Abstract
Good demand side management in smart grids does not only depend on the amount of energy consumed by various appliances, but also on the temporal characteristics of the consumption, i.e. the load profile of the appliances. Representative load profiles can be used for predicting future energy consumption. However, a load profile is hard to characterise as it often depends on the operational conditions of the appliance when the measurements were taken. For instance the load profile of a washing machine will depend on the amount of cloths and the inlet water temperature. This paper presents a methodology for empirically obtaining the load profile from an ensemble of event driven traces of a stochastically varying mode of an appliance.
The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant number 608806 CoSSMic.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Amato, A., Di Martino, B., Scialdone, M., Venticinque, S., Hallsteinsen, S., Jiang, S.: A distributed system for smart energy negotiation. In: Fortino, G., Di Fatta, G., Li, W., Ochoa, S., Cuzzocrea, A., Pathan, M. (eds.) IDCS 2014. LNCS, vol. 8729, pp. 422–434. Springer, Heidelberg (2014)
Asar, A., Hassnain, S., Khattack, A.: A multi-agent approach to short term load forecasting problem. Int. J. Intell. Control Syst. 10(1), 52–59 (2005)
Bansal, R.C., Pandey, J.C.: Load forecasting using artificial intelligence techniques: a literature survey. Int. J. Comput. Appl. Technol. 22(2/3), 109–119 (2005)
Barker, S.K., Kalra, S., Irwin, D.E., Shenoy, P.J.: Empirical characterization and modeling of electrical loads in smart homes. In: International Green Computing Conference, IGCC 2013, Arlington, VA, USA, 27–29 June 2013, Proceedings. pp. 1–10 (2013)
de Boor, C.: A Practical Guide to Splines, Applied Mathematical Sciences, vol. 27. Springer, New York (1978)
Claude, E., Shannon, C.E.: Communication in the presence of noise. Proc. Inst. Radio Eng. 37(1), 10–21 (1949)
Feinberg, E., Genethliou, D.: Load forecasting. In: Chow, J., Wu, F., Momoh, J. (eds.) Applied Mathematics for Restructured Electric Power Systems. Power Electronics and Power Systems, pp. 269–285. Springer, US (2012)
Saw, J.G., Yang, M.C.K., Mo, T.C.: Chebyshev inequality with estimated mean and variance. Am. Stat. 38(2), 130 (1984)
Höllig, K., Hörner, J.: Approximation and Modeling with B-Splines. Society for Industrial and Applied Mathematics, Philadelphia (2014)
Gelazanskas, L., Gamage, K.A.A.: Demand side management in smart grid: a review and proposals for future direction. Sustain. Cities Soc. 11, 22–30 (2014)
Mahmoud, A., Ortmeyer, T., Reardon, R.E.: Load forecasting bibliography phase ii. Power Apparatus Syst. IEEE Trans. PAS 100(7), 3217–3220 (1981)
Björck, Å.: Numerical Methods for Least Squares Problems. Other Titles in Applied Mathematics, Society for Industrial and Applied Mathematics (SIAM) (1996)
Rathmair, M., Haase, J.: Simulator for smart load management in home appliances. In: SIMUL 2012 : The Fourth International Conference on Advances in System Simulation, pp. 1–6 (2012)
Rothe, M., Wadhwani, D.A., Wadhwani, D.: Short term load forecasting using multi parameter regression. Int. J. Comput. Sci. Inf. Secur. 6(2), 303–306 (2009). arxiv.org/abs/0912.1015
Ruzzelli, A., Nicolas, C., Schoofs, A., O’Hare, G.: Real-time recognition and profiling of appliances through a single electricity sensor. In: Proceedings of the 7th Annual IEEE Communications Society Conference on Sensor Mesh and Ad Hoc Communications and Networks (SECON), pp. 1–9, June 2010
Wood, G., Newborough, M.: Energy-use information transfer for intelligent homes: Enabling energy conservation with central and local displays. Energy Build. 39(4), 495–503 (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Horn, G., Venticinque, S., Amato, A. (2015). Inferring Appliance Load Profiles from Measurements. In: Di Fatta, G., Fortino, G., Li, W., Pathan, M., Stahl, F., Guerrieri, A. (eds) Internet and Distributed Computing Systems. IDCS 2015. Lecture Notes in Computer Science(), vol 9258. Springer, Cham. https://doi.org/10.1007/978-3-319-23237-9_11
Download citation
DOI: https://doi.org/10.1007/978-3-319-23237-9_11
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-23236-2
Online ISBN: 978-3-319-23237-9
eBook Packages: Computer ScienceComputer Science (R0)