Quantifying the Reliability of Electrical Networks: An Approach via Markovian Reward Models
Abstract
Power grids are going through a phase transition. Whereas power grids traditionally encompassed centralized sources and dumb distribution networks, the new smart grids count with distributed power generation, smart meters and intelligent demand response programs. One of the key problems faced in this transition consists of assessing the reliability gains due to automation. In this paper we present a Markov reward model to quantify the reliability gains due to the smartening of the power grid. The metrics generalize standard quantities, such as SAIDI and CAIDI, that are widely used in the electrical engineering domain.References
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Liu, Y. and Trivedi, K. (2006). Survivability quantification: The analytical modeling approach. International Journal of Performability Engineering, 2(1):29–44.
Meyer, J. (1980). On evaluating the performability of degradable computing systems. IEEE Transactions on Computers, 29:720–731.
Meyer, J. F. (1992). Performability: a retrospective and some pointers to the future. Perf. Evaluation, 14:139–156.
Mohagheghi, S., Yang, F., and Falahati, B. (2011). Impact of demand response on distribution system reliability. In Power and Energy Society General Meeting, 2011 IEEE, pages 1–7.
Wang, S., Zhao, W., and Chen, Y. (2008). Distribution system reliability evaluation considering dg impacts. In Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, pages 2603–2607.
Waseem, I. (2008). Impacts of Distributed Generation on the Residential Distributed Network Operation. M.Sc. Thesis, Virginia Polytechnic Institute.
Zhang, J. and Bo, Z. (2010). Research of the impact of distribution generation on distribution network loss. In Universities Power Engineering Conference 2010, pages 1–4.
Zou, K., Keerthipala, W., and Perera, S. (2007). SAIDI minimization of a remote distribution feeder. In AUPEC 2007, pages 1–5.
de Souza e Silva, E., Figueiredo, D., and Leão, R. (2009). The TangramII integrated modeling environment for computer systems and networks. SIGMETRICS Perform. Eval. Rev., 36(4):64–69.
de Souza e Silva, E. and Muntz, R. (1992). Métodos Computacionais de Solução de Cadeias de Markov. VIII Escola de Computação.
E. de Souza e Silva and H.R. Gail (2001). The Uniformization Method in Performability Analysis. In Performability Modeling: Techniques and Tools. John Wiley & Sons.
Elmakias, D. (2008). New Computational Methods in Power System Reliability. Springer Publishing Company, Incorporated, 1st edition.
Keshav, S. and Rosenberg, C. (2011). How internet concepts and technologies can help green and smarten the electrical grid. ACM SIGCOMM Computer Communication Review.
Liu, Y. and Trivedi, K. (2006). Survivability quantification: The analytical modeling approach. International Journal of Performability Engineering, 2(1):29–44.
Meyer, J. (1980). On evaluating the performability of degradable computing systems. IEEE Transactions on Computers, 29:720–731.
Meyer, J. F. (1992). Performability: a retrospective and some pointers to the future. Perf. Evaluation, 14:139–156.
Mohagheghi, S., Yang, F., and Falahati, B. (2011). Impact of demand response on distribution system reliability. In Power and Energy Society General Meeting, 2011 IEEE, pages 1–7.
Wang, S., Zhao, W., and Chen, Y. (2008). Distribution system reliability evaluation considering dg impacts. In Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, pages 2603–2607.
Waseem, I. (2008). Impacts of Distributed Generation on the Residential Distributed Network Operation. M.Sc. Thesis, Virginia Polytechnic Institute.
Zhang, J. and Bo, Z. (2010). Research of the impact of distribution generation on distribution network loss. In Universities Power Engineering Conference 2010, pages 1–4.
Zou, K., Keerthipala, W., and Perera, S. (2007). SAIDI minimization of a remote distribution feeder. In AUPEC 2007, pages 1–5.
Published
2012-07-16
How to Cite
DINIZ, Morganna; MENASCHÉ, Daniel S.; LEÃO, Rosa M. M.; SILVA, Edmundo de Souza e; AVRITZER, Alberto.
Quantifying the Reliability of Electrical Networks: An Approach via Markovian Reward Models. In: WORKSHOP ON PERFORMANCE OF COMPUTER AND COMMUNICATION SYSTEMS (WPERFORMANCE), 11. , 2012, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2012
.
p. 141-154.
ISSN 2595-6167.
