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Energy Harvesting in Wireless Sensor Networks
Uppsala University, Disciplinary Domain of Science and Technology, Technology, Department of Engineering Sciences, Signals and Systems Group.
2019 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Over the past few years, the interest of remote wireless sensor networks has increased with the growth of Internet of Things technology. The wireless sensor network applications vary from tracking animal movement to controlling small electrical devices. Wireless sensors deployed in remote areas where the grid is unavailable are normally powered by batteries, inducing a limited lifespan for the sensor. This thesis work presents a solution to implement solar energy harvesting to a wireless sensor network. By gathering energy from the environment and using it in conjunction with an energy storage, the lifetime of a sensor node can be extended while at the same time reducing maintenance costs. To make sensor nodes in a network energy efficient, an adaptive controller of the nodes energy consumption can be used.

A network consisting of a client node and a server node was created. The client node was powered by a small solar cell in conjunction with a capacitor. A linear-quadratic tracking algorithm was implemented to adaptively change the transmission rate for a node based on its current and previous battery level and the energy harvesting model. The implementation was done using only integers. To evaluate the system for extended run-times, the battery level was simulated using MATLAB. The system was simulated for different weather conditions.

The simulation results show that the system is viable for both cloudy and sunny weather conditions. The integer linear-quadratic algorithm responds to change very abruptly in comparison to a floating point-version.

Place, publisher, year, edition, pages
2019. , p. 56
Series
UPTEC E, ISSN 1654-7616 ; 19 014
Keywords [en]
energy harvesting, contiki
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:uu:diva-388006OAI: oai:DiVA.org:uu-388006DiVA, id: diva2:1331362
External cooperation
Syntronic
Educational program
Master Programme in Electrical Engineering
Presentation
2019-06-19, Å2003, Ångströmlaboratoriet Lägerhyddsvägen 1 Hus 2, Plan 0, Uppsala, 16:00 (Swedish)
Supervisors
Examiners
Available from: 2019-06-28 Created: 2019-06-26 Last updated: 2019-06-28Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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Output format
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