Power grids deal with the business of generation, transmission, and distribution of electric power. Recently, interest in power quality in electrical distribution systems has increased rapidly. In Korea, the communication network to deliver voltage, current, and temperature measurements gathered from pole transformers to remote monitoring centers employs cellular mobile technology. Due to high cost of the cellular mobile technology, power quality monitoring measurements are limited and data gathering intervals are large. This causes difficulties in providing the power quality monitoring service. To alleviate the problems, in this paper we present a communication infrastructure to provide low cost, reliable data delivery. The communication infrastructure consists of wired connections between substations and monitoring centers, and wireless connections between pole transformers and substations. For the wireless connection, we employ a wireless sensor network and design its corresponding data forwarding protocol to improve the quality of data delivery. For the design, we adopt a tree-based data forwarding protocol in order to customize the distribution pattern of the power quality information. We verify the performance of the proposed data forwarding protocol quantitatively using the NS-2 network simulator.
References
[1]
Santoso, S; Beaty, HW; Dugan, RC; McGranaghan, MF. Electrical Power Systems Quality; McGraw-Hill: New York, NY, USA, 1996.
[2]
Korea Electric Power Corporation (KEPCO). Available on line: http://www.kepco.co.kr/eng/ (accessed on 15 September 2010).
[3]
Akkaya, K; Younis, M. A survey on routing protocols for wireless sensor networks. Elsevier Ad Hoc Networks?2005, 3, 325–349, doi:10.1016/j.adhoc.2003.09.010.
[4]
Intanagonwiwat, C; Govindan, R; Estrin, D. Directed diffusion: A scalable and robust communication paradigm for sensor networks. Proceedings of ACM International Conference on Mobile Computing and Networking, Boston, MA, USA, 6–11 August, 2000; ACM Press: New York, NY, USA, 2000; pp. 56–67.
[5]
Handy, MJ; Haase, M; Timmermann, D. Low energy adaptive clustering hierarchy with deterministic cluster-head selection. Proceedings of IEEE International Conference on Mobile Wireless Communications and Networks, Stockholm, Sweden, 9–11 September, 2002; pp. 368–372.
[6]
Krap, B; Kung, HT. GPSR: Greedy Perimeter Stateless Routing for wireless networks. Proceedings of ACM International Conference on Mobile Computing and Networking, Boston, MA, USA, 6–11 August, 2000; ACM Press: New York, NY, USA, 2000; pp. 243–254.
[7]
Hou, YT; Shi, Y; Sherali, HD; Midkiff, SF. On energy provisioning and relay node placement for wireless sensor networks. IEEE Trans. Wirel. Commun?2005, 4, 2579–2590, doi:10.1109/TWC.2005.853969.
[8]
Ye, F; Luo, H; Cheng, J; Lu, S; Zhang, L. A two-tier data dissemination model for large-scale wireless sensor networks. Proceedings of ACM International Conference on Mobile Computing and Networking, Atlanta, GA, USA, 23–26 September, 2002; ACM Press: New York, NY, USA, 2002; pp. 148–159.
[9]
Jung, H; Kim, JY; Chang, KT; Jung, CS. Slope movement detection using ubiquitous sensor network. J. Electr. Eng. Technol?2009, 4, 143–148, doi:10.5370/JEET.2009.4.1.143.
[10]
Romer, K; Mattern, F. The design space of wireless sensor networks. IEEE Wirel. Commun?2004, 11, 54–61, doi:10.1109/MWC.2004.1368897.
[11]
Al-Karaki, JN; Kamal, AE. Routing techniques in wireless sensor networks: A survey. IEEE Wirel. Commun?2004, 11, 6–28.
[12]
The ZebraNet Wildlife Tracker, Available online: http://www.princeton.edu/~mrm/zebranet.html/ (accessed on 15 September 2010).
[13]
Citysense, Available online: http://www.citysense.com/ (accessed on 15 September 2010).
[14]
SensorMap, Available online: http://atom.research.microsoft.com/sensewebv3/sensormap/ (accessed on 15 September 2010).
[15]
Anagnostopoulos, C; Hadjiefthymiades, S. Enhancing situation-aware systems through imprecise reasoning. IEEE Trans. Mob. Comput?2008, 7, 1153–1168, doi:10.1109/TMC.2008.34.
[16]
O'Donoghue, J; Herbert, J. Data management system: A context aware architecture for pervasive patient monitoring. Proceeding of International Conference on Smart Homes and Health Telematic, Sherbrooke, Québec, PQ, Canada, 4–6 July, 2005; pp. 159–166.
[17]
IEEE Std. 802.15.4. Part 15.4: Wireless medium access control (MAC) and physical layer (PHY) specifications for low-rate wireless personal area networks (WPANs), 2003.
[18]
IEEE Std. 802.11. Wireless LAN medium access control (MAC) and physical layer (PHY) specification: higher speed physical layer (PHY) extension in the 2.4GHz Band, 1999.
[19]
Available online: http://www.isi.edu/nsnam/ns/ (accessed on 15 September 2010).
[20]
Rappaport, TS. Wireless Communications, Principles and Practice; Prentice Hall: Englewood Cliffs, NJ, USA, 1996.
[21]
Li, J; Blake, C; Couto, DSJD; Lee, HI; Morris, R. Capacity of ad hoc wireless networks. Proceedings of ACM International Conference on Mobile Computing and Networking, Rome, Italy, 16–21 July, 2001; ACM Press: New York, NY, USA, 2001; pp. 61–69.
[22]
Toumpis, S; Goldsmith, AJ. Capacity regions for wireless ad hoc networks. IEEE Trans. Wirel. Commun?2003, 2, 736–748.
[23]
Gupta, P; Kumar, PR. The capacity of wireless networks. IEEE Trans. Inform. Theory?2000, 46, 388–404, doi:10.1109/18.825799.