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Automatic Meter Reading (AMR) system is expected to be used for real time load monitoring to optimize power generation and energy efficiency. Recently, it has been a serious problem that user’s lifestyle may be revealed by a tool to estimate consumer’s lifestyle from a real-time load profile. In order to solve this issue, Battery-based Load Hiding ( BLH ) algorithms are proposed to obfuscate an actual load profile by charging and discharging. Although such BLH algorithms have already been studied, it is important to consider multiple households case where one battery is shared among them due to its high cost. In this paper, a monetary fair BLH algorithm for multiple households is proposed. In presented scheme, the core unit calculates the difference between the charged amount and discharged one for each household. If the difference is bigger than the predefined threshold (monetary unfair occurs), the most disadvantageous and advantageous households are given priority to discharge and charge the battery and other households should charge to achieve monetary fairness. The efficiency of the scheme is demonstrated through the computer simulation with a real dataset.
Słowa kluczowe
Rocznik
Tom
Strony
110--119
Opis fizyczny
Bibliogr. 22 poz., rys., tab.
Twórcy
autor
- Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8522, Japan
autor
- Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8522, Japan
autor
- Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8522, Japan
autor
- Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8522, Japan
autor
- Department of Information and Computer Science, Keio University, 3-14-1 Hiyoshi, Kohoku, Yokohama, Kanagawa 223-8522, Japan
Bibliografia
- [1] E. L. Quinn, “Smart metering and privacy: existng law and competing policies”, Report for the Colorado Public Utilities Commission, University of Colorado Law School, Boulder, Colorado, 2009.
- [2] G. W. Hart, “Residential energy monitoring and computerized surveillance via utility power flows”, IEEE Technol. Soc. Mag., vol. 8, no. 2, pp. 12–16, 1989.
- [3] M. A. Lisovich, D. K. Mulligan, and S. B. Wicker, “Inferring personal information from demand response systems”, IEEE Secur. & Priv. Mag., vol. 8, no. 1, pp. 11–20, 2010.
- [4] A. Molina-Markham, P. Shenoy, K. Fu, E. Cecchet, and D. Irwin, “Private memoirs of a smart meter”, in ACM Worksh. Embedded Sensing Syst. for Energy-Efficien. in Build. BuildSys 2010, Zurich, Switzerland, pp. 61–66.
- [5] G. Hart, “Nonintrusive appliance load monitoring”, Proc. of the IEEE, vol. 80, no. 12, pp. 1870–1891, 1992.
- [6] M. Marceau and R. Zmeureanu, “Nonintrusive load disaggregation computer program to estimate the energy consumption of major end uses in residential buildings”, Energy Convers. & Manag., vol. 41, no. 13, pp. 1389–1403, 2000.
- [7] C. Laughman, R. Cox, S. Shaw, S. Leeb, L. Norford, and P. Armstrong, “Power signature analysis”, IEEE Power & Energy Mag., vol. 1, no. 2, pp. 56–63, 2003.
- [8] N. Batra, J. Kelly, O. Parson, H. Dutta, W. Knottenbelt, A. Rogers, A. Singh, and M. Srivastava, “NILMTK: an open source toolkit for non-intrusive load monitoring, in Proc. 50th Int. Conf. Future Energy Syst. ACM e-Energy 2014, Cambridge, UK, 2014, pp. 265–276.
- [9] S. McLaughlin, D. Podkuiko, S. Miadzvezhanka, A. Delozier, and P. McDaniel, “Multi-vendor penetration testing in the advanced metering infrastructure”, in Proc. 26th Ann. Comp. Secur. Appl. Con. Austin ACSAC’10, Texas, USA, 2010, pp. 107–116.
- [10] G. Kalogridis, C. Efthymiou, S. Z. Denic, T. A. Lewis, and R. Cepeda, “Privacy for smart meters: towards undetectable appliance load signatures”, in Proc. 1st IEEE Int. Conf. Smart Grid Commun. SmartGridComm 2010, Gaithersburg, Maryland, USA, 2010, pp. 232–237.
- [11] S. McLaughlin, P. McDaniel, and W. Aiello, “Protecting consumer privacy from electric load monitoring”, in Proc. 18th ACM Conf. Com. Commun. Secur. CCS 2011, Chicago, IL, USA, 2011, pp. 87–98.
- [12] W. Yang, N. Li, Y. Qi, W. Qardaji, S. McLaughlin, and P. McDaniel, “Minimizing private data disclosures in the smart grid”, in Proc. 19th ACM Conf. Com. Commun. Secur. CCS 2012, Raleigh, NC, USA, 2012, pp. 415–427.
- [13] J. Gomez-Vilardebo and D. Gündüz, “Smart meter privacy for multiple users in the presence of an alternative energy source”, in IEEE Trans. on Inform. Forensics & Secur., vol. 10, pp. 132–141, 2014.
- [14] L. Yang, X. Chen, J. Zhang, and H. Poor, “Optimal privacypreserving energy management for smart meters”, in Proc. IEEE Conf. Comp. Commun. IEEE INFOCOM 2014, Toronto, Ontario, Canada, 2014, pp. 513–521.
- [15] L. Alejandro et al., “Global market for smart electricity meters: Government policies driving strong growth”, Working Paper, US International Trade Commission, 2014 [Online]. Available: https://www.usitc.gov/publications/ 332/ id-037smart meters ?nal.pdf
- [16] F. Geth, D. Six, J. Tant, T. De Rybel, Peter Tant, and J. Driesen, “Techno-economical and life expectancy modeling of battery energy storage systems”, in Proc. 21st Int. Conf. and Exhibition on Electricity Distrib. CIRED 2011, Frankfurt, Germany 2011, pp. 1–4.
- [17] Ryoju estate develops “ene-self” power supply system for apartment bldgs., adopting PV modules, emergency generator and lithiumion battery, Mitsubishi Heavy Industries, Ltd., Mar. 2013 [Online]. Available: https://www.mhi.co.jp/en/m/news/story/1303071630.html (accessed: 01.10.2016).
- [18] Pecan Street Dataport – a universe of data, available around the world [Online]. Available: https://dataport.pecanstreet.org/
- [19] T. M. Cover and J. A. Thomas, Elements of information theory. Wiley, 2012.
- [20] P. E. Meyer, “Infotheo: Information-theoretic measures”, R package version 1.2.0, 2014 [Online]. Available: https://cran.r-project.org/ web/packages/infotheo/index.html
- [21] O. Parson, G. Fisher, A. Hersey, N. Batra, J. Kelly, A. Singh, W. Knottenbelt, and A. Rogers, “Dataport and NILMTK: A building data set designed for non-intrusive load monitoring”, in Proc. 1st Int. Symp. on Sig. Process. Appl. in Smart Build. at 3rd IEEE Global Conf. Sig. & Inform. Process. GlobalSIP 2015, Orlando, USA, 2015.
- [22] “Pacific Gas and Electric Company: electric schedule A-1” [Online]. Available: http://www.pge.com/.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
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Bibliografia
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bwmeta1.element.baztech-1966cc26-3491-4f6d-96c2-f3e3a2f90c23