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

Arthur Henrique de Andrade Melani, Miguel Angelo de Carvalho Michalski, Carlos Alberto Murad, Adherbal Caminada Netto and Gilberto Francisco Martha de Souza
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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

Energies, 2022, vol. 15, issue 8, 1-16

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.

Keywords: generalized stochastic Petri nets (GSPN); maintenance; distributed energy resources (DER); small hydroelectric power plants (SHPP) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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