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Energy Storage Technologies in Photovoltaics Systems

Gokturk, Ayse Ozge (2018)

 
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Gokturk, Ayse Ozge
2018

Electrical Engineering
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Hyväksymispäivämäärä
2018-11-07
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201810242455
Tiivistelmä
In solar power systems, photovoltaic cells are used for conversion from solar irradiance to direct current. They can be modeled as an ideal diode which is affected from some factors like parasitic resistance, temperature, and irradiance. This thesis will give an explanation about these main concepts and examine relationship between photovoltaic cells and these factors.
Efficiency of solar power systems can be improved by installation of electrical energy storage technologies into systems. For achieving this, mechanical, electrical or electrochemical systems can be used. Pumped hydroelectric storage systems, compressed air energy storage systems and flywheel energy storage systems are implemented systems to store electrical energy by using mechanical systems. In addition to these systems, battery energy storage systems can be implemented to solar power systems that are mainly lead-acid, lithium-ion, sodium-sulfur, and nickel-cadmium batteries. These battery energy storage systems and flow batteries store energy by using electrochemical reactions. Lastly, capacitors, supercapacitors and superconducting magnetic energy storage can be classified as electrical energy storage systems. In this thesis, these storage technologies will be analyzed and compared to be able to get an optimized storage solution in terms of different requirements.
Photovoltaic power fluctuations that are caused from cloud shading of sun or other environmental impacts is one of the main drawback of solar power systems. For smoothing these photovoltaic fluctuations several methods can be thought. In this thesis, moving average algorithm will be implemented into fluctuated signal and thesis will finalize by comparing difference between fluctuated and smoothed signals.
Kokoelmat
  • Opinnäytteet - ylempi korkeakoulututkinto [40800]
Kalevantie 5
PL 617
33014 Tampereen yliopisto
oa[@]tuni.fi | Tietosuoja | Saavutettavuusseloste
 

 

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Kalevantie 5
PL 617
33014 Tampereen yliopisto
oa[@]tuni.fi | Tietosuoja | Saavutettavuusseloste