IOT Based Augmented Perturb-and-Observe Soft Switching Boost Converters for Photovoltaic Power Systems in Smart Cities

Banu, J. Barsana; Moses, M. Balasingh

doi:10.1007/s11277-018-5280-x

Cited by 11 publications

(4 citation statements)

References 22 publications

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“…Researchers came out with different theoretical models and designs, as well as some real-world implementations. 11,25,26 The researchers have approached forecasting the wind speed and its corresponding generated power from different perspectives to utilize it in smart city models. The approaches can be classified into two main categories.…”

Section: Related Workmentioning

confidence: 99%

“…[7][8][9] The most addressed renewable resources are from solar, electromagnetic, and wind resources. 6,10,11 The solar energy is harvested using solar panels, electromagnetic energy through radiofrequency energy harvesting systems, and the wind energy via wind turbines. 1,6,10 Wind energy has a growing installed-capacity rate of more than 30% yearly and will reach up to 12% of all electricityproducing resources around the globe by 2020.…”

Section: Introductionmentioning

confidence: 99%

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Aiming for smart wind energy: A comparison analysis between wind speed forecasting techniques

Alhaddad¹,

Ever

Fahrioğlu

et al. 2019

Trans Emerging Tel Tech

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Smart cities are one of the promising application areas where the energy management (supply/dispatch) issues have the potential to positively affect the society. In the common era of information and technology, the consumers expect the required amount of energy to be present at anytime. This energy is obtained through renewable and nonrenewable resources. Smart wind energy is the idea of efficient energy generation utilizing the wind while satisfying green expectations. However, the random characteristics caused by various external factors have significant effects on wind speeds, thus introducing difficulties in power systems operations and energy generation. Forecasting techniques can be effectively used to predict future wind speeds and power generation to optimize the energy output. The objective of this study is to provide a framework for a local smart-city wind energy harvesting model. Our study evaluates wind speed forecasting models based on synced weather characteristics (air temperature, humidity, and pressure), against models based on wind speed data itself. The produced models are implemented via k-nearest neighbors and linear regression. Two different data sets are addressed for performance comparison purposes. The first one is 5 years of 10-minute time span measurements at Middle East Technical University campus. The second data set is 3 years of the same time span at a site in California, USA. The accuracy of predictions is found to be higher for the data sets with lower variance (METU data set). However, the models fit the higher variance (NREL data set) data better than the lower one.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Aiming for smart wind energy: A comparison analysis between wind speed forecasting techniques

Alhaddad¹,

Ever

Fahrioğlu

et al. 2019

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…The world added more capacity from solar PV than from any other type of power generating technology, and more solar PV was installed than the net capacity additions of fossil fuels and nuclear power combined, about 98 GW of solar PV capacity was installed both on and off the grid, accumulating 402 GW worldwide at the end of 2017 [3]. Sunlight based solar generators have been utilized as a part of the small-scale, low voltage levels of standalone systems and also in greatest-power establishments associated into network manner and working at any level of voltage in smart cities [7]. Some examples of building integrated PV systems are presented in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

“…Some examples of building integrated PV systems are presented in Figure 1. However, regarding energy efficiency, the little transformation productivity is one of the issues the PV faces [7]. This transformation is not more than 20% for crystalline-based solar cell, reaching 30% in new exploratory cells.…”

Section: Introductionmentioning

confidence: 99%

Analysis and characterization of PV module defects by thermographic inspection

Gallardo-Saavedra

Hernández-Callejo

Duque-Pérez

2019

Rev.Fac.Ing.Univ.Antioquia

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Being able to detect, to identify and to quantify the severity of defects that appear within photovoltaic modules is essential to constitute a reliable, efficient and safety system, avoiding energy losses, mismatches and safety issues. The main objective of this paper is to perform an in-depth, onsite study of 17,142 monocrystalline modules to detect every single existing defect, classifying them in different groups, studying the variance of the same kind of defect in different modules and the patterns of each group of thermal defects. Results can be useful in a subsequent development of a software to automatically detect if a module has an anomaly and its classification. Focusing on the results obtained, all faults detected have been classified in five different thermographic defects modes: hotspot in a cell, bypass circuit overheated, hotspot in the junction box, hotspot in the connection of the busbar to the junction box and whole module overheated. An analysis of patterns of the different defects is included, studiyng location within the module, size and temperature statistical results, as average temperature, standard deviation, maximum temperature, median and first and third quartile.

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Design of Novel Dual Input DC–DC Converter for Energy Harvesting System in IoT Sensor Nodes

Lavanya

Jegatheesan

Vijayakumar

2020

Wireless Pers Commun

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IOT Based Augmented Perturb-and-Observe Soft Switching Boost Converters for Photovoltaic Power Systems in Smart Cities

Cited by 11 publications

References 22 publications

Aiming for smart wind energy: A comparison analysis between wind speed forecasting techniques

Aiming for smart wind energy: A comparison analysis between wind speed forecasting techniques

Analysis and characterization of PV module defects by thermographic inspection

Design of Novel Dual Input DC–DC Converter for Energy Harvesting System in IoT Sensor Nodes

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