IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORKS BASED AI CONCEPTS TO THE SMART GRID

Marko A. Dimitrijević, Miona Andrejević-Stošović, Jelena Milojković, Vančo Litovski

DOI Number
-
First page
411
Last page
424

Abstract


 

ICT and energy are two economic domains that became among the most influential to the growth of modern society. These, in the same time, due to exploitation of natural resources and producing unwanted effects to the environment, represent a kind of menace to the eco system and the human future. Implementation of measures to mitigate these unwanted effects established a new paradigm of production and distribution of electrical energy named smart grid. It relies on many novelties that improve the production, distribution and consumption of electricity among which one of the most important is the ICT. Among the ICT concepts implemented in modern smart grid one recognizes the artificial intelligence and, specifically the artificial neural network. Here, after reviewing the subject and setting the case, we are reporting some of our newest results aiming at broadening the set of tools being offered by ICT to the smart grid. We will describe our result in prediction of electricity demand and characterization of new threats to the security of the ICT that may use the grid as a carrier of the attack. We will use artificial neural networks (ANNs) as a tool in both subjects.


Full Text:

PDF

References


V. Litovski, P. Petković, ”Why The Power Grid Needs Cryptography?”, Zbornik radova VII simpozijuma Industrijska Elektronika - INDEL 2008, Banja Luka, 06.11.-08.11., 2008, pp. 75-81. Reprinted in Electronics, ISSN 1450-5843, Vol. 13, No. 1, June 2009, pp. 30-36.

M. Dimitrijević, J. Milojković, S. Bojanić, V. Litovski, “ICT and Power: Synergy and Hostility”, Proc. of the 10th Int. Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services, TELSIKS 2011, Niš, Serbia, ISBN: 978-1-4577-2017-8, pp. 186-194, Invited paper.

-, “GeSI SMARTer 2020: The Role of ICT in Driving a Sustainable Future”, The Boston Consulting Group, http://gesi.org/SMARTer2020.

S. Iyer, “Cyber Security for Smart Grid, Cryptography, and Privacy”, Hindawi Publishing Corporation, Int. J. of Digital Multimedia Broadcasting, Vol. 2011, Article ID 372020, 8 pages.

R. Harmon, H. Demirkan, “The Next Wave of Sustainable IT”, IT Professional, vol. 13, no. 1, pp. 19-25, Jan./Feb. 2011, doi:10.1109/MITP.2010.140.

-, “Electricity Consumption and Efficiency Trends in the Enlarged European Union”, Institute for Environment and Sustainability, 2007, http://www.eubusiness.com/ topics/energy/electricity-jrc.bk/

A. P. Bianzino, A. K. Raju, D. Rossi, “Greening the Internet: Measuring Web Power Consumption”, IT Pro, January/February 2011, Published by the IEEE Computer Society, pp. 48-53.

O. Nieto, et all., “Energy Profile of a Personal Computer”, Proceedings of the LVI Conf. of ETRAN, Zlatibor, Serbia, June 2012, ISBN 978-86-80509-67-9, Proc. on a disc, Paper EL3.3-1-4.

R. Adam, W. Wintersteller, From Distribution to Contribution. Commercializing the Smart Grid, Booz & Company, Munich, 2008.

J. Miller, “The Smart Grid – How Do We Get There?”, Smart Grid News, June 26, 2008. http://www.smartgridnews.com/

-, “SMART 2020: Enabling the Low Carbon Economy in the Information Age”, Climate Group, GeSI 2008, www.theclimategroup.org/assets/resources/publications/Smart2020 Report.pdf.

H. M. Al-Hamadi, S. A. Soliman, “Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model”, Electric Power Systems Research, Vol. 68, No. 1, 2004, pp. 47-59.

Tzafestas, S., and Tzafestas, E., “Computational Intelligence Techniques for Short-Term Electric Load Forecasting”, Journal of Intelligent and Robotic Systems, Vol. 31, No. 1-3, 2001, pp. 7-68.

F. Liu, R. D. Findlay, Q. Song, “A Neural Network Based Short Term Electric Load Forecasting in Ontario Canada”, in Int. Conf. on Computational Intelligence for Modelling Control and Automation, and Int. Conf. on Intelligent Agents, Web Technologies and Internet Commerce, (CIMCA-IAWTIC'06), 2006, pp. 119 – 125.

World wide competition within the EUNITE network. (2001). [Online] Available: http://neuron.tuke.sk/competition

J. Milojković, V. Litovski, “Dynamic One Step Ahead Prediction of Electricity Loads at Suburban Level”, Proc. of the First IEEE Int. Workshop on Smart grid Modeling and Simulation – at IEEE SmartGridComm 2011, SGMS2011, Brussels, October 2011, Proc. on disc, paper no. 25.

J. Milojković, V. Litovski, “One Day Ahead Peak Electricity Load Prediction”, IX Symposium Industrial Electronics, INDEL 2012, Banja Luka, November 2012, pp. 261-267.

L. Freeman, “The Changing Nature of Loads and the Impact on Electric Utilities”, Tech Advantage Expo - Electronics Exhibition and Conference 2009, New Orleans, USA, Feb. 2009, www.techadvantage.org/2009ConferenceHandouts/2E_Freeman.pdf.

V. Terzija, V. Stanojević,: “STLS Algorithm for Power-Quality Indices Estimation”, IEEE Transactions on Power Delivery, April 2008, Vol. 24, No. 2, pp. 544-552.

G. Goertzel, “An Algorithm for the Evaluation of Finite Trigonometric Series”, The American Mathematical Monthly, January 1958, No. 1, Vol. 65, pp 34-35.

M. Dimitrijević, V. Litovski, “Power Factor and Distortion Measuring for Small Loads Using USB Acquisition Module”, Journal of Circuits, Systems, and Computers, Vol. 20, No. 5, August 2011, pp. 867-880.

M. Dimitrijević, Electronic System for Polyphase Nonlinear Load Analysis Based on FPGA, PhD thesis, Niš, 2012.

J. Milojković, V. B. Litovski, “Eco-Design in Electronics – The State of the Art”, Facta Universitatis, Series: Working and Living Environmental Protection, ISSN 0354 – 804X, Vol. 2, No. 2, 2002, pp. 87-100.

F. Cleveland, “IEC TC57 security standards for the power system information infrastructure beyond simple encryption”, June 2007. IEC TC57 WG15 Security Standards White Paper ver. 11. http://www.xanthus-consulting.com/pages/publications.htm

M. Andrejević-Stošović, M. Dimitrijević, V. Litovski, “Computer Security Vulnerability Seen From the Electricity Distribution Grid Side”, Applied Artificial Intelligence, Taylor & Francis Ltd., 2014, accepted for publication


Refbacks

  • There are currently no refbacks.


ISSN: 0353-3670