An Optimized AC/DC Buck-Boost Converter for Wind Energy Harvesting Application

Haidar, Mohammad; Chiblé, Hussein; Zitti, E. Di; Caviglia, Daniele D.

doi:10.1109/eeeic.2019.8783648

Cited by 7 publications

(3 citation statements)

References 11 publications

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“…The second is to monitor the input power and run a maximum power point tracking (MPPT) algorithm for optimization. The third is to communicate the power state with an external device via serial communication [15,16].…”

Section: Methodsmentioning

confidence: 99%

A Low Power AC/DC Interface for Wind-Powered Sensor Nodes

et al. 2021

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Sensor nodes have been assigned a lot of tasks in a connected environment that is growing rapidly. The power supply remains a challenge that is not answered convincingly. Energy harvesting is an emerging solution that is being studied to integrate in low power applications such as internet of things (IoT) and wireless sensor networks (WSN). In this work an interface circuit for a novel fluttering wind energy harvester is presented. The system consists of a switching converter controlled by a low power microcontroller. Optimization techniques on the hardware and software level have been implemented, and a prototype is developed for testing. Experiments have been done with generated input signals resulting in up to 67% efficiency for a constant voltage input. Other experiments were conducted in a wind tunnel that showed a transient output that is compatible with the target applications.

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Section: Methodsmentioning

confidence: 99%

A Low Power AC/DC Interface for Wind-Powered Sensor Nodes

et al. 2021

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“…Therefore, it would not be suitable for directly powering a DC sensor node. To this purpose, an optimized AC/DC buck-boost converter for aeolian energy harvesting was investigated [22]. Another shortcoming that is implicitly entailed by aeolian harvesting is that performances of such a technique is strongly depended on wind forecast, therefore a system that automatically copes with this issue may be useful [23] or, alternatively, setting up a method to predict power provided by wind could be a remedy as well [24].…”

Section: Energy Harvesting Techniques For Wireless Sensor Networkmentioning

confidence: 99%

A Review of Energy Harvesting Techniques for Low Power Wide Area Networks (LPWANs)

Peruzzi

Pozzebon

2020

Energies

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The emergence of Internet of Things (IoT) architectures and applications has been the driver for a rapid growth in wireless technologies for the Machine-to-Machine domain. In this context, a crucial role is being played by the so-called Low Power Wide Area Networks (LPWANs), a bunch of transmission technologies developed to satisfy three main system requirements: low cost, wide transmission range, and low power consumption. This last requirement is especially crucial as IoT infrastructures should operate for long periods on limited quantities of energy: to cope with this limitation, energy harvesting is being applied every day more frequently, and several different techniques are being tested for LPWAN systems. The aim of this survey paper is to provide a detailed overview of the the existing LPWAN systems relying on energy harvesting for their powering. In this context, the different LPWAN technologies and protocols will be discussed and, for each technology, the applied energy harvesting techniques will be described as well as the architecture of the power management units when present.

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“…This phenomenon can be described wherein the daytime, the air above the ground warms faster than the air above the water. The inland air expansion will be warm and will continue to rise, and more relaxed and denser air will rush in to replace the wind [4], [5]. As the emphasis on global electricity has led to increased greenhouse gas emissions, significant investments have been turned to alternative ways to use wind as a renewable source of energy for electricity generation.…”

Section: Introductionmentioning

confidence: 99%

Design of Savonius model wind turbine for power catchment

Fang

Rahim

2022

IJECE

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In this study, the fossil fuel usage by-product is carbon dioxide, which is known as the primary cause in global warming. Alternatively, wind energy is a clean alternative energy source compared the fuel consumption can cause smoke pollution. The goal of the work is to develop a pollution controller device model Savonius wind turbine to represent the characterized actual speed wind turbine concepts into convert kinetic energy into electric energy from campus and monitoring all output data display on the cloud. The wind speed operation is enabled through the use of ESP8266 as internet of things (IoT) platform and the alternating current (AC) direct current (DC) harvesting circuit into improve stability of the wind energy performance. Secondly, a magnet coil synchronous generator is used, which is a grid coupled through a diode rectifier and voltage source converter. The parameters that have been measured using wireless fidelity (Wi-Fi) module ESP8266 are considering wind speed, current, voltage and power. The wind speed with 7.8 MPH can produce a maximum output voltage and output current of 1.104 V and 4.321 μA, respectively. Blynk applications functional as role present performance monitoring kit wind turbine analysis with more precise and efficient in anywhere and anytime.

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An Optimized AC/DC Buck-Boost Converter for Wind Energy Harvesting Application

Cited by 7 publications

References 11 publications

A Low Power AC/DC Interface for Wind-Powered Sensor Nodes

A Low Power AC/DC Interface for Wind-Powered Sensor Nodes

A Review of Energy Harvesting Techniques for Low Power Wide Area Networks (LPWANs)

Design of Savonius model wind turbine for power catchment

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