4.6 Article

Numerical simulation of underground Seasonal Solar Thermal Energy Storage (SSTES) for a single family dwelling using TRNSYS

期刊

SOLAR ENERGY
卷 86, 期 1, 页码 289-300

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.solener.2011.10.002

关键词

Seasonal Solar Thermal Energy Storage; TRNSYS; Solar heating

资金

  1. US Department of Education

向作者/读者索取更多资源

A system for capturing and storing solar energy during the summer for use during the following winter has been simulated. Specifically, flat plate solar thermal collectors attached to the roof of a single family dwelling were used to collect solar thermal energy year round. The thermal energy was then stored in an underground fabricated Seasonal Solar Thermal Energy Storage (SSTES) bed. The SSTES bed allowed for the collected energy to supplement or replace fossil fuel supplied space heat in typical single family homes in Richmond, Virginia, USA. TRNSYS was used to model and simulate the winter thermal load of a typical Richmond home. The simulated heating load was found to be comparable to reported loads for various home designs. TRNSYS was then used to simulate the energy gain from solar thermal collectors and stored in an underground, insulated, vapor proof SSTES bed filled with sand. Combining the simulation of the winter heat demand of typical homes and the SSTES system showed reductions in fossil fuel supplied space heating in excess of 64%. The optimization of the SSTES scheme showed that a 15 m(3) bed volume, 90% of the south facing roof, and a flow rate of 11.356 lpm through the solar collectors were optimal parameters. The overall efficiency of the system ranged from 50% to 70% when compared to the total useful energy gain of the solar collectors. The overall efficiency was between 6.1% and 7.6% when compared to the total amount of solar radiation incident upon the solar collectors. (C) 2011 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Physics, Applied

Schottky diodes from 2D germanane

Nanda Gopal Sahoo, Richard J. Esteves, Vinay Deep Punetha, Dmitry Pestov, Indika U. Arachchige, James T. McLeskey

APPLIED PHYSICS LETTERS (2016)

Article Computer Science, Artificial Intelligence

Comparison of genetic algorithm to particle swarm for constrained simulation-based optimization of a geothermal power plant

Joshua Clarke, Laura McLay, James T. McLeskey

ADVANCED ENGINEERING INFORMATICS (2014)

Article Engineering, Chemical

Characterization of Nanoaerosol Size Change During Enhanced Condensational Growth

P. Worth Longest, James T. McLeskey, Michael Hindle

AEROSOL SCIENCE AND TECHNOLOGY (2010)

Article Chemistry, Physical

Electrospray aerosol deposition of water soluble polymer thin films

Marshall L. Sweet, Dmitry Pestov, Gary C. Tepper, James T. McLeskey

APPLIED SURFACE SCIENCE (2014)

Article Construction & Building Technology

Modeling seasonal solar thermal energy storage in a large urban residential building using TRNSYS 16

L. T. Terziotti, M. L. Sweet, J. T. McLeskey

ENERGY AND BUILDINGS (2012)

Article Energy & Fuels

The constrained design space of double-flash geothermal power plants

Joshua Clarke, James T. McLeskey

GEOTHERMICS (2014)

Article Chemistry, Physical

Origin of Red Shift in the Photoabsorption Peak in MEH-PPV Polymer

Santanab Giri, Corell H. Moore, James T. Mcleskey, Puru Jena

JOURNAL OF PHYSICAL CHEMISTRY C (2014)

Article Nanoscience & Nanotechnology

ZnO Nanowires Synthesized by Vapor Phase Transport Deposition on Transparent Oxide Substrates

Dongshan Yu, Tarek Trad, James T. McLeskey, Valentin Craciun, Curtis R. Taylor

NANOSCALE RESEARCH LETTERS (2010)

Article Energy & Fuels

Co-planar bi-metallic interdigitated electrode substrate for spin-coated organic solar cells

Shinobu Nagata, Gary M. Atkinson, Dmitry Pestov, Gary C. Tepper, James T. McLeskey

SOLAR ENERGY MATERIALS AND SOLAR CELLS (2011)

Article Materials Science, Multidisciplinary

Electrospun Polymer-Fiber Solar Cell

Shinobu Nagata, Gary M. Atkinson, Dmitry Pestov, Gary C. Tepper, James T. Mcleskey

ADVANCES IN MATERIALS SCIENCE AND ENGINEERING (2013)

Article Materials Science, Multidisciplinary

Activated carbon-doped polystyrene fibers for direct contact membrane desalination

Richard J. Alan Esteves, Veronica Gornick, Dea Santi Alqurwani, Joshua Koenig-Lovejoy, Haneen Abdelrazeq, Majeda Khraisheh, Anna Forzano, Mohamed Gad-el-Hak, Hooman Vahedi Tafreshi, James T. McLeskey

EMERGENT MATERIALS (2020)

Article Energy & Fuels

A passive house with seasonal solar energy store: in situ data and numerical modelling

Joshua Clarke, Shane Colclough, Philip Griffiths, James T. McLeskey

INTERNATIONAL JOURNAL OF AMBIENT ENERGY (2014)

Article Education, Scientific Disciplines

Curriculum Development for a Nuclear Track in Mechanical Engineering

John E. Speich, James T. Mcleskey, Mohamed Gad-El-Hak

INTERNATIONAL JOURNAL OF ENGINEERING EDUCATION (2010)

Article Energy & Fuels

Machine learning-aided discovery of bismuth-based transition metal oxide double perovskites for solar cell applications

Siddharth Sradhasagar, Omkar Subhasish Khuntia, Srikanta Biswal, Sougat Purohit, Amritendu Roy

Summary: In this study, machine learning models were developed to predict the bandgap and its character of double perovskite materials, with LGBMRegressor and XGBClassifier models identified as the best predictors. These models were further employed to predict the bandgap of novel bismuth-based transition metal oxide double perovskites, showing high accuracy, especially in the range of 1.2-1.8 eV.

SOLAR ENERGY (2024)

Article Energy & Fuels

Multi-objective optimizations of solar receiver based on deep learning strategy in different application scenarios

Wei Shuai, Haoran Xu, Baoyang Luo, Yihui Huang, Dong Chen, Peiwang Zhu, Gang Xiao

Summary: In this study, a hybrid model based on numerical simulation and deep learning is proposed for the optimization and operation of solar receivers. By applying the model to different application scenarios and considering multiple performance objectives, small errors are achieved and optimal structure parameters and heliostat scales are identified. This approach is not only applicable to gas turbines but also heating systems.

SOLAR ENERGY (2024)

Article Energy & Fuels

An accurate prediction of electronic structure, mechanical stability and optical response of BaCuF3 fluoroperovskite for solar cell application

Mubashar Ali, Zunaira Bibi, M. W. Younis, Muhammad Mubashir, Muqaddas Iqbal, Muhammad Usman Ali, Muhammad Asif Iqbal

Summary: This study investigates the structural, mechanical, and optoelectronic properties of the BaCuF3 fluoroperovskite using the first-principles modelling approach. The stability and characteristics of different cubic structures of BaCuF3 are evaluated, and the alpha-BaCuF3 and beta-BaCuF3 compounds are found to be mechanically stable with favorable optical properties for solar cells and high-frequency UV applications.

SOLAR ENERGY (2024)

Article Energy & Fuels

Efficient laboratory perovskite solar cell recycling with a one-step chemical treatment and recovery of ITO-coated glass substrates

Dong Le Khac, Shahariar Chowdhury, Asmaa Soheil Najm, Montri Luengchavanon, Araa mebdir Holi, Mohammad Shah Jamal, Chin Hua Chia, Kuaanan Techato, Vidhya Selvanathan

Summary: A novel recycling system is proposed in this study to decompose and reclaim the constituent materials of organic-inorganic perovskite solar cells (PSCs). By utilizing a one-step solution process extraction approach, the chemical composition of each layer is successfully preserved, enabling their potential reuse. The proposed recycling technique helps mitigate pollution risks, minimize waste generation, and reduce recycling costs.

SOLAR ENERGY (2024)

Article Energy & Fuels

A compound fault diagnosis model for photovoltaic array based on 1D VoVNet-SVDD by considering unknown faults

Peijie Lin, Feng Guo, Xiaoyang Lu, Qianying Zheng, Shuying Cheng, Yaohai Lin, Zhicong Chen, Lijun Wu, Zhuang Qian

Summary: This paper proposes an open-set fault diagnosis model for PV arrays based on 1D VoVNet-SVDD. The model accurately diagnoses various types of faults and is capable of identifying unknown fault types.

SOLAR ENERGY (2024)