American Journal of Data Mining and Knowledge Discovery

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Autonomic Internet of Things for Enforced Demand Management in Smart Grid

Received: Jan. 06, 2017    Accepted: Feb. 08, 2017    Published: Mar. 02, 2017
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Abstract

Recent research in the field of Internet of Things (IoT) has concentrated on the adaptation of the autonomic computing theory to make IoT self-sufficient and self-managing. The smart grid is one popular IoT application which can greatly benefit from the adoption of autonomy. In this paper, we propose the idea of enforced demand management (EDM) in smart grid as an implementation of the autonomic computing framework. Instead of allowing all consumer appliances to be active, the smart grid can actuate and control selected appliances remotely and autonomic-ally. This will allow the smart grid to be able to exercise some control over the load and consequently the demand it faces during peak hours of usage. Subsequently, the smart grid will be able to enhance efficiency and reliability. Furthermore, cellular network requirements for enabling such a method are also highlighted for the case of Long-Term-Evolution (LTE).

DOI 10.11648/j.ajdmkd.20170202.15
Published in American Journal of Data Mining and Knowledge Discovery ( Volume 2, Issue 2, June 2017 )
Page(s) 69-75
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Smart Grid, Internet of Things (IoT), Wireless Sensor Networks (WSN), Autonomic Computing, Demand Response

References
[1] Brezhnev, Eugene, and Vyacheslav Kharchenko. "BBN-based approach for assessment of Smart Grid and nuclear power plant interaction." Design & Test Symposium, 2013 East-West. IEEE, 2013.
[2] P. Siano, C. Cecati, C. Citro, and P. Siano, “Smart operation of windturbines and diesel generators according to economic criteria,” IEEE Trans. Ind. Electron., vol. 58, no. 10, pp. 4514–4525, Oct. 2011.
[3] Shu-wen, Wu. "Research on the key technologies of IoT applied on smart grid." Electronics, Communications and Control (ICECC), 2011 International Conference on. IEEE, 2011.
[4] Erol-Kantarci, Melike, and Hussein T. Mouftah. "Energy-Efficient Information and Communication Infrastructures in the Smart Grid: A Survey on Interactions and Open Issues." Communications Surveys & Tutorials, IEEE 17.1 (2015): 179-197.
[5] Li Na, Chen Xi, Wu Fan and Li Xiangzhen, Study of Hierarchical Information Aggregation Technology on the Internet of Things for Smart Grid, Information and Communications Technologies. pp. 20-27, vol 2. 2010.
[6] Singh, D., Tripathi, G., & Jara, A. J. (2014, March). A survey of Internet-of-Things: Future vision, architecture, challenges and services. In Internet of Things (WF-IoT), 2014 IEEE World Forum on (pp. 287-292). IEEE.
[7] Matharu, G. S., Upadhyay, P., & Chaudhary, L. (2014, December). The Internet of Things: Challenges & security issues. In Emerging Technologies (ICET), 2014 International Conference on (pp. 54-59). IEEE.
[8] Scarfò, A. (2014, September). Internet of Things, the Smart X enabler. In Intelligent Networking and Collaborative Systems (INCoS), 2014 International Conference on (pp. 569-574). IEEE.
[9] Q. M. Ashraf and M. H. Habaebi, "Autonomic schemes for threat mitigation in Internet of Things," Elsevier Journal of Network and Computer Applications, vol. 49, no. 1, pp. 112-127, 2015.
[10] J. O. Kephart and D. M. Chess, “The vision of autonomic computing,” Computer, vol. 36, no. 1, pp. 41-50, Jan. 2003. doi: 10.1109/MC.2003.1160055.
[11] AAD Knowledge Transfer Network, "Autonomous Systems: Opportunities and Challenges for the UK," 2012. [Online]. Available: https://connect.innovateuk.org/c/document_library/get_file?folder Id=278657&name=DLFE-91023.pdf
[12] Ashraf, Q. M., & Habaebi, M. H. (2015). “Introducing Autonomy in Internet of Things.” Recent Advances in Computer Science. 215-221.
[13] Yu, R., Zhang, Y., Gjessing, S., Yuen, C., Xie, S., & Guizani, M. (2011). Cognitive radio based hierarchical communications infrastructure for smart grid. IEEE Network, 25 (October), 6 –14. doi: 10.1109/MNET.2011.6033030.
[14] R. H. Khan, J. Y. Khan, “A Heterogeneous WiMAX-WLAN Network for AMI Communications in the Smart grid”, in IEEE International Workshop on Wireless Infrastructure for Smart Grid, Nov. 2012.
[15] Ahmed, M. H. U., Alam, M. G. R., Kamal, R., Hong, C. S., & Lee, S. (2012). Smart grid cooperative communication with smart relay. Journal of Communications and Networks, 14 (6), 640–652. doi: 10.1109/JCN.2012.00030.
[16] Tingting, Jiang, and Zhao Junhui. "Optimal gateway deployment in the smart grid Machine-to-Machine networks." Communications and Networking in China (CHINACOM), 2014 9th International Conference on. IEEE, 2014.
[17] Fan, Zhong, et al. "The power of data: Data analytics for M2M and smart grid." Innovative Smart Grid Technologies (ISGT Europe), 2012 3rd IEEE PES International Conference and Exhibition on. IEEE, 2012.
[18] Salam, S. Abdul, et al. "M2M communication in Smart Grids: Implementation scenarios and performance analysis." Wireless Communications and Networking Conference Workshops (WCNCW), 2012 IEEE. IEEE, 2012.
[19] Lu, Guang, et al. "Enabling smart grid with ETSI M2M standards." Wireless Communications and Networking Conference Workshops (WCNCW), 2012 IEEE. IEEE, 2012.
[20] Cooper, J., & James, A. (2009). Challenges for database management in the internet of things. IETE Technical Review, 26 (5), 320-329.
[21] Yun, M., & Yuxin, B. (2010, June). Research on the architecture and key technology of Internet of Things (IoT) applied on smart grid. In Advances in Energy Engineering (ICAEE), 2010 International Conference on (pp. 69-72). IEEE.
[22] Q. M. Ashraf, M. H. Habaebi and J. Chebil, "SIHAT: simplifying interfaces in health-nets for achieving telemetry," in Handbook on the emerging trends in scientific research, Kuala Lumpur, Pak Publishing Group, 2014, pp. 207-217.
[23] C. Gellings, “The concept of demand-side management for electric utilities,” Proc. IEEE, vol. 73, no. 10, pp. 1468–1470, Oct. 1985.
[24] M. Fahrioglu, M. Fern, and F. Alvarado, “Designing cost effective de- mand management contracts using game theory,” in Proc. IEEE Power Eng. Soc. 1999 Winter Meet., New York, Jan. 1999.
[25] N. Ruiz, I. Cobelo, and J. Oyarzabal, “A direct load control model for virtual power plant management,” IEEE Trans. Power Syst., vol. 24, no. 2, pp. 959–966, May 2009.
[26] Y. Tang, H. Song, F. Hu, and Y. Zou, “Investigation on TOU pricing principles,” in Proc. IEEE PES Transm. Distrib. Conf. Exhib.: Asia Pacific, Dalian, China, Aug. 2005.
[27] S. Zeng, J. Li, and Y. Ren, “Researchoftime-of-useelectricitypricing models in China: A survey,” in Proc. IEEE Int. Conf. Ind. Eng. Eng. Manage., Singapore, Dec. 2008.
[28] Samadi, Pedram, et al. "Advanced demand side management for the future smart grid using mechanism design." Smart Grid, IEEE Transactions on 3.3 (2012): 1170-1180.
[29] P. Rowles, 'The Difference between Demand Response and Demand Side Management | energy advantage', Energyadvantage.com, 2010. [Online]. Available: http://www.energyadvantage.com/blog/2010/02/demand-response-demand-side-management-what%E2%80%99s-difference/. [Accessed: 11-Jun-2015].
[30] C. Hertzog, 'Smart Grid Library', 2015. [Online]. Available: http://www.smartgridlibrary.com/. [Accessed: 11-Jun-2015].
[31] Q. Ashraf, M. Habaebi, G. Sinniah, M. Ahmed, S. Khan and S. Hameed, "Autonomic protocol and architecture for devices in Internet of Things," in Proceedings of IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia 2014), Kuala Lumpur, 2014.
[32] S. Westwood, “The State of LTE,” OpenSignal Global State of LTE Report, March 2015.
[33] Vodafone, Huawei, HiSilicon, Ericsson and Qualcomm, “RP-161324: Enhancement of NB-IoT”, 16 June 2016.
Cite This Article
  • APA Style

    Qazi Mamoon Ashraf, Chun Yeow Yeoh, Ayesheh Ahrari Khalaf, Ahmed Al-Haddad, Mohamed Hadi Habaebi, et al. (2017). Autonomic Internet of Things for Enforced Demand Management in Smart Grid. American Journal of Data Mining and Knowledge Discovery, 2(2), 69-75. https://doi.org/10.11648/j.ajdmkd.20170202.15

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    ACS Style

    Qazi Mamoon Ashraf; Chun Yeow Yeoh; Ayesheh Ahrari Khalaf; Ahmed Al-Haddad; Mohamed Hadi Habaebi, et al. Autonomic Internet of Things for Enforced Demand Management in Smart Grid. Am. J. Data Min. Knowl. Discov. 2017, 2(2), 69-75. doi: 10.11648/j.ajdmkd.20170202.15

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    AMA Style

    Qazi Mamoon Ashraf, Chun Yeow Yeoh, Ayesheh Ahrari Khalaf, Ahmed Al-Haddad, Mohamed Hadi Habaebi, et al. Autonomic Internet of Things for Enforced Demand Management in Smart Grid. Am J Data Min Knowl Discov. 2017;2(2):69-75. doi: 10.11648/j.ajdmkd.20170202.15

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  • @article{10.11648/j.ajdmkd.20170202.15,
      author = {Qazi Mamoon Ashraf and Chun Yeow Yeoh and Ayesheh Ahrari Khalaf and Ahmed Al-Haddad and Mohamed Hadi Habaebi and Wan Razli Wan Abdullah and Mohamed Razman Yahya},
      title = {Autonomic Internet of Things for Enforced Demand Management in Smart Grid},
      journal = {American Journal of Data Mining and Knowledge Discovery},
      volume = {2},
      number = {2},
      pages = {69-75},
      doi = {10.11648/j.ajdmkd.20170202.15},
      url = {https://doi.org/10.11648/j.ajdmkd.20170202.15},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajdmkd.20170202.15},
      abstract = {Recent research in the field of Internet of Things (IoT) has concentrated on the adaptation of the autonomic computing theory to make IoT self-sufficient and self-managing. The smart grid is one popular IoT application which can greatly benefit from the adoption of autonomy. In this paper, we propose the idea of enforced demand management (EDM) in smart grid as an implementation of the autonomic computing framework. Instead of allowing all consumer appliances to be active, the smart grid can actuate and control selected appliances remotely and autonomic-ally. This will allow the smart grid to be able to exercise some control over the load and consequently the demand it faces during peak hours of usage. Subsequently, the smart grid will be able to enhance efficiency and reliability. Furthermore, cellular network requirements for enabling such a method are also highlighted for the case of Long-Term-Evolution (LTE).},
     year = {2017}
    }
    

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    AU  - Qazi Mamoon Ashraf
    AU  - Chun Yeow Yeoh
    AU  - Ayesheh Ahrari Khalaf
    AU  - Ahmed Al-Haddad
    AU  - Mohamed Hadi Habaebi
    AU  - Wan Razli Wan Abdullah
    AU  - Mohamed Razman Yahya
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    T2  - American Journal of Data Mining and Knowledge Discovery
    JF  - American Journal of Data Mining and Knowledge Discovery
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    AB  - Recent research in the field of Internet of Things (IoT) has concentrated on the adaptation of the autonomic computing theory to make IoT self-sufficient and self-managing. The smart grid is one popular IoT application which can greatly benefit from the adoption of autonomy. In this paper, we propose the idea of enforced demand management (EDM) in smart grid as an implementation of the autonomic computing framework. Instead of allowing all consumer appliances to be active, the smart grid can actuate and control selected appliances remotely and autonomic-ally. This will allow the smart grid to be able to exercise some control over the load and consequently the demand it faces during peak hours of usage. Subsequently, the smart grid will be able to enhance efficiency and reliability. Furthermore, cellular network requirements for enabling such a method are also highlighted for the case of Long-Term-Evolution (LTE).
    VL  - 2
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Author Information
  • Telekom Research and Development, Cyberjaya, Malaysia

  • Telekom Research and Development, Cyberjaya, Malaysia

  • IElectrical and Computer Engineering Faculty, International Islamic University Malaysia, Kuala Lumpur, Malaysia

  • IElectrical and Computer Engineering Faculty, International Islamic University Malaysia, Kuala Lumpur, Malaysia

  • IElectrical and Computer Engineering Faculty, International Islamic University Malaysia, Kuala Lumpur, Malaysia

  • Telekom Research and Development, Cyberjaya, Malaysia

  • Telekom Research and Development, Cyberjaya, Malaysia

  • Section