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Generalized Stochastic Petri Nets for Planning and Optimizing Maintenance Logistics of Small Hydroelectric Power Plants

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  • Arthur Henrique de Andrade Melani

    (Department of Mechatronics and Mechanical System Engineering, Polytechnic School of the University of São Paulo, São Paulo 05508-030, Brazil)

  • Miguel Angelo de Carvalho Michalski

    (Department of Mechatronics and Mechanical System Engineering, Polytechnic School of the University of São Paulo, São Paulo 05508-030, Brazil)

  • Carlos Alberto Murad

    (Department of Mechatronics and Mechanical System Engineering, Polytechnic School of the University of São Paulo, São Paulo 05508-030, Brazil)

  • Adherbal Caminada Netto

    (Department of Mechanical Engineering, Polytechnic School of the University of São Paulo, São Paulo 05508-010, Brazil)

  • Gilberto Francisco Martha de Souza

    (Department of Mechatronics and Mechanical System Engineering, Polytechnic School of the University of São Paulo, São Paulo 05508-030, Brazil)

Abstract

Maintenance plays a crucial role in the availability of an asset. In particular, when a company’s assets are decentralized, logistical aspects directly impact maintenance management and, consequently, productivity. In the energy generation sector, this scenario is common in enterprises and projects in which distributed energy resources (DERs), such as small hydroelectric power plants (SHPPs), are considered. Hence, the objective of this work is to propose an application of generalized stochastic Petri nets (GSPN) for the planning and optimization of the maintenance logistics of a DER enterprise with two SHPPs. In the presented case study, different scenarios are modeled considering logistical aspects related to the availability of spare parts and the sharing of maintenance teams between plants. From the financial return resulting from the estimated energy generation and the operating cost of each simulated scenario, the most profitable one can be estimated. The results demonstrate the ability of GSPNs to estimate the influence of the number of spare parts and maintenance teams on the availability of DERs, allowing the optimization of costs related to maintenance logistics.

Suggested Citation

  • Arthur Henrique de Andrade Melani & Miguel Angelo de Carvalho Michalski & Carlos Alberto Murad & Adherbal Caminada Netto & Gilberto Francisco Martha de Souza, 2022. "Generalized Stochastic Petri Nets for Planning and Optimizing Maintenance Logistics of Small Hydroelectric Power Plants," Energies, MDPI, vol. 15(8), pages 1-16, April.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:8:p:2742-:d:789745
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    References listed on IDEAS

    as
    1. Arthur H.A. Melani & Carlos A. Murad & Adherbal Caminada Netto & Gilberto F.M. Souza & Silvio I. Nabeta, 2019. "Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets," Energies, MDPI, vol. 12(10), pages 1-28, May.
    2. Jakov Batelić & Karlo Griparić & Dario Matika, 2021. "Impact of Remediation-Based Maintenance on the Reliability of a Coal-Fired Power Plant Using Generalized Stochastic Petri Nets," Energies, MDPI, vol. 14(18), pages 1-14, September.
    3. Sungeun Jung & Younghye Bae & Jongsung Kim & Hongjun Joo & Hung Soo Kim & Jaewon Jung, 2021. "Analysis of Small Hydropower Generation Potential: (1) Estimation of the Potential in Ungaged Basins," Energies, MDPI, vol. 14(11), pages 1-20, May.
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    5. Chang Wook Kang & Muhammad Imran & Muhammad Omair & Waqas Ahmed & Misbah Ullah & Biswajit Sarkar, 2019. "Stochastic-Petri Net Modeling and Optimization for Outdoor Patients in Building Sustainable Healthcare System Considering Staff Absenteeism," Mathematics, MDPI, vol. 7(6), pages 1-26, June.
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