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Performance Analysis of Second Order Semi-Markov Chains: An Application to Wind Energy Production

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Listed:
  • Guglielmo D’Amico

    (Università G. d’Annunzio)

  • Filippo Petroni

    (Università degli studi di Cagliari)

  • Flavio Prattico

    (Università degli studi dell’Aquila)

Abstract

In this paper a general second order semi-Markov reward model is presented. Equations for the higher order moments of the reward process are presented for the first time and applied to wind energy production. The application is executed by considering a database, freely available from the web, that includes wind speed data taken from L.S.I. - Lastem station (Italy) and sampled every 10 minutes. We compute the expectation, the variance, the skewness and the kurtosis of the total energy produced by using the commercial blade Aircon HAWT - 10 kW.

Suggested Citation

  • Guglielmo D’Amico & Filippo Petroni & Flavio Prattico, 2015. "Performance Analysis of Second Order Semi-Markov Chains: An Application to Wind Energy Production," Methodology and Computing in Applied Probability, Springer, vol. 17(3), pages 781-794, September.
    • Handle: RePEc:spr:metcap:v:17:y:2015:i:3:d:10.1007_s11009-013-9394-z
    DOI: 10.1007/s11009-013-9394-z
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    References listed on IDEAS

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    1. D’Amico, Guglielmo & Petroni, Filippo, 2012. "A semi-Markov model for price returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4867-4876.
    2. Fredrik Stenberg & Raimondo Manca & Dmitrii Silvestrov, 2007. "An Algorithmic Approach to Discrete Time Non-homogeneous Backward Semi-Markov Reward Processes with an Application to Disability Insurance," Methodology and Computing in Applied Probability, Springer, vol. 9(4), pages 497-519, December.
    3. Aleka A. Papadopoulou & George Tsaklidis & Sally McClean & Lalit Garg, 2012. "On the Moments and the Distribution of the Cost of a Semi Markov Model for Healthcare Systems," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 717-737, September.
    4. Aleka Papadopoulou & George Tsaklidis, 2007. "Some Reward Paths in Semi-Markov Models with Stochastic Selection of the Transition Probabilities," Methodology and Computing in Applied Probability, Springer, vol. 9(3), pages 399-411, September.
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    Cited by:

    1. Yi, He & Cui, Lirong, 2017. "Distribution and availability for aggregated second-order semi-Markov ternary system with working time omission," Reliability Engineering and System Safety, Elsevier, vol. 166(C), pages 50-60.
    2. Fang, Chen & Cui, Lirong, 2021. "Reliability evaluation for balanced systems with auto-balancing mechanisms," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    3. Guglielmo D'Amico & Ada Lika & Filippo Petroni, 2019. "Risk Management of Pension Fund: A Model for Salary Evolution," IJFS, MDPI, vol. 7(3), pages 1-17, August.
    4. Dmitrii Silvestrov & Raimondo Manca, 2017. "Reward Algorithms for Semi-Markov Processes," Methodology and Computing in Applied Probability, Springer, vol. 19(4), pages 1191-1209, December.
    5. D’Amico Guglielmo & Petroni Filippo & Sobolewski Robert Adam, 2019. "Optimal Control of a Dispatchable Energy Source for Wind Energy Management," Stochastics and Quality Control, De Gruyter, vol. 34(1), pages 19-34, June.
    6. Yi, He & Cui, Lirong & Balakrishnan, Narayanaswamy, 2021. "New reliability indices for first- and second-order discrete-time aggregated semi-Markov systems with an application to TT&C system," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

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