data we have on aerosol sources, formation processes, conversion dynamics,
and collection methods. Aerosols, composed of particulate matter (PM),
sulfates, and nitrates, hold significant sway across the hemisphere. Accurate
measurement demands the refinement of in-situ, satellite, and ground-based
techniques. As aerosols interact intricately with the environment, their full
impact remains an enigma. Enter a groundbreaking study in Morocco that
dared to compare an internet of thing (IoT) system with satellite-based
atmospheric models, with a focus on fine particles below 10 and 2.5
micrometers in diameter. The initial results, particularly in regions abundant
with extraction pits, shed light on the IoT system's potential to decode
aerosols' role in the grand narrative of climate change. These findings inspire
hope as we confront the formidable global challenge of climate change.
The use of technology has a significant impact to reduce the consequences of
accidents. Sensors, small components that detect interactions experienced by
various components, play a crucial role in this regard. This study focuses on
how the MPU6050 sensor module can be used to detect the movement of
people who are falling, defined as the inability of the lower body, including
the hips and feet, to support the body effectively. An airbag system is
proposed to reduce the impact of a fall. The data processing method in this
study involves the use of a threshold value to identify falling motion. The
results of the study have identified a threshold value for falling motion,
including an acceleration relative (AR) value of less than or equal to 0.38 g,
an angle slope of more than or equal to 40 degrees, and an angular velocity
of more than or equal to 30 °/s. The airbag system is designed to inflate
faster than the time of impact, with a gas flow rate of 0.04876 m3
/s and an
inflating time of 0.05 s. The overall system has a specificity value of 100%,
a sensitivity of 85%, and an accuracy of 94%.
The fundamental principle of the paper is that the soil moisture sensor obtains
the moisture content level of the soil sample. The water pump is automatically
activated if the moisture content is insufficient, which causes water to flow
into the soil. The water pump is immediately turned off when the moisture
content is high enough. Smart home, smart city, smart transportation, and
smart farming are just a few of the new intelligent ideas that internet of things
(IoT) includes. The goal of this method is to increase productivity and
decrease manual labour among farmers. In this paper, we present a system for
monitoring and regulating water flow that employs a soil moisture sensor to
keep track of soil moisture content as well as the land’s water level to keep
track of and regulate the amount of water supplied to the plant. The device
also includes an automated led lighting system.
In order to provide sensing services to low-powered IoT devices, wireless sensor networks (WSNs) organize specialized transducers into networks. Energy usage is one of the most important design concerns in WSN because it is very hard to replace or recharge the batteries in sensor nodes. For an energy-constrained network, the clustering technique is crucial in preserving battery life. By strategically selecting a cluster head (CH), a network's load can be balanced, resulting in decreased energy usage and extended system life. Although clustering has been predominantly used in the literature, the concept of chain-based clustering has not yet been explored. As a result, in this paper, we employ a chain-based clustering architecture for data dissemination in the network. Furthermore, for CH selection, we employ the coati optimisation algorithm, which was recently proposed and has demonstrated significant improvement over other optimization algorithms. In this method, the parameters considered for selecting the CH are energy, node density, distance, and the network’s average energy. The simulation results show tremendous improvement over the competitive cluster-based routing algorithms in the context of network lifetime, stability period (first node dead), transmission rate, and the network's power reserves.
The construction industry is an industry that is always surrounded by
uncertainties and risks. The industry is always associated with a threatindustry which has a complex, tedious layout and techniques characterized by
unpredictable circumstances. It comprises a variety of human talents and the
coordination of different areas and activities associated with it. In this
competitive era of the construction industry, delays and cost overruns of the
project are often common in every project and the causes of that are also
common. One of the problems which we are trying to cater to is the improper
handling of materials at the construction site. In this paper, we propose
developing a system that is capable of tracking construction material on site
that would benefit the contractor and client for better control over inventory
on-site and to minimize loss of material that occurs due to theft and misplacing
of materials.
Today, health monitoring relies heavily on technological advancements. This
study proposes a low-power wide-area network (LPWAN) based, multinodal
health monitoring system to monitor vital physiological data. The suggested
system consists of two nodes, an indoor node, and an outdoor node, and the
nodes communicate via long range (LoRa) transceivers. Outdoor nodes use an
MPU6050 module, heart rate, oxygen pulse, temperature, and skin resistance
sensors and transmit sensed values to the indoor node. We transferred the data
received by the master node to the cloud using the Adafruit cloud service. The
system can operate with a coverage of 4.5 km, where the optimal distance
between outdoor sensor nodes and the indoor master node is 4 km. To further
predict fall detection, various machine learning classification techniques have
been applied. Upon comparing various classifier techniques, the decision tree
method achieved an accuracy of 0.99864 with a training and testing ratio of
70:30. By developing accurate prediction models, we can identify high-risk
individuals and implement preventative measures to reduce the likelihood of
a fall occurring. Remote monitoring of the health and physical status of elderly
people has proven to be the most beneficial application of this technology.
The effectiveness of adaptive filters are mainly dependent on the design
techniques and the algorithm of adaptation. The most common adaptation
technique used is least mean square (LMS) due its computational simplicity.
The application depends on the adaptive filter configuration used and are well
known for system identification and real time applications. In this work, a
modified delayed μ-law proportionate normalized least mean square
(DMPNLMS) algorithm has been proposed. It is the improvised version of the
µ-law proportionate normalized least mean square (MPNLMS) algorithm.
The algorithm is realized using Ladner-Fischer type of parallel prefix
logarithmic adder to reduce the silicon area. The simulation and
implementation of very large-scale integration (VLSI) architecture are done
using MATLAB, Vivado suite and complementary metal–oxide–
semiconductor (CMOS) 90 nm technology node using Cadence RTL and
Genus Compiler respectively. The DMPNLMS method exhibits a reduction
in mean square error, a higher rate of convergence, and more stability. The
synthesis results demonstrate that it is area and delay effective, making it
practical for applications where a faster operating speed is required.
The increasing demand for faster, robust, and efficient device development of enabling technology to mass production of industrial research in circuit design deals with challenges like size, efficiency, power, and scalability. This paper, presents a design and analysis of low power high speed full adder using negative capacitance field effecting transistors. A comprehensive study is performed with adiabatic logic and reversable logic. The performance of full adder is studied with metal oxide field effect transistor (MOSFET) and negative capacitance field effecting (NCFET). The NCFET based full adder offers a low power and high speed compared with conventional MOSFET. The complete design and analysis are performed using cadence virtuoso. The adiabatic logic offering low delay of 0.023 ns and reversable logic is offering low power of 7.19 mw.
The global agriculture system faces significant challenges in meeting the
growing demand for food production, particularly given projections that the
world's population will reach 70% by 2050. Hydroponic farming is an
increasingly popular technique in this field, offering a promising solution to
these challenges. This paper will present the improvement of the current
traditional hydroponic method by providing a system that can be used to
monitor and control the important element in order to help the plant grow up
smoothly. This proposed system is quite efficient and user-friendly that can
be used by anyone. This is a combination of a traditional hydroponic system,
an automatic control system and a smartphone. The primary objective is to
develop a smart system capable of monitoring and controlling potential
hydrogen (pH) levels, a key factor that affects hydroponic plant growth.
Ultimately, this paper offers an alternative approach to address the challenges
of the existing agricultural system and promote the production of clean,
disease-free, and healthy food for a better future.
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A laboratory scale IoT-based measuring of the solar photovoltaic parameters
1. International Journal of Reconfigurable and Embedded Systems (IJRES)
Vol. 11, No. 2, July 2022, pp. 135~145
ISSN: 2089-4864, DOI: 10.11591/ijres.v11.i2.pp135-145 135
Journal homepage: http://ijres.iaescore.com
A laboratory scale IoT-based measuring of the solar
photovoltaic parameters
Arsyad Cahya Subrata1,2
, Tole Sutikno1,2
, Sunardi1
, Anggit Pamungkas2
, Watra Arsadiando2
,
Ahmad Raditya Cahya Baswara1
1
Department of Electrical Engineering, Universitas Ahmad Dahlan, Yogyakarta, Indonesia
2
Embedded Systems and Power Electronics Research Group, Yogyakarta, Indonesia
Article Info ABSTRACT
Article history:
Received Mar 2, 2022
Revised Apr 8, 2022
Accepted May 12, 2022
Harvesting solar energy as a renewable energy source has received
significant attention through serious studies that could be applied massively.
However, the nonlinear nature of photovoltaic (PV) concerning the
surrounding environment, especially irradiation and temperature, affects the
resulting output. Therefore, the correlation between environmental
parameters and PV's energy needs to be studied. This paper presents a design
for measuring solar PV parameters monitored on a laboratory scale. The
monitoring is based on internet of things (IoT) technology analyzed in real-
time. The system was tested in various weather conditions for 18 hours. The
results obtained indicate that the output voltage was influenced by the
lighting factor of the PV and the surrounding temperature.
Keywords:
Harvesting solar energy
Internet of things
Laboratory scale
Lighting factor
Solar photovoltaic This is an open access article under the CC BY-SA license.
Corresponding Author:
Tole Sutikno
Department of Electrical Engineering, Universitas Ahmad Dahlan
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, D. I. Yogyakarta 55191, Indonesia
Email: tole@ee.uad.ac.id
1. INTRODUCTION
The generation of electricity from renewable energy sources is a promising solution to the problems
associated with the impact of carbon generated by fossil fuels. Renewable energy sources have been widely
developed because they offer clean and sustainably available energy solutions for conventional non-hydro
technologies [1], [2]. As a renewable energy source technology, photovoltaic (PV) systems are increasingly
being recognized as cost-effective and clean energy technologies [3]–[6]. This allowed PV systems to have
advantages in terms of availability, cost-effectiveness, accessibility, capacity, and efficiency compared to
other renewable energy sources [7].
A study released by the International Energy Agency (IEA) on world energy consumption shows
that solar panel installations in 2050 will supply 45% of the world's demand [8]. Based on the General
National Energy Plan (RUEN) in Presidential Decree No. 22 of 2017 [9], in 2025, Indonesia targets the
development of new and renewable energy by up to 23%. Research and development of solar panel
technology as a renewable energy source needs to be done to increase [10]. Various learning laboratories
install solar panels and windmills as learning tools in the US [11]. Besides being open to the public to know
the performance of solar panels and windmills, the data taken from the laboratory is also used by its members
for further research.
The solar panel system installed far from the monitoring lab is one of the obstacles. The best method
to solve the problem is to adopt a remote monitoring system using a frequently used technique called the
internet of things (IoT) [12], [13]. IoT technology has rapidly expanded into a variety of fields, enabling
2. ISSN: 2089-4864
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136
quick and easy interaction with most everyday objects and assisting in the gathering of much more detailed
information about objects to provide a wide range of new developments [14]–[18].
Measurement of solar panel parameters wirelessly can be done with various communication
protocols. The Bluetooth protocol, as done by Le et al. [19], has the advantage of being a low-cost device.
Bikrat et al. [20], [21] in their studies also used Bluetooth and WiFi protocols in their research. Parameter
data from each solar panel is sent via Bluetooth to the minicomputer, and then the minicomputer sends the
data to the web server via WiFi protocol. However, the minicomputer cannot receive data sent via Bluetooth
if the distance between them is greater than 10 meters. Nkoloma et al. [22] used text messages (short
message service (SMS)) to send data. By using this, data can be sent over long distances, but it is constrained
by data transmission speed and cannot be done quickly. Data transmission utilizing radio frequency protocols
provides advantages in terms of speed of delivery and distances that can be achieved up to 100 meters or
more, depending on the device used. In their studies, Papageorgas et al. [23], Ranhotigamage et al. [24],
Parikh et al. [25], and Shariff et al. [26] used Zigbee, which utilizes radio frequency for data transmission.
The distance that this device can cover is 50 to 60 meters. In their studies, Guerriero et al. [27], [28] used
MiWi, a wireless protocol that uses 2.4 radio frequency as its communication protocol. Spanias et al. [29]
used a smart monitoring device (SMD), that uses radio frequency to detect system failures from solar panels.
Despite being widely used for data transmission, radio frequency incurs higher costs depending on the
desired coverage distance.
By utilizing IoT technology with an internet network, this alternative for sending data can offer
speed and a vast distance. This paper develops IoT technology for sending parameter data from solar panels
and ships it directly to a web server. The data stored on the webserver can then be processed for further
identification for 24 hours. Then, this data can be used as a lesson for researchers to determine the
characteristics of the PV employed in a PV system during the daily cycle and influenced by weather factors.
Also, the proposed system can figure out how much electricity the solar system could produce.
2. PV ENERGY CONVERSION SYSTEM
A PV system generally consists of a PV module, a power conversion device, and a load, as shown in
Figure 1. The configuration of the PV system varies depending on the requirements of the application. For
applications with high voltage requirements, a multilevel power conversion (DC-AC-DC) is usually required
or used in conjunction with a power converter with a high voltage ratio [30]. But when there is a DC load or
a need to charge a battery, the configuration is usually simpler.
Figure 1. PV system configuration
The PV module consists of a combination of PV cells made of pn junction semiconductor material.
Accurate modeling is needed to anticipate the nonlinear structure of the PV module output due to the input
variable temperature and solar irradiation. Figure 2 shows the equivalent circuit of the widely used single-
diode PV model. The cell output current (𝐼𝑐𝑒𝑙𝑙) can be calculated by (2) via Kirchhoff's law.
−𝐼𝑐𝑒𝑙𝑙 − 𝐼𝑆𝐻 + 𝐼𝑃𝐻 − 𝐼𝐷 = 0 (1)
and
𝐼𝑐𝑒𝑙𝑙 = 𝐼𝑃𝐻 − 𝐼0 (𝑒
𝑉𝑐𝑒𝑙𝑙+𝐼𝑐𝑒𝑙𝑙𝑅𝑆
𝑛𝑉𝑡
− 1) −
𝑉𝑐𝑒𝑙𝑙+𝐼𝑐𝑒𝑙𝑙𝑅𝑆
𝑅𝑆𝐻
(2)
3. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864
A laboratory scale IoT-based measuring of the solar photovoltaic parameters (Arsyad Cahya Subrata)
137
where STC-𝐼𝑃𝐻 is the photocurrent generated under standard test conditions, STC-𝐼0 is the saturation current
of the diode, 𝑅𝑆 is the series resistance, 𝑅𝑆𝐻 is the shunt resistance, and ideally diode factor-𝑛 which can be
estimated by the Bisection and Lambert-W methods [31].
Figure 2. Single diode model PV module equivalent circuit
In this system, the PV panel has a voltage of 18 V with an output power of 50 W. The PV panel is
connected to the input of a buck-boost DC-DC converter-type power conversion device. The converter is
embedded in a solar charge control (SCC) device, which is then connected to the load. If the PV panel
generates sufficient power, the SCC will regulate the power supplied to the load and supply power to charge
the battery while it is not fully charged. However, if the PV panel does not have enough power, then the SCC
will arrange for the battery to provide power to the load.
SCC regulates four stages of battery charging, and the charging process diagram is shown in Figure
3. When the battery is not fully charged, in this case, the battery is in the bulk charge stage, and the power
will be fully sent to the battery. The charging process operates at the absorption stage until the battery is
almost at the absorption voltage setpoint. At this stage, a constant voltage is applied for 150–180 minutes
(depending on the type of battery) so that the battery voltage is at the setpoint [32]. Finally, once the battery
is fully charged, the voltage is reduced to a float voltage setpoint so that it can be used to supply the load. If
the load exceeds the SCC current, the battery cannot be maintained at the float setpoint. Also, if the battery
voltage is lower than the setpoint of the float stage for a certain period, then charge back to the bulk stage.
Figure 3. Battery charging stage
3. METHOD
In this process, a system is designed for measuring solar panel parameters, and the purpose is to
measure voltage, current, power, temperature, and light intensity. The LCD is used to display the output of
these parameter values offline, while to store the solar panel parameter values, the microSD and Web Server
are used. The components used in this paper are summarized in Table 1.
4. ISSN: 2089-4864
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138
Table 1. List of components and their functions
Components Function
Solar Panel 50Wp Power generator
12V battery Load and energy backup system
PWM SCC Charging controller
NodeMCU ESP8266 Main controller + WiFi module
Inverter AC load converter
ACS712 5A Current sensor
INA219 Voltage sensor
ADS1115 ADC 16bit reader
Photodiode Solar irradiance level sensor
DHT11 Ambient temperature sensor
The IoT system in this system is used as a monitoring output of parameter values generated from
sensors to identify data in real-time. Then, the collected data is displayed on the LCD output and stored on
the web server. After that, the parameter value data can be processed for further processing. Figure 4 shows a
system diagram, while Figure 5 shows the process of the system.
Figure 4. PV system parameter measurement configuration
Figure 5. The process of the PV parameter monitoring system
3.1. PV and supporting device
The PV block and the supporting device are PV systems applied for battery charging. The
instruments used in this block are 50 W monocrystalline PV, SCC with a capacity of 10 A PWM type, 12 V
7.2 Ah battery, and 30 W load.
5. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864
A laboratory scale IoT-based measuring of the solar photovoltaic parameters (Arsyad Cahya Subrata)
139
3.2. Sensing device
The sensor device serves to measure essential parameters in the PV system. The current sensor is a
sensor that works based on field effects. This sensor can be used to measure AC or DC. It has been equipped
with an operational amplifier circuit to increase the current measurement sensitivity and measure small
current changes. A voltage sensor is a sensor used to measure AC or DC voltage. The working principle of
the voltage sensor module is based on the principle of suppression of resistance and can reduce its original
input voltage up to 5 times.
The voltage sensor is based on a voltage divider circuit converted to a reference voltage (𝑉𝑟𝑒𝑓) of the
microcontroller. The value of this sensor's voltage divider resistor (𝑅1 and 𝑅2) depends on the magnitude of
the input voltage as a voltage. In this case, the PV voltage (𝑉𝑃𝑉), will be measured. The voltage divider
circuit equation is obtained as (3) [33].
𝑉𝑟𝑒𝑓 = 𝑉𝑃𝑉
𝑅2
𝑅1+𝑅2
(3)
On the side of the current sensor, the output current generated is identical to the oscillation generated by the
sensor. Therefore, a signal conditioning circuit consisting of a subtractor and an inverter is needed. The
subtractor circuit uses an Op-Amp with an output voltage of (4).
𝑉𝑜,𝑈1
= (
𝑅3
𝑅2+𝑅3
𝑉𝑅𝑉1) − (
𝑅4
𝑅1
𝑉𝑖) = (𝑉𝑅𝑉2
− 𝑉𝑖) (4)
While inverting uses Op-Amp 𝑈2 with an output voltage of (5).
𝑉𝑜,𝑈2
= − (
𝑅𝑉2
𝑅5
) 𝑉𝑜,𝑈1
(5)
The DHT11 sensor used in this paper is a sensor module that functions to sense temperature and
humidity in objects with an analog voltage output which can be further processed using a microcontroller.
The light sensor uses a light dependent resistor (LDR) sensor. This module allows for detecting ambient light
brightness and intensity using the LM393 comparator chip. The operating voltage of this LDR module is
3.3V–5V. This module generates both analog and digital signals.
3.3. Data processing device
In this paper, the microcontroller is the NodeMCU. The NodeMCU. It is integrated with the
ESP8266 module, which is a very effective platform for communication or control over the internet, either
used as a stand-alone or by using an additional microcontroller, in this case, Arduino as the controller. The
use of this module is to control devices via the internet to support the IoT system. Furthermore, the RTC
module, which is one type of module that functions as a real-time clock (RTC) or digital timer, is used. In
this paper, the RTC module is used to calculate time starting from seconds, minutes, hours, days, dates,
months, and years accurately and maintain or store time data.
3.4. Viewer device
The main viewer in this paper is via a web server. A web server is software that functions as a
recipient of requests sent through a browser and then responds to requests in the form of website pages. In
this paper, the webserver is ThingSpeak, an IoT platform and API to store sensor data monitored in real-time.
The next display device is a 16x2 LCD, which is placed close to the PV system. This is intended to make it
easier to monitor the system directly. An additional device in the form of a microSD card is used to store data
offline. This is meant to be a backup for your data in case something goes wrong with your internet
connection.
4. RESULTS AND DISCUSSION
The PV parameter monitoring system has been developed, as shown in Figure 6. The system starts
by initializing the sensor library and ThingSpeak as well as the variables used in the algorithm. The ACS172
sensor carries out the data collection of voltage and current from the PV module. Pseudocode for taking
voltage and current parameters using the following pseudocode.
6. ISSN: 2089-4864
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140
void temp_current(){
adc_value = analogRead(pinADC);
voltage = (adc_value / 1024.0) * 5.0;
current = ((voltage – offset_voltage) / s);
}
NodeMCU has a 10-bit ADC, so it can represent 210
= 1024. This program snippet is a voltage
conversion, so 5.0 is the value of the I/O pin voltage used. While s is a constant of sensor sensitivity.
Furthermore, the ambient temperature data is obtained with the following pseudocode.
DHT dht(DHTPIN, DHTTYPE);
dht.begin();
float celcius_1 = dht.readTemperature();
In this pseudocode, we apply the DHT11 library included with the sensor. This library facilitates the
development of code listings because it shortens the program. Furthermore, the light intensity data using
pseudocode is based on a similar principle to the pseudocode to access the ACS712 sensor.
void irradiance(){
int value = analogRead (pin_ldr);
float voltage_out = 5.0 * value / 1024;
}
Furthermore, WiFi connectivity is checked. If it is available, the microcontroller will access the SD
card. If there is an SD card, the algorithm will read the sensors and time reference from the RTC module. The
collected data is then stored in the SD card and displayed on the LCD. Further, the information is sent to the
cloud server via a WiFi gateway, which is accessed via ESP8266.
Figure 6 shows the process of taking parameter data in a PV system. The PV system consists of a
PV module controlled by the SCC as the primary source of power generation used for battery charging. The
ThingSpeak platform as a graphics viewer is accessed via a laptop. The sensors, microcontrollers, and other
parts are put in a box, which is then attached to the PV module holder.
Figure 6. PV system parameter data collection
The measurement results of PV system parameters displayed graphically with the ThingSpeak
platform are shown in Figures 7 and 8. The most commonly used parameters as variables in the PV
performance optimization algorithm are temperature and irradiance. Figures 7(a) and 7(b) show the varying
temperature and irradiance values from 12.30 to 13.10 (GMT+7). This is caused by environmental influences
such as being blocked by clouds, trees, or buildings.
7. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864
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141
(a) (b)
Figure 7. Measurement results of (a) temperature and (b) irradiance displayed graphically on ThingSpeak
Changes in temperature and irradiance variables will cause the PV output power value to change. As
shown in Figures 8(a) and 8(b), the PV output is in the form of fluctuating voltage and current. This is
because temperature and irradiance affect the PV output voltage and current. As a result, the PV output
power depicted in Figure 8(c) varies.
(a) (b)
(c)
Figure 8. Measurement results (a) voltage, (b) current, and (c) power due to variations in temperature and
irradiance
Overall, the PV system parameter monitoring must be running well. Sending data from the
microcontroller to ThingSpeak runs according to a predetermined time interval. Since this parameter
monitoring system works based on IoT techniques, an internet connection must send and display data to
ThingSpeak. In Figures 7 and 8, the internet connection is temporarily turned off. As a result, there was a
failure while sending data by the microcontroller to ThingSpeak for a moment.
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Furthermore, the test was carried out for 18 hours with a full internet connection. It aimed to
determine the correlation between essential parameters in the PV system and the surrounding environment.
The parameter values are stored on the microSD and recorded in real-time via the RTC module. Figures 9
and 10 show the effect of daily time on the irradiation and stress parameters, respectively. The irradiation
value shown in Figure 9 was recorded and started to increase after 04.00 to 06.00, then began to decrease
after 16.00 to 18.00. In daylight, irradiation was recorded to be relatively stable due to bright lighting. But
between 14:00 and 16:00, there was shading, which made the irradiation value temporarily drop.
Figure 9. Irradiation value measured from morning to evening
On the side of the voltage parameters shown in Figure 10, the characteristics are not much different
from the irradiation parameters when tested from morning to evening. The shading phenomenon that causes
the irradiation value to decrease also affects the measured voltage value. It can be seen that the voltage value
decreases similarly to irradiation. On the other hand, the voltage values measured during daylight show
uneven fluctuations. This is influenced by the ambient temperature value, which also varies. This clearly
shows that the parameters of irradiation and the temperature of the environment affect the PV output voltage.
Figure 10. Voltage values measured from morning to evening
5. CONCLUSION
This research carried out parameter measurements of IoT-based PV systems on a laboratory scale.
The IoT system utilizes the ThingSpeak platform, easily accessible for general purposes and real-time
analysis. The system developed includes NodeMCU ESP8266 as a microcontroller, ACS712 5A for
measuring current, INA219 for PV output voltage, a photodiode for measuring irradiance hitting PV panels,
9. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864
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and DHT11 for measuring ambient temperature. This system is equipped with an ADS1115 as an ADC 16-
bit reader. Other supporting components are a 50 Wp solar panel, a 12 V battery, a PWM SCC as a charging
controller, and an inverter. Overall, the developed system successfully measures the parameters of the PV
system in various weather conditions for 18 hours and sends them to the data viewer both online and offline
correctly. This research can be used as a learning model for lab-scale PV systems in the future. Another
application that will be developed is the management of energy loads from solar PV systems and grid power
to optimize consumption and save energy for consumers. This management system monitors the energy
generated by PV due to changing weather.
ACKNOWLEDGEMENTS
This research is funded by a grant from the LPPM Universitas Ahmad Dahlan under contract
number: PUPS-297/SP3/LPPM-UAD/VI/2021. This work is also supported by the Embedded System and
Power Electronics Research Group (ESPERG). Thanks to Hendril Satrian Purnama and Tri Wahono for
helping set up the system.
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BIOGRAPHIES OF AUTHORS
Arsyad Cahya Subrata received B.E. and M.E. in electrical engineering from
Universitas Ahmad Dahlan, Indonesia and Universitas Diponegoro, Indonesia in 2016 and
2020, respectively. Currently, he is a member of the Embedded Systems and Power Electronics
Research Group (ESPERG) research team since 2018, and has been a Lecturer with the
Electrical Engineering Department, Universitas Ahmad Dahlan (UAD), Yogyakarta, Indonesia
since 2021. His research interests include renewable energy, robotics, artificial intelligence,
control instrumentation, intelligent control, and internet of things. He can be contacted at
email: arsyad.subrata@te.uad.ac.id.
Tole Sutikno is a lecturer in Electrical Engineering Department at the Universitas
Ahmad Dahlan (UAD), Yogyakarta, Indonesia. He received his B.Eng., M.Eng. and Ph.D.
degrees in Electrical Engineering from Universitas Diponegoro, Universitas Gadjah Mada and
Universiti Teknologi Malaysia, in 1999, 2004 and 2016, respectively. He has been an
Associate Professor at UAD, Yogyakarta, Indonesia since 2008. He is currently the Editor-in-
Chief of TELKOMNIKA and the Head of the Embedded Systems and Power Electronics
Research Group (ESPERG). His research interests include the fields of digital design,
industrial applications, industrial electronics, industrial informatics, power electronics, motor
drives, renewable energy, FPGA applications, embedded systems, artificial intelligence,
intelligent control, information technology and digital library. He can be contacted at email:
tole@ee.uad.ac.id, or tole@te.uad.ac.id.
Sunardi received the B.E. and M.E. in electrical engineering from Universitas
Gadjah Mada and Institut Teknologi Bandung in 1999 and 2003, respectively. He also received
his Ph.D. in electrical engineering from Universiti Teknologi Malaysia in 2011. He is currently
as Associate Professor with the Electrical Engineering Department, Universitas Ahmad Dahlan
(UAD), Yogyakarta, Indonesia. His current research interests include signal processing, image
processing, and artificial intelligence. He can be contacted at email: sunardi@ee.uad.ac.id.
11. Int J Reconfigurable & Embedded Syst ISSN: 2089-4864
A laboratory scale IoT-based measuring of the solar photovoltaic parameters (Arsyad Cahya Subrata)
145
Anggit Pamungkas received his B.E. in electrical engineering from Universitas
Ahmad Dahlan, Indonesia, in 2018. Currently, he is a member of the Embedded Systems and
Power Electronics Research Group (ESPERG) research team since 2019. His current research
interests include power electronics, renewable energy development and robotics. He can be
contacted at email: Anggitpamungkas17@gmail.com.
Watra Arsadiando received his B.E. in electrical engineering from Universitas
Ahmad Dahlan, Indonesia, in 2017. Currently, he is a member of the Embedded Systems and
Power Electronics Research Group (ESPERG) research team since 2019. His current research
interests include power electronics, renewable energy development and robotics. He can be
contacted at email: watra24arsadiando@gmail.com.
Ahmad Raditya Cahya Baswara received the B.E. and M.E. in electrical
engineering from Universitas Gadjah Mada in 2014 and 2018, respectively. He is currently a
Lecturer with the Electrical Engineering Department, Universitas Ahmad Dahlan (UAD),
Yogyakarta, Indonesia. His current research interests include renewable energy, power
electronics, wireless power, energy conversion. He can be contacted at email:
ahmadradityac@ee.uad.ac.id.