Special Issue: Modeling and Simulation of Energy Systems

Adams, Thomas A.

doi:10.3390/pr7080523

Cited by 3 publications

(1 citation statement)

References 21 publications

(13 reference statements)

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“…Reviews of dynamic simulation applications for optimizing energy and chemical systems are shown in [3,4], while applications of discrete event simulation to the optimization of industrial systems can be found in [4][5][6]. Usage of simulation in specific situations are presented in [7] for sustainable plant design, in [8] for gasifier pressure modeling, and in [9] for analyzing a petrochemical process wastewater plant.…”

Section: A Literature Reviewmentioning

confidence: 99%

A Stochastic Simulator of a Multi-Component Distillation Tower Built as an Excel Macro

Hernández¹,

Rosas²,

Torres³

2023

Eng. Technol. Appl. Sci. Res.

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Dynamic process simulation is widely used in teaching controller design, as it allows foreseeing the performance of different control configurations and controller tunings. Currently, most college-level controller design exercises that are based on simulation consider deterministic perturbations (i.e. steps or ramps). In real life however, processes are more likely to face fluctuating, random disturbances, so the use of stochastic simulation in controller tuning exercises would provide students with an experience closer to their future professional practice than that provided by deterministic simulation. However, public institutions attempting to use dynamic, stochastic simulators in teaching, are hindered by the need of buying licenses of simulation packages or specialized programming languages (such as Matlab), as there aren´t any dynamic, stochastic simulators available as downloadable freeware. This paper shows a dynamic, stochastic simulator with a friendly interface of a distillation tower, developed as an Excel macro. This simulator has the advantage that it can be used at no cost to educational institutions since Excel is almost universally known and used by college faculties.

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Section: A Literature Reviewmentioning

confidence: 99%

A Stochastic Simulator of a Multi-Component Distillation Tower Built as an Excel Macro

Hernández¹,

Rosas²,

Torres³

2023

Eng. Technol. Appl. Sci. Res.

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Small-Scale Hybrid and Polygeneration Renewable Energy Systems: Energy Generation and Storage Technologies, Applications, and Analysis Methodology

et al. 2022

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The energy sector is nowadays facing new challenges, mainly in the form of a massive shifting towards renewable energy sources as an alternative to fossil fuels and a diffusion of the distributed generation paradigm, which involves the application of small-scale energy generation systems. In this scenario, systems adopting one or more renewable energy sources and capable of producing several forms of energy along with some useful substances, such as fresh water and hydrogen, are a particularly interesting solution. A hybrid polygeneration system based on renewable energy sources can overcome operation problems regarding energy systems where only one energy source is used (solar, wind, biomass) and allows one to use an all-in-one integrated systems in order to match the different loads of a utility. From the point of view of scientific literature, medium- and large-scale systems are the most investigated; nevertheless, more and more attention has also started to be given to small-scale layouts and applications. The growing diffusion of distributed generation applications along with the interest in multipurpose energy systems based on renewables and capable of matching different energy demands create the necessity of developing an overview on the topic of small-scale hybrid and polygeneration systems. Therefore, this paper provides a comprehensive review of the technology, operation, performance, and economical aspects of hybrid and polygeneration renewable energy systems in small-scale applications. In particular, the review presents the technologies used for energy generation from renewables and the ones that may be adopted for energy storage. A significant focus is also given to the adoption of renewable energy sources in hybrid and polygeneration systems, designs/modeling approaches and tools, and main methodologies of assessment. The review shows that investigations on the proposed topic have significant potential for expansion from the point of view of system configuration, hybridization, and applications.

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A User-Friendly Dynamic Reactor Simulator Built in Microsoft Excel

Hernández¹,

Rosas²,

Hernandez-Arrieta³

2022

Eng. Technol. Appl. Sci. Res.

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Computer plant simulation is being used in all aspects of engineering, through many simulation software packages. However, almost all of them require licenses that must be purchased by engineering colleges intending to use simulation in their teaching. As public educational institutions everywhere are facing a scarcity of economic resources, they can resort to a freeware steady-state plant simulator, however, there is no availability of reliable, free dynamic plant simulators. In addition, published experiences on developing dynamic simulators use programming languages requiring paid licenses (e.g. Matlab) and thus have limited relevancy to schools struggling to cut expenses. This article first uses a set of typical college objectives to discuss the advantages of building their own dynamic simulators, and then shows the development of a user-friendly dynamic simulator of a batch reactor constructed entirely within Microsoft Excel, which, in contrast to the programming languages used in related reports, is already widely used by universities around the world.

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Special Issue: Modeling and Simulation of Energy Systems

Cited by 3 publications

References 21 publications

A Stochastic Simulator of a Multi-Component Distillation Tower Built as an Excel Macro

A Stochastic Simulator of a Multi-Component Distillation Tower Built as an Excel Macro

Small-Scale Hybrid and Polygeneration Renewable Energy Systems: Energy Generation and Storage Technologies, Applications, and Analysis Methodology

A User-Friendly Dynamic Reactor Simulator Built in Microsoft Excel

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