A Parametric Study of a Solar-Assisted House Heating System with a Seasonal Underground Thermal Energy Storage Tank

Nhut, Le Minh; Raza, Waseem; Park, Youn Cheol

doi:10.3390/su12208686

Cited by 6 publications

(4 citation statements)

References 38 publications

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“…An interesting study [18] looked at the impact of the consumer behavior on the performance of a solar thermal system in South Africa and showed how little behavioral changes can bring significant efficiency improvements. A paper by Nhut [19], who carried out a systemic parametric study of a solar-assisted house heating system with a seasonal underground thermal energy storage tank, looked at system parameters, such as the size of the tank and the insulation thickness of the tank, in terms of annual energy production. Another system parametric study [20] looks at a solar-heating-and-cooling system for a detached single-family household in hot climates in terms of cost savings.…”

Section: = [1 − ( − )]mentioning

confidence: 99%

A Parametric Study of a Hybrid Photovoltaic Thermal (PVT) System Coupled with a Domestic Hot Water (DHW) Storage Tank

2020

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Photovoltaic-thermal panels are hybrid systems that combine the two types of conventional solar energy technologies (photovoltaic and thermal panels) and simultaneously generate both thermal and electrical energy in a micro-cogeneration system. Like any co-generation system, there is an optimal balance that can be achieved between the thermal and electrical energy produced. For this reason, it is important to establish the relationship and inter-connection between the two. Limited research is available on the cogeneration interaction in a PVT system, so the novelty of this article lies in the consideration of the entire energy system connected to the PVT panel, including the storage tank and the consumer demand curve, and the investigation of the thermal parametric variation. This study analyses the impact of the variation of some thermal parameters of a domestic hot water tank on the electrical efficiency of a photovoltaic-thermal panel. A model of a system of photovoltaic-thermal panels is built in a transient systems simulation program (TRNSYS) and a one-factor-at-a-time analysis is carried out for the cold-water main temperature, tank size, tank outlet flow and consumer demand curve. The results show that the variation of the outlet flow to the consumer has the highest impact on the electrical efficiency, of about 6.8%. The next highest impact factor is the size of the tank with a variation of 4.7%. Matching the profile of the consumer is also an important aspect. It was observed that the peak electrical efficiency occurs during peak consumer demand. Finally, the instantaneous variation of the thermal and electrical power of the system was analysed as a function of the temperature at the inlet of the photovoltaic-thermal panel.

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Section: = [1 − ( − )]mentioning

confidence: 99%

A Parametric Study of a Hybrid Photovoltaic Thermal (PVT) System Coupled with a Domestic Hot Water (DHW) Storage Tank

2020

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“…The importance of using renewable energy sources holds a unique position in the realm of contemporary technological development 1 . The utilization of solar power represents a highly promising opportunity for the production of energy in the near future, primarily due to its capacity to serve as a renewable natural energy source, which ranks among the largest of such sources in the world and can be harnessed for distribution beyond the demands of local consumption 2 , 3 . It does not require additional costs; it is clean and does not pose a risk of contamination.…”

Section: Introductionmentioning

confidence: 99%

A stacking ensemble classifier-based machine learning model for classifying pollution sources on photovoltaic panels

Byun

Jeong

2023

Sci Rep

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Solar energy is a very efficient alternative for generating clean electric energy. However, pollution on the surface of solar panels reduces solar radiation, increases surface transmittance, and raises the surface temperature. All these factors cause photovoltaic (PV) panels to be less efficient. To address this problem, a stacking ensemble classifier-based machine learning model is proposed. In this study, different sources of pollution on each solar panel are used, and their power generation is recorded. The proposed model includes gradient boost, extra tree, and random forest classifiers, with the extra tree classifier serving as a meta-learner. The model takes into account various weather features during the training process, including irradiance and temperature, aiming to increase its accuracy and robustness in identifying pollution sources on the PV panel. Moreover, the proposed model is evaluated using various methods in order to examine performance metrics such as accuracy, F1 score, and precision. Results show that the model can achieve an accuracy score of 97.37%. The model’s performance is also compared to state-of-the-art machine learning models, demonstrating its superiority in accurately classifying pollution sources on PV panels. By utilizing different sources of pollution and weather features during training, the model can accurately classify different pollution sources, resulting in increased power generation efficiency and the longevity of PV panels. The main results of this study can be used to manage and maintain PV panels since the model can identify PV modules that need to be cleaned to keep producing the most power. Furthermore, the efficiency, reliability, and sustainability of PV panels can be further enhanced by the proposed model.

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“…There are also some economy and feasibility studies conducted for TESS and ESS systems [16]; [17]; [18]; [19], which are concerned with the operating and investment costs of such systems.…”

Section: Introductionmentioning

confidence: 99%

Simulation and modeling of a solar-aided underground energy storage system

2023

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The significance of energy storage methods and related R&D studies are increasing due to the depletion of fossil fuels, rising energy prices, and growing environmental concerns. Storage of energy means elimination of practical concerns for the time difference between the time when the energy is produced and when it?s needed. The importance of producing and storing energy through renewable sources is increasing every day, especially in developing countries like T?rkiye, as such countries would like to reduce their dependence on foreign sources. This study focuses on an UTES (Underground Thermal Energy Storage) system that was modeled for Van Region, using M-file program. The performance of an isolated day heat system as a TES was investigated, and the thermal energy storage capacity of the system was researched for a 5x5x5 m soil area located on the Van Yuzuncu Yil University Campus. The temperature distribution, heat loss, and efficiency calculations were performed for a complete year and 3D representations of the findings were obtained. The lowest efficiencies were observed in May, while the highest efficiencies were observed in July. It was found that the maximum heat loss from the system took place during December and January, and the system could be easily and effectively become a heating source for a single household with the addition of a heat pump.

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A Parametric Study of a Solar-Assisted House Heating System with a Seasonal Underground Thermal Energy Storage Tank

Cited by 6 publications

References 38 publications

A Parametric Study of a Hybrid Photovoltaic Thermal (PVT) System Coupled with a Domestic Hot Water (DHW) Storage Tank

A Parametric Study of a Hybrid Photovoltaic Thermal (PVT) System Coupled with a Domestic Hot Water (DHW) Storage Tank

A stacking ensemble classifier-based machine learning model for classifying pollution sources on photovoltaic panels

Simulation and modeling of a solar-aided underground energy storage system

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