Thermal energy storage for enhanced building energy flexibility

Tunçbilek, Ekrem; Yıldız, Çağatay; Arıcı, Müslüm; Ma, Zhenjun; Awan, Muhammad Bilal

doi:10.1016/b978-0-323-99588-7.00004-3

Cited by 3 publications

(2 citation statements)

References 128 publications

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“…Moreover, it is expected that the investments in TES technologies for cooling and power applications will surge from 13 billion USD to 28 billion USD in the same period [43]. In buildings, TES can be mainly used for demand shifting and load modulation through integration with heat pumps and hot water storage systems as well as with building envelopes [44].…”

Section: Thermal Energy Storagementioning

confidence: 99%

“…The results showed that the TES system integration with the HVAC system helped reduce peak demand by 73% and provided 37.1% cost savings for the analyzed period. Tuncbilek et al [44] reviewed a number of studies involving the use of TES for enhanced flexibility of buildings and building energy systems. The review demonstrated that the use of TES can reduce overall energy consumption, operational costs, and emissions of buildings.…”

Section: Thermal Energy Storagementioning

confidence: 99%

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An Overview of Emerging and Sustainable Technologies for Increased Energy Efficiency and Carbon Emission Mitigation in Buildings

Ma,

Awan,

et al. 2023

Buildings

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The building sector accounts for a significant proportion of global energy usage and carbon dioxide emissions. It is important to explore technological advances to curtail building energy usage to support the transition to a sustainable energy future. This study provides an overview of emerging and sustainable technologies and strategies that can assist in achieving building decarbonization. The main technologies reviewed include uncertainty-based design, renewable integration in buildings, thermal energy storage, heat pump technologies, thermal energy sharing, building retrofits, demand flexibility, data-driven modeling, improved control, and grid-buildings integrated control. The review results indicated that these emerging and sustainable technologies showed great potential in reducing building operating costs and carbon footprint. The synergy among these technologies is an important area that should be explored. An appropriate combination of these technologies can help achieve grid-responsive net-zero energy buildings, which is anticipated to be one of the best options to simultaneously reduce building emissions, energy consumption, and operating costs, as well as support dynamic supply conditions of the renewable energy-powered grids. However, to unlock the full potential of these technologies, collaborative efforts between different stakeholders are needed to facilitate their integration and deployment on a larger and wider scale.

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Section: Thermal Energy Storagementioning

confidence: 99%

Section: Thermal Energy Storagementioning

confidence: 99%

An Overview of Emerging and Sustainable Technologies for Increased Energy Efficiency and Carbon Emission Mitigation in Buildings

Ma,

Awan,

et al. 2023

Buildings

Self Cite

View full text Add to dashboard Cite

show abstract

Dynamic building thermal mass clustering for energy flexibility assessment: An application to demand response events

Mugnini,

Ramallo-González,

Parreño

et al. 2024

Energy and Buildings

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A novel approach to estimate building electric power consumption based on machine learning method: toward net-zero energy, low carbon and smart buildings

Alotaibi,

Abuhussain,

Dodo

et al. 2024

International Journal of Low-Carbon Technologies

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The modern era has witnessed a surge in energy consumption and its dependence on fossil fuels, which are harmful to the environment, prompting researchers to examine techniques for regulating energy usage in buildings, specifically with regard to residential electricity consumption. The pursuit of net-zero energy consumption and low carbon emission buildings is a significant undertaking that nations across the globe are actively endeavoring to accomplish. In order to accomplish this goal, the structure in question must efficiently oversee its overall energy usage while concurrently capitalizing on sustainable energy sources. The precise estimation of future electricity usage in buildings is an essential element in the process of energy efficiency planning and optimization. The present study introduces a soft computing methodology and data decomposition as approaches for evaluating the energy usage of residential structures. An innovative machine learning approach is introduced for the purpose of estimating the initial cost required to construct a green structure that consumes no net energy. By utilizing wavelet decomposition, it is possible to determine how to transform the structure into one that is intelligent and energy efficient. Following wavelet parallel converter analysis, the data were processed with an estimator model based on an ideal neural network. The results indicate that the mean estimation errors for recurrent neural network, Autoregressive fractionally integrated moving average (ARFIMA), and gene expression programming (GEP) were reduced by 72%, 65%, and 77%, respectively, using this method. Conversely, when the proposed methodology is applied to the smart management of building energy consumption, the examined structures experience an average reduction of 8% in energy consumption. Moreover, the outcomes of CO2 gas emissions demonstrate that the suggested model possesses the capability to accurately forecast CO2 emissions. The study highlights the necessity of employing innovative techniques such as machine learning to decrease building energy usage and CO2 emissions. The discovery of these results can assist policymakers and stakeholders in the energy sector in advancing the adoption of smart building technologies.

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Thermal energy storage for enhanced building energy flexibility

Cited by 3 publications

References 128 publications

An Overview of Emerging and Sustainable Technologies for Increased Energy Efficiency and Carbon Emission Mitigation in Buildings

An Overview of Emerging and Sustainable Technologies for Increased Energy Efficiency and Carbon Emission Mitigation in Buildings

Dynamic building thermal mass clustering for energy flexibility assessment: An application to demand response events

A novel approach to estimate building electric power consumption based on machine learning method: toward net-zero energy, low carbon and smart buildings

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