Monitoring and Determination of Wind Energy Potential by Web Based Wireless Network

11cbbfbb49d629da1c5cb042adc0211a?s=47 Onur K.
December 14, 2012

Monitoring and Determination of Wind Energy Potential by Web Based Wireless Network

11th International Conference on Machine Learning and Applications ICMLA 2012

Monitoring and Determination of Wind Energy Potential by Web Based Wireless Network

http://www.icmla-conference.org/icmla12/

11cbbfbb49d629da1c5cb042adc0211a?s=128

Onur K.

December 14, 2012
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Transcript

  1. 1.

    Onur KESKİN İsmet ATEŞ Z. Haktan Karadeniz Alpaslan Turgut Zeki

    Kıral Mechatronics Engineering Mechanical Engineering Dokuz Eylül University
  2. 2.

    • Introduction • System Overview – « Sense – Plan

    – Act » layers • The Setup – Data Acquisitioning – Web Interface • Conclusion – rPiaaS – Future Works 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 2
  3. 3.

    • Increase in Renewable Energy – Application – Equipment •

    Potential determination is the key – For utilization of renewable energy site – For gathering maximum efficiency in the site 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 3
  4. 4.

    Error in measurement of wind speed will cause significant amount

    of error on wind energy potential 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 4 ∝ 3
  5. 5.

    • Potential determination measurement must be – Long term –

    Distributed • Atmospheric parameters need to be measure – Wind speed and direction, – Temperature, – Humidity, – Solar radiation, – Barometric pressure, etc. 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 5
  6. 6.

    • Sensor data logging types; – Data logger on field

    – Data logger via air 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications - Boca Raton, Florida, USA 6 Logging On-Board Logging Wirelessly Operating Cost High Low Installation Cost Low High Data Recovery Poor Strong Monitoring None Real time
  7. 7.

    Sense Various sensors Plan Communication Microcontroller Act Web Server Dynamic

    web site 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications - Boca Raton, Florida, USA 7
  8. 8.

    – Choosing proper sensor type and range is mandatory –

    Energy consumption and reliability is important for survivability 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 8
  9. 9.

    • For wind speed and direction – Thies combined wind

    sensor • Works under 15V • PWM with respect to wind speed • 8-bit gray code encoder for wind direction – HMC6352 digital compass • Additional sensor for wind direction • Selectable update rate from 1 Hz to 20 Hz • 0.5° heading resolution • 1° repeatability • Consumes 1 mA at 3V 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 9
  10. 10.

    • For temperature and humidity – SHT11 combined digital sensor

    • 12 bit pre-calibrated sensor • Relative humidity in a range from 0% to 100% • Maximum RH measuring time interval 8 ms • Temperature in a range from -40°C to +125°C • Consumes 266 mA at 3V 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 10
  11. 11.

    • For sunlight intensity – Photovoltaic (PV) module is used

    – Maximum 10 W power output – Module is also used for powering the measuring system – Switching between NiHM battery pack and PV cell is performed by custom electronic board 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 11
  12. 12.

    • Communication between data logger and sensor can be performed

    wired or wirelessly • Planning is performed via microcontroller through wireless communication • A suitable wireless network protocol is chosen for recording sensor data 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 12
  13. 13.

    • Wireless communication is – Easy to implement – Expandable

    • But; – Information and data security must be ensured – Energy consumption is higher than wired 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 13
  14. 14.

    Wireless Protocol GSM/GPRS IEEE 802.11 ZigBee Etc. 11 April 2013

    ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 14
  15. 15.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 15 GSM/GPRS IEEE 802.11 ZigBee Range High (3) Low (1) Medium (2) Security Low (1) Medium (2) High (3) Speed Medium (2) High (3) Low (1) Lifetime Low (1) Medium (2) High (3) Node Size High (3) Low (1) Medium (2) Setup Costs Expensive (1) Average (2) Cheap (3) Additional Costs Must (1) Optional (2) No Need (3) TOTAL 12 13 17
  16. 16.

    • Arduino Uno R3 is used – 8-bit ATmega328 processor

    – 16 MHz clock frequency – 32 KB flash memory – Various serial communication protocol are supported • I2C is used with HMC6352 • 1-wire is used for SHT11 • TTL serial is used with ZigBee module 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 16
  17. 17.

    • Main advantage of using Arduino is its shields –

    Shield is used for extending main board – Commonly used shields are already in market such as wireless shield – Custom shield production and use is easy with a certain of PCB design and software knowledge 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 17
  18. 18.

    • Our shield is for; – 1-wire connection to SHT11

    – I2C connection to HMC6352 – Analog input with adjustable signal amplifier – Level shifter for 15V (wind sensor) to 5V (Arduino) – SPI connection for future works 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 18
  19. 19.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 19 1 2 1 4N25M – Optocoupler 2 LM358N – Op-Amp
  20. 20.

    • Power management between PV module and battery • Voltage

    regulation for whole system • Status LEDs for power input and its source • Shield is designed for; – Signal loss in voltage supply and sensor cables – Noise filtering/rejection 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 20
  21. 21.

    Arduino Weather Shield Temperature & Relative Humidity Wind Speed &

    Direction Power Wireless Shield ZigBee 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 21 Operating System UART to USB ZigBee TCP/IP Apache MySQL PHP
  22. 22.

    • Temperature in ⁰C degree • Relative humidity in %

    (percentage) • Compass heading in ⁰ (degree) • Current power source – 1 for Battery – 0 for PV module • Wind speed in Hz 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 22
  23. 23.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 23 Login page http://people.deu.edu.tr/onur.keskin/wis.html
  24. 24.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 24 Dashboard
  25. 25.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 25 Sensor Logs
  26. 26.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 26 Custom Reports
  27. 27.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 27 Profile Details
  28. 28.

    • In this study, we successfully developed a web based

    solution for wind energy potential monitoring and potential determination with using wireless network. 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 28
  29. 29.

    • The Raspberry Pi is a credit-card-sized single-board computer. –

    Processor; 700 MHz – RAM; 256 (model A) or 512 (model B) MB – Power; 2.5 W (model A) or 3.5 W (model B) – Storage; full size SD card – Size; 85.60 x 53.98 mm – Weight; 45 g 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 29
  30. 30.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 30
  31. 31.

    11 April 2013 ICMLA 2012 - 11th International Conference on

    Machine Learning and Applications Boca Raton, Florida, USA 31
  32. 32.

    • Disrubuting our sensors on our campus area for upcoming

    wind farm • Our aim is to be useful for other renewable energy applications; – Solar fields by using solar trackers – Pyrometers and barometer for weather forecast – Charging support with using PV module 11 April 2013 ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA 32
  33. 33.

    Onur Keskin – onur.keskin@deu.edu.tr İsmet Ateş – iismetates@gmail.com Z. Haktan

    Karadeniz – haktan.karadeniz@deu.edu.tr Alpasan Turgut – alpaslan.turgut@deu.edu.tr Zeki Kıral – zeki.kiral@deu.edu.tr ICMLA 2012 - 11th International Conference on Machine Learning and Applications Boca Raton, Florida, USA Dokuz Eylül University Izmir, Turkey 38.369702, 27.208022
  34. 34.

    • Patrick Moriarty, Damon Honnery, “What is the global potential

    for renewable energy?, Renewable and Sustainable Energy Reviews”, Volume 16, Issue 1, January 2012, Pages 244-252, ISSN 1364-0321, 10.1016/j.rser.2011.07.151. • Marion Große, Wind Measurement for Accurate Energy Predictions – An Overview, http://wwindea.org/technology/ch02/en/2_2_1.html • Bent Sørensen, “Renewable Energy Its physics, engineering, use, environmental impacts, economy and planning aspects Third Edition”, Elsevier, 2004 • Thies Clima , “Wind Printer Lot. No. 4.3276.20.000 Datasheet”, 1986 • Honeywell Int. Inc., “Digital Compass Solution - HMC6352”, 2006 • Sensirion AG, “Datasheet SHT1x (SHT10, SHT11, SHT15) Humidity and Temperature Sensor IC”, 2011 • Shanghai Sendtrue Technologies Co., Ltd , “SM5100B-D GSM/GPRS Module”, 2008 • Roving Networks, “RN-131G & RN-131C - WiFly GSX 802.11 b/g Wireless LAN Module”, 2010 • Digi Int. Inc., “XBee®/XBee-PRO® ZB RF Modules”, 2012 • Johnny Cache, Joshua Wright, Vincent Liu, “Hacking Exposed Wireless: Wireless Security Secrets & Solutions”, McGraw-Hill, 2010 • Arduino UNO Rev. 3, “http://arduino.cc/en/Main/ArduinoBoardUno” • Steel, R. G. D. and Torrie, J. H., “Principles and Procedures of Statistics”, New York: McGraw-Hill, 1960, pp. 187, 287.
  35. 35.

    Slide # Picture Designer 1 Energy_sunset Adrián Vidal 2 GoodnightCopenhagen

    Casey Manning 3 Catavento João Vitor Munduruca 4 Newton Chris Bogie 5 Tetris Michaël Van de Vyver 6 Cloud_Storage Satchell Drakes 8 Radar Douglas Barnabé dos Santos 9 Franklin Chris Bogie 10 Autumn Tom Watson 11 vaieel_solar Joe Dawson Jr 12 arrow Nima Karimi 12 simple_connect4 kirk visola 13 Doppler_Effect Christopher T. Howlett 14 radiotower Aaron Harlow 15 Lines_and_Lines Miguel Santamaría 16 Circuits gary blaney 17 CMYK_Basics Bjørn Eivind Rostad 18 circuit O Delgado G 20 Omnisphere Junior Silva 21 Network Dan Grigore 22 Atomic Ben Barry 28 airplane_classico rulfzid 29 BacktoSkool Alfredo Lopez 30 The Owl Douglas 32 4 colour rainbow Eurux