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THE ROLE OF HYBRID POWER SYSTEMS TO CREATE SELF-SUSTAINING SMART HOMES FOR THE ELDERLY AND DISABLED

Year 2015, Volume: 1 Issue: 1, 1 - 11, 08.01.2016

Abstract

With the increase in the number of the elderly and due to the disabled’ demand for independent living, there is significant interest in smart home technologies which can assist the elderly and disabled to continue living at home with independence and safety. The feasibility and effectiveness of smart home technologies for promoting independence, health, and quality of life have been proved in the literature.  In recent years, there is increasing interest from care providers to provide caregiving services for the elderly and disabled in their home environments instead of caring them in assisted-living centres due to a number of reasons including costs. Since caregiving services are provided at specific times, a few times a day or week, smart home technologies can help care providers deploy services which trigger alerts when urgent situations occur. However, due to the cost of caregiving services, maintenance costs of smart home systems, and increasing electric energy consumption, generating electricity from renewable energy sources can play an important role for this objective. In this study, we present an environmentally friendly hybrid power system which automatically chooses its energy source(s) without any user input and give the results of simulation study performed using Homer software. The simulation study proves that the proposed hybrid power system can easily generate electricity required by a smart home.

References

  • Lê, Q., Nguyen H. B. and Barnett, T. “Smart Homes for Older People: Positive Aging in a Digital World,” Future Internet, vol. 4, no. 2, pp. 607-617, 2012.
  • Gaddam, A., Mukhopadhyay, S. C. and Gupta, G. S. “Towards the Development of a Cognitive Sensors Network Based Home for Elder Care,” 6th International Conference on Wireless and Mobile Communications, 2010, pp. 484-491.
  • Moutacalli, M. T., Marmen, V., Bouzouane, A. and Bouchard, B. “Activity Pattern Mining using Temporal Relationships in a Smart Home,” IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), 2013, pp. 83-87.
  • Manley, E. D. and Deogun, J. S. “Location Learning for Smart Homes,” 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007.
  • Wang, J., Zhang, Z., Li, B., Lee, S. and Sherratt, R. S. “An Enhanced Fall Detection System for Elderly Person Monitoring,” IEEE Transactions on Consumer Electronics, vol. 60, no. 1, pp. 23-29, 2014.
  • Jalal, A., Uddin, M. Z. and Kim, T.-S. “Depth Video-based Human Activity Recognition System Using Translation and Scaling Invariant Features for Life Logging at Smart Home,” IEEE Transactions on Consumer Electronics, vol. 58, no. 3, pp. 863-871, 2012.
  • Jovanov, E., Lords, A., Raskovic, D., Cox, P., Adhami, R. and Andrasik, F. “Stress monitoring using a distributed wireless intelligent sensor system,” IEEE Engineering in Medicine and Biology Magazine, vol. 22, no. 3, pp. 49-55, 2003.
  • Jalal, A. and Kamal, S. “Real-Time Life Logging via a Depth Silhouette-based Human Activity Recognition System for Smart Home Services,” Proc. 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2014, pp. 74-80.
  • Son, Y. -S., Jo, J., Park, J. -H. and Pulkkinen, T. “Diabetic Patient Care using Home User Activity Recognition,” ICTC 2013, 2013, pp. 191-196.
  • Suryadevara, N. K. and Mukhopadhyay, S. C. “Wireless sensors network based safe home to care elderly people: A realistic approach,” 2011 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 2011, pp. 1-5.
  • The ZigBee Alliance. [ONLINE]. Available at: http://www.zigbee.org [Accessed 24 October 2015].
  • CPVM - 100W Solar Panel -100W 12V Crystalline PV Module. [ONLINE]. Available at: http://www.cdtsolar.com/100_watt [Accessed 22 October 2015].
  • BWC XL.1 Wind turbine specifications. [ONLINE]. Available at: https://www.altestore.com/mmsolar/others/XL1Brochure.pdf [Accessed 22 October 2015].
  • T-105 with Bayonet Cap. [ONLINE]. Available at: http://www.trojanbattery.com/pdf/datasheets/T105_Trojan_Data_Sheets.pdf [Accessed 22 October 2015].
  • YEGM, Yenilenebilir Enerji Genel Müdürlüğü, GEPA atlas. [ONLINE]. Available at: http://www.eie.gov.tr/yenilenebilir/gunes.aspx [Accessed 24 October 2015].
  • Gokcol, C., Sunan, E. and Dursun, B. “Rüzgar Enerjisi ile Gebze’de Bir Evin Elektrik İhtiyacının Karşılanması,” Proc. ELECO 2008 Elektrik-Elektronik ve Bilgisayar Mühendisliği Sempozyumu, 2008.
  • HOMER Energy. [ONLINE]. Available at: http://www.homerenergy.com/ [Accessed 22 October 2015].
  • Lambert, T., Gilman, P., and Lilienthal, P. “Micropower system modeling with HOMER,” in Integration of Alternative Sources of Energy, Farret, F. A. and Simoes, M. G. (Eds.), John Wiley & Sons Inc.: USA, 2006, pp. 379-418.
  • Gokcol, C. And Dursun, B. “A comprehensive economical and environmental analysis of the renewable power generating systems for Kırklareli University, Turkey,” Energy and Buildings, vol. 64, pp. 249-257, 2013.
  • Dursun, B. and Gokcol, C. “Economic analysis of a wind-battery hybrid system: an application for a house in Gebze, Turkey, with moderate, wind energy potential,” Turk J Elec Eng& Comp Sci, vol. 20, no. 3, pp. 319-333, 2012.

THE ROLE OF HYBRID POWER SYSTEMS TO CREATE SELF-SUSTAINING SMART HOMES FOR THE ELDERLY AND DISABLED

Year 2015, Volume: 1 Issue: 1, 1 - 11, 08.01.2016

Abstract

With the increase in the number of the elderly and due to the disabled’ demand for independent living, there is significant interest in smart home technologies which can assist the elderly and disabled to continue living at home with independence and safety. The feasibility and effectiveness of smart home technologies for promoting independence, health, and quality of life have been proved in the literature.  In recent years, there is increasing interest from care providers to provide caregiving services for the elderly and disabled in their home environments instead of caring them in assisted-living centres due to a number of reasons including costs. Since caregiving services are provided at specific times, a few times a day or week, smart home technologies can help care providers deploy services which trigger alerts when urgent situations occur. However, due to the cost of caregiving services, maintenance costs of smart home systems, and increasing electric energy consumption, generating electricity from renewable energy sources can play an important role for this objective. In this study, we present an environmentally friendly hybrid power system which automatically chooses its energy source(s) without any user input and give the results of simulation study performed using Homer software. The simulation study proves that the proposed hybrid power system can easily generate electricity required by a smart home.

 

References

  • Lê, Q., Nguyen H. B. and Barnett, T. “Smart Homes for Older People: Positive Aging in a Digital World,” Future Internet, vol. 4, no. 2, pp. 607-617, 2012.
  • Gaddam, A., Mukhopadhyay, S. C. and Gupta, G. S. “Towards the Development of a Cognitive Sensors Network Based Home for Elder Care,” 6th International Conference on Wireless and Mobile Communications, 2010, pp. 484-491.
  • Moutacalli, M. T., Marmen, V., Bouzouane, A. and Bouchard, B. “Activity Pattern Mining using Temporal Relationships in a Smart Home,” IEEE Symposium on Computational Intelligence in Healthcare and e-health (CICARE), 2013, pp. 83-87.
  • Manley, E. D. and Deogun, J. S. “Location Learning for Smart Homes,” 21st International Conference on Advanced Information Networking and Applications Workshops (AINAW'07), 2007.
  • Wang, J., Zhang, Z., Li, B., Lee, S. and Sherratt, R. S. “An Enhanced Fall Detection System for Elderly Person Monitoring,” IEEE Transactions on Consumer Electronics, vol. 60, no. 1, pp. 23-29, 2014.
  • Jalal, A., Uddin, M. Z. and Kim, T.-S. “Depth Video-based Human Activity Recognition System Using Translation and Scaling Invariant Features for Life Logging at Smart Home,” IEEE Transactions on Consumer Electronics, vol. 58, no. 3, pp. 863-871, 2012.
  • Jovanov, E., Lords, A., Raskovic, D., Cox, P., Adhami, R. and Andrasik, F. “Stress monitoring using a distributed wireless intelligent sensor system,” IEEE Engineering in Medicine and Biology Magazine, vol. 22, no. 3, pp. 49-55, 2003.
  • Jalal, A. and Kamal, S. “Real-Time Life Logging via a Depth Silhouette-based Human Activity Recognition System for Smart Home Services,” Proc. 11th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), 2014, pp. 74-80.
  • Son, Y. -S., Jo, J., Park, J. -H. and Pulkkinen, T. “Diabetic Patient Care using Home User Activity Recognition,” ICTC 2013, 2013, pp. 191-196.
  • Suryadevara, N. K. and Mukhopadhyay, S. C. “Wireless sensors network based safe home to care elderly people: A realistic approach,” 2011 IEEE Recent Advances in Intelligent Computational Systems (RAICS), 2011, pp. 1-5.
  • The ZigBee Alliance. [ONLINE]. Available at: http://www.zigbee.org [Accessed 24 October 2015].
  • CPVM - 100W Solar Panel -100W 12V Crystalline PV Module. [ONLINE]. Available at: http://www.cdtsolar.com/100_watt [Accessed 22 October 2015].
  • BWC XL.1 Wind turbine specifications. [ONLINE]. Available at: https://www.altestore.com/mmsolar/others/XL1Brochure.pdf [Accessed 22 October 2015].
  • T-105 with Bayonet Cap. [ONLINE]. Available at: http://www.trojanbattery.com/pdf/datasheets/T105_Trojan_Data_Sheets.pdf [Accessed 22 October 2015].
  • YEGM, Yenilenebilir Enerji Genel Müdürlüğü, GEPA atlas. [ONLINE]. Available at: http://www.eie.gov.tr/yenilenebilir/gunes.aspx [Accessed 24 October 2015].
  • Gokcol, C., Sunan, E. and Dursun, B. “Rüzgar Enerjisi ile Gebze’de Bir Evin Elektrik İhtiyacının Karşılanması,” Proc. ELECO 2008 Elektrik-Elektronik ve Bilgisayar Mühendisliği Sempozyumu, 2008.
  • HOMER Energy. [ONLINE]. Available at: http://www.homerenergy.com/ [Accessed 22 October 2015].
  • Lambert, T., Gilman, P., and Lilienthal, P. “Micropower system modeling with HOMER,” in Integration of Alternative Sources of Energy, Farret, F. A. and Simoes, M. G. (Eds.), John Wiley & Sons Inc.: USA, 2006, pp. 379-418.
  • Gokcol, C. And Dursun, B. “A comprehensive economical and environmental analysis of the renewable power generating systems for Kırklareli University, Turkey,” Energy and Buildings, vol. 64, pp. 249-257, 2013.
  • Dursun, B. and Gokcol, C. “Economic analysis of a wind-battery hybrid system: an application for a house in Gebze, Turkey, with moderate, wind energy potential,” Turk J Elec Eng& Comp Sci, vol. 20, no. 3, pp. 319-333, 2012.
There are 20 citations in total.

Details

Primary Language English
Journal Section Issue
Authors

Bahtiyar Dursun

Gürkan Tuna

Ayşe Tuna

Publication Date January 8, 2016
Published in Issue Year 2015 Volume: 1 Issue: 1

Cite

APA Dursun, B., Tuna, G., & Tuna, A. (2016). THE ROLE OF HYBRID POWER SYSTEMS TO CREATE SELF-SUSTAINING SMART HOMES FOR THE ELDERLY AND DISABLED. Kirklareli University Journal of Engineering and Science, 1(1), 1-11.