Hybrid photovoltaic-thermosyphon water heating system for residential application

Chow, Tommy W. S.; He, Wei; Ji, J.

doi:10.1016/j.solener.2005.02.003

Cited by 317 publications

(91 citation statements)

References 13 publications

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“…In the dynamic model of Buzás et al [17] spatial distribution is not considered as the collector is considered as a mixed tank. Spatially distributed works that come close to this work are PV/water systems, [18][19][20] solar tunnel dryer, [21] and solar water heater. [20] This work sought to use a model-based approach to design and construct solar collectors for low and high outlet temperatures in a solar adsorption drying system for drying agricultural products and for regeneration of the adsorbent used for night drying.…”

Section: Introductionmentioning

confidence: 80%

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Distributed mathematical model supporting design and construction of solar collectors for drying

et al. 2017

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Coupled partial differential equations were developed to investigate which collector lengths are appropriate for drying and adsorbent regeneration under prevailing Ghanaian weather. Unlike approaches based on empirical data, the numerical model is more flexible. Effects of operational and design variables on outlet temperature and performance were systematically studied. Collector length and air speed affect performance indicators. Operational overall heat loss coefficient, an important characteristic of the collector, is not constant but varies during the day. With plausible physical parameters, the model describes the experimental data well. Collector lengths of 1.5 and 4.5 m suited drying and regeneration, respectively.

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Section: Introductionmentioning

confidence: 80%

“…In fact, under the assumption that the rate of heat storage in the material of the collector is small as compared with the other terms, the two heat gains [Eqs. (18) and (19)] should be equal, which provide an operational definition of the actual overall heat loss coefficient as Eq. (21).…”

Section: Solar Collector Modelingmentioning

confidence: 99%

Distributed mathematical model supporting design and construction of solar collectors for drying

et al. 2017

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“…[36] described a correlation between PV efficiency (η) and T PV given by a linear relation (η = η T,re f 1 − β T PV − T re f + γlog 10 G t ), which depends of reference temperature (T ref ), temperature coefficient (β), radiation coefficient (γ), and direct irradiance (G t ). Chow et al [37] establish a model to estimate the PV array power output (P PV ) as a function of T PV given by P PV = η AG t pτ g [1 − β(T PV − 25)] where p is a packing factor and τ g is the glazing transmissivity. Nevertheless, in practice, PV module efficiency is dependent on geographical location and its respective climatological conditions [38].…”

Section: Pv Module Performancementioning

confidence: 99%

Temperature Estimation for Photovoltaic Array Using an Adaptive Neuro Fuzzy Inference System

et al. 2017

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Abstract:Module temperature is an important parameter of photovoltaic energy systems since their performance is affected by its variation. Several cooling controllers require a precise estimation of module temperature to reduce excessive heating and power losses. In this work, an adaptive neuro fuzzy inference system technique is developed for temperature estimation of photovoltaic systems. For the learning process, experimental measurements comprising six environmental variables (temperature, irradiance, wind velocity, wind direction, relative humidity, and atmospheric pressure) and one operational variable (photovoltaic power output) were used as training parameters. The proposed predictive model comprises a zero-order Sugeno neuro fuzzy system with two generalized bell-shaped membership functions per input and 128 fuzzy rules. The model is validated with experimental information from an instrumented photovoltaic system with a fitness correlation parameter of R = 95%. The obtained results indicate that the proposed methodology provides a reliable tool for estimation of modules temperature based on environmental variables. The developed algorithm can be implemented as part of a cooling control system of photovoltaic modules to reduce the efficiency losses.

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“…Vokas et al (2006) studied a photovoltaicthermal system for domestic heating and cooling concluding that the system can cover a remarkable percentage of the domestic heating and cooling demands. Chow et al (2006) presented a photovoltaic-thermosyphon collector for residential applications with rectangular flow channels and discussed the energy performance.…”

Section: Solar Home Systemsmentioning

confidence: 99%

Photovoltaic Systems and Applications

Akarslan¹

2012

Modeling and Optimization of Renewable Energy Systems

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Hybrid photovoltaic-thermosyphon water heating system for residential application

Cited by 317 publications

References 13 publications

Distributed mathematical model supporting design and construction of solar collectors for drying

Distributed mathematical model supporting design and construction of solar collectors for drying

Temperature Estimation for Photovoltaic Array Using an Adaptive Neuro Fuzzy Inference System

Photovoltaic Systems and Applications

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