DOI QR코드

DOI QR Code

Performance Improvement of Air Conditioner Network System using Wireless Sensors Through System Performance Index and Dynamic Power Distribution Control

시스템 성능 지수 및 동적 전력분산 제어를 통한 무선센서를 이용한 에어컨 네트워크 시스템의 성능 개선

  • Choi, Ho-seek (School of Electrical Engineering, Kyungpook National Unversity) ;
  • Kwon, Woo-hyen (School of Electrical Engineering, Kyungpook National Unversity) ;
  • Yoon, Byung-keun (School of Electrical Engineering, Kyungpook National Unversity)
  • 최호식 (경북대학교학교 전자공학과) ;
  • 권우현 (경북대학교학교 전자공학과) ;
  • 윤병근 (경북대학교학교 전자공학과)
  • Received : 2018.11.28
  • Accepted : 2019.01.29
  • Published : 2019.01.31

Abstract

Wireless sensors have been developed in numerous ways for enhancing the convenience of installation, management and maintenance of sensors. Energy harvesting wireless sensors, which can collect energy from the external environment for permanent usage without the need of recharging and exchanging batteries, have been developed and employed used in Internet of Things and at various industrial sites. Energy harvesting wireless sensors are significantly affected by the sensor lifespan to sudden variation in the external environment. Furthermore, reduction in the sensor operating timespan can greatly affect the characteristics of the devices connected through a network. In this paper, a system performance index is proposed that can comprehensively evaluate the lifespan of a solar cell wireless sensor, determine the characteristics of devices connected to the associated network, and recommend dynamic power distribution control for improving the system performance index. Improvement in the system performance index was verified by applying the proposed dynamic power distribution control to an air conditioner network system using a solar cell wireless sensor. Obtained results corroborate that the dynamic power distribution control can extend the lifespan of the incorporated wireless sensor and reduce the air conditioner's power consumption.

Keywords

HSSHBT_2019_v28n1_64_f0001.png 이미지

Fig. 1. Air conditioner network system using wireless sensor.

HSSHBT_2019_v28n1_64_f0002.png 이미지

Fig. 2. Block diagram of dynamic power distribution control.

HSSHBT_2019_v28n1_64_f0003.png 이미지

Fig. 3. System performance index at initial battery level 40%.

HSSHBT_2019_v28n1_64_f0004.png 이미지

Fig. 4. System performance index at initial battery level 80%.

HSSHBT_2019_v28n1_64_f0005.png 이미지

Fig. 5. Available operating life index at initial battery level 40%.

HSSHBT_2019_v28n1_64_f0006.png 이미지

Fig. 6. Available operating life index at initial battery level 80%.

HSSHBT_2019_v28n1_64_f0007.png 이미지

Fig. 7. Accuracy index and stability index at initial battery level 40%.

HSSHBT_2019_v28n1_64_f0008.png 이미지

Fig. 8. Accuracy index and stability index at initial battery level 80%.

HSSHBT_2019_v28n1_64_f0009.png 이미지

Fig. 9. Change of room temperature according to initial battery level.

Table 1. Scheduling according to available power consumption.

HSSHBT_2019_v28n1_64_t0001.png 이미지

References

  1. F.I. Simjee and P.H. Chou, "Efficient charging of supercapacitors for extended lifetime of wireless sensor nodes", IEEE Trans. Power Electron, Vol. 23, No. 3, pp.1526-1536, 2008. https://doi.org/10.1109/TPEL.2008.921078
  2. C. Park and P.H. Chou, "AmbiMax: Autonomous Energy Harvesting Platform for Multi-Supply Wireless Sensor Nodes", 3rd Ann. IEEE Commun. Soc. on Sens. Ad Hoc Commun. Netw (SECON), Vol. 1, pp.168-177, 2006.
  3. Y.K. Tan and S.K. Panda, "Self-Autonomous Wireless Sensor Nodes with Wind Energy Harvesting for Remote Sensing of Wind-Driven Wildfire Spread", IEEE Trans. on Instrum. Meas., Vol. 60, No. 4, April 2011.
  4. V. Leonov, T. Torfs, P. Fiorini, and C. Van Hoof, "Ther-moelectric Converters of Human Warmth for Self-Powered Wireless Sensor Nodes", IEEE Sens. J., Vol.7, No. 5, pp.650-657, 2007. https://doi.org/10.1109/JSEN.2007.894917
  5. J. Hsu, S. Zahedi, and A. Kansal, and M. Srivastava, and V. Raghunathan, "Adaptive duty cycling for energy harvesting systems", ISLPED'06 Proc. of the 2006 Int. Symp. on Low Power Electron. Design, pp.180-185, 2006.
  6. M. Shim, "An Energy-efficient MAC Protocol using Dynamic Duty-cycles for Wireless Sensor Networks with Energy Harvesting", M. S. thesis, Graduate School, KNU, Korea, Dec. 2010.
  7. D.R. Lee, "The efficient energy management method for wireless sensor node in the energy producing environment", M. S. thesis, Graduate School, Chung-Ang University, Korea, 2012.
  8. C.R. Murthy, "Power Management and Data Rate Maximization in Wireless Energy Harvesting Sensors", 2008 IEEE 19th Int. Symp. on Pers., Indoor Mob. Radio Commun., pp.1-5, 2008.
  9. M.N. Bae, B.C. Choi, and B.B. Lee, and I.H. Lee, "Development of Self-Charging Wireless Sensor Node using Solar Energy", J. KIISE : Comput. Pract. Lett., Vol. 16, pp.12-18, 2012.
  10. Y.M. Park, K.M. Kim, and Y.H. Oh, "Energy Efficient Improved Routing Protocol based on Cluster for Wireless Sensor Networks", J. Inst. Electron. Eng. Korea, Vol. 45, No. 9, pp.705-710, 2008.
  11. O.M. Gul, "Asymptotically Optimal Scheduling for Energy Harvesting Wireless Sensor Networks", 2017 IEEE 28th Ann. Int. Symp. on Pers., Indoor Mob. Radio Commun. (PIMRC), pp.1-7, 2017.
  12. Y. Li, Z. Jia, S. Xie, and F. Liu, "Dynamically Reconfigurable Hardware With a Novel Scheduling Strategy in Energy-Harvesting Sensor Networks", IEEE Sens. J., Vol.13, No. 5, pp.2032-2038, 2013. https://doi.org/10.1109/JSEN.2013.2247038
  13. V. S. Rao, R. V. Prasad, and I. G. M. M. Niemegeers, "Optimal Task Scheduling Policy in Energy Harvesting Wireless Sensor Network", 2015 IEEE Wirel. Commun. Netw. Conf. (WCNC), pp.1030-1035, 2015.