Exploring dynamic operation of a solar dish-stirling engine: Validation and implementation of a novel TRNSYS type

Bidhendi, Mohammad Vahidi; Abbassi, Yasser

doi:10.1016/j.seta.2020.100765

Cited by 11 publications

(3 citation statements)

References 37 publications

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“…Each Fortran subroutine is called a 'Type' and contains the model for a single system component. Several studies have been carried out in order to validate the numerical models developed in TRNSYS from the Colorado State University experimental houses and other researchers around the world [55][56][57][58]. In this study, the following main TRNSYS Types [31,[59][60][61] At first, the Type 56 subroutine has been used to model the thermal behavior of the Gemini test cells; in particular, two thermal zones have been modeled, one for each test cell.…”

Section: Description Of the Numerical Modelmentioning

confidence: 99%

Energy Performances Assessment of Extruded and 3D Printed Polymers Integrated into Building Envelopes for a South Italian Case Study

et al. 2021

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Plastic materials are increasingly becoming used in the building envelope, despite a lack of investigation on their effects. In this work, an extruded Acrylonitrile-Butadiene-Styrene panel has been tested as a second-skin layer in a ventilated facade system using a full-scale facility. The experimental results show that it is possible to achieve performances very similar to conventional materials. A numerical model has then been developed and used to investigate the performances of plastic and composite polymer panels as second-skin layers. The experimental data has been used to verify the behavior of the numerical model, from a thermal point of view, showing good reliability, with a root mean square error lower than 0.40 °C. This model has then been applied in different refurbishment cases upon varying: the polymer and the manufacturing technology (extruded or 3D-printed panels). Eight refurbishment case studies have been carried out on a typical office building located in Napoli (Italy), by means of a dynamic simulation software. The simulation results show that the proposed actions allow the reduction of the thermal and cooling energy demand (up to 6.9% and 3.1%, respectively), as well as the non-renewable primary energy consumption (up to 2.6%), in comparison to the reference case study.

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Section: Description Of the Numerical Modelmentioning

confidence: 99%

Energy Performances Assessment of Extruded and 3D Printed Polymers Integrated into Building Envelopes for a South Italian Case Study

et al. 2021

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“…The research conducted by Bidhendi et al [9] explore solar dish/Stirling engine system under different climates and operating conditions. They used TRNSYS© to estimate the impact of irradiation flux and ambient temperature on the daily, monthly and seasonal performance of the solar dish-Stirling engine system.…”

Section: Introductionmentioning

confidence: 99%

Thermal Behaviour of a Solar Dish Collector with Flat Mirrors Using CFD Analysis

Cucumo¹,

Ferraro²,

Kaliakatsos³

et al. 2020

IJHT

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In this work a Solar Thermal Generator is analysed from an energy point of view. It is a dish collector that is part of a concentrating solar grid system. The analysed plant is used for the generation of low enthalpy thermal energy as an integration to the hot water production plant for some student residences of the University of Calabria (Italy). A thermal model is developed that simulates the behaviour of the plant with the aim of analysing its performance and optimizing the design of its fundamental parts from an energy point of view. The optical model of the solar collector is carried out for a particular external condition. The emissive characteristics of the absorber is determined with the use of a thermal imaging camera. To identify the main parameters that affect the functioning and the thermal balance of the capturing system, a thermo-fluid dynamic analysis is performed. The results show which are the main causes of loss. It is possible to understand the weight of each factor in the energy balance.

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“…The numerical models investigated are based on a collection of experimental data obtained from the real operation of a prototype dish-Stirling solar concentrator installed at the campus of the University of Palermo. The direct availability of such data, in the case of the aforementioned technology, is not common, and several previous studies were exclusively theoretical, such as [29][30][31][32]. Furthermore, in the case of the application of artificial intelligence techniques, sometimes the data used are mainly obtained from other analytical or numerical models and not from experimental measurement campaigns [24]; • One of the most important characteristics of the following research is that the tools that are used to develop the proposed models are explicitly stated and belong to the category of open-source software (Python and TensorFlow), ensuring the absolute replicability of the algorithms by the scientific community.…”

mentioning

confidence: 99%

Development of Neural Network Prediction Models for the Energy Producibility of a Parabolic Dish: A Comparison with the Analytical Approach

et al. 2022

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Solar energy is one of the most widely exploited renewable/sustainable resources for electricity generation, with photovoltaic and concentrating solar power technologies at the forefront of research. This study focuses on the development of a neural network prediction model aimed at assessing the energy producibility of dish–Stirling systems, testing the methodology and offering a useful tool to support the design and sizing phases of the system at different installation sites. Employing the open-source platform TensorFlow, two different classes of feedforward neural networks were developed and validated (multilayer perceptron and radial basis function). The absolute novelty of this approach is the use of real data for the training phase and not predictions coming from another analytical/numerical model. Several neural networks were investigated by varying the level of depth, the number of neurons, and the computing resources involved for two different sets of input variables. The best of all the tested neural networks resulted in a coefficient of determination of 0.98 by comparing the predicted electrical output power values with those measured experimentally. The results confirmed the high reliability of the neural models, and the use of only open-source IT tools guarantees maximum transparency and replicability of the models.

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Exploring dynamic operation of a solar dish-stirling engine: Validation and implementation of a novel TRNSYS type

Cited by 11 publications

References 37 publications

Energy Performances Assessment of Extruded and 3D Printed Polymers Integrated into Building Envelopes for a South Italian Case Study

Energy Performances Assessment of Extruded and 3D Printed Polymers Integrated into Building Envelopes for a South Italian Case Study

Thermal Behaviour of a Solar Dish Collector with Flat Mirrors Using CFD Analysis

Development of Neural Network Prediction Models for the Energy Producibility of a Parabolic Dish: A Comparison with the Analytical Approach

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