Distributed Energy Resource Operation Analysis Using Discrete Event-Simulation

Rupnik, Bojan; Kragelj, Dušan; Šinko, Simona; Kramberger, Tomaž

doi:10.17559/tv-20190626184415

Cited by 1 publication

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“…Accordingly, the authors use discrete event simulation (DES) to describe production systems from a real environment [16]. For example, Rupnik et al [17] in their paper present a DES approach for simulation of distributed energy resources. The main advantage of DES is the ability to create a digital model of the real production system in a relatively simple way, without interfering with the operation of the real system [18].…”

Section: Background and Literature Reviewmentioning

confidence: 99%

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

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Planning the order and size of batches is an extremely complex task especially if these tasks are related to production companies in a real environment. This research deals with the problem of determining the entry order and size of product batches in order to optimize inter-operational waits, in the form of waiting in queues for processing and waiting due to the setting-up of the workplace. In real environment, these waits represent a large share of the time spent in the production of a unit of product in a hybrid flow shop. This problem is almost impossible to be solved with analytical models because they may require many simplifying assumptions. Therefore, a simulationoptimization approach is used to solve this problem. Discrete event simulation allows greater flexibility in the representation of the real production system, while the integrated optimization tool, a genetic algorithm, serves to find the optimal solution relatively quickly. To ensure simpler production management, batch size is defined as a fixed value with the exception of a different first or last batch which represents the difference to the required production volume. Therefore, two optimization cases are presented in the paper. Although both cases show improvements, the case when a different batch is the first batch shows better results. In that case, the share of setup time in the total production time of the product unit was reduced from 4% to 3%, and the share of waiting time in the queue for processing was reduced from 76% to 32%.

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Section: Background and Literature Reviewmentioning

confidence: 99%

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

2021

Teh. vjesn.

View full text Add to dashboard Cite

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Distributed Energy Resource Operation Analysis Using Discrete Event-Simulation

Cited by 1 publication

References 0 publications

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

Determining the Minimum Waiting Times in a Hybrid Flow Shop Using Simulation-Optimization Approach

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