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Optimal Design of Photovoltaic Connected Energy Storage System Using Markov Chain Models

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  • Woo-sung Kim

    (College of Business Administration, Konkuk University, Seoul 05029, Korea)

  • Hyunsang Eom

    (School of Mechanical and Control Engineering, Handong Global University, Pohang 37554, Korea)

  • Youngsung Kwon

    (School of Mechanical and Control Engineering, Handong Global University, Pohang 37554, Korea)

Abstract

This study improves an approach for Markov chain-based photovoltaic-coupled energy storage model in order to serve a more reliable and sustainable power supply system. In this paper, two Markov chain models are proposed: Embedded Markov and Absorbing Markov chain. The equilibrium probabilities of the Embedded Markov chain completely characterize the system behavior at a certain point in time. Thus, the model can be used to calculate important measurements to evaluate the system such as the average availability or the probability when the battery is fully discharged. Also, Absorbing Markov chain is employed to calculate the expected duration until the system fails to serve the load demand, as well as the failure probability once a new battery is installed in the system. The results show that the optimal condition for satisfying the availability of 3 nines (0.999), with an average load usage of 1209.94 kWh, is the energy storage system capacity of 25 MW, and the number of photovoltaic modules is 67,510, which is considered for installation and operation cost. Also, when the initial state of charge is set to 80% or higher, the available time is stable for more than 20,000 h.

Suggested Citation

  • Woo-sung Kim & Hyunsang Eom & Youngsung Kwon, 2021. "Optimal Design of Photovoltaic Connected Energy Storage System Using Markov Chain Models," Sustainability, MDPI, vol. 13(7), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:7:p:3837-:d:527334
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    References listed on IDEAS

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    Cited by:

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    2. Hassan Shaban & Essam H. Houssein & Marco Pérez-Cisneros & Diego Oliva & Amir Y. Hassan & Alaa A. K. Ismaeel & Diaa Salama AbdElminaam & Sanchari Deb & Mokhtar Said, 2021. "Identification of Parameters in Photovoltaic Models through a Runge Kutta Optimizer," Mathematics, MDPI, vol. 9(18), pages 1-22, September.
    3. Arturo Y. Jaen-Cuellar & David A. Elvira-Ortiz & Roque A. Osornio-Rios & Jose A. Antonino-Daviu, 2022. "Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review," Energies, MDPI, vol. 15(15), pages 1-36, July.

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