Cooling effect and heat index (HI) assessment on car cabin cooler powered by solar panel in parked car

With the rapid development of social economy, China's energy demand has been growing at an alarming rate. The annual cumulative power generation is about &#160;6.8 trillion kilowatts hour in 2017, and 70% of them is provided by fossil fuel resources, so it is important to promote the use of renewable and clean energy, such as solar power generation technology. The advantages of using solar panel roof in urban areas include reduction of the need of land use in the crowed city and less dependence on fossil fuels. However, there is need to understand impacts of solar roof on local climate, on energy supply during heatwaves, and associated economic benefits in China. This study selected a heatwave event in Jiangsu province, China to simulate the impact of solar panel roof on local thermal environment and energy supply. During that time, the cooling energy consumption reached more than half of the total electricity consumption. A new heat transfer scheme of solar panel roof was introduced into WRF/BEP/BEM model, which include layers (glass protective panel, solar panel, bottom plate) and was divided into two types for heat transfer calculation: bracket and non-bracket. The results showed that the urban average 2-m daytime temperature decreased by 0.3&#8451; in non-bracket case which is better than that of bracket case, while its cooling effect on nighttime temperature was small. For the bracket case, its cooling effect on daytime and nighttime air temperature were equal (0.2oC). Both solar panel roofs can reduce indoor daytime air temperature with the maximum cooling effect around 11:00 local time for non-bracket roof and 14:00 for bracket roof. However, bracket roof increased nighttime indoor air temperature and air-conditioning energy consumption. Solar panel roofs also reduce daytime turbulent kinetic energy and constrain the development of boundary layer. Results also show that with solar photoelectric conversion efficiency being 0.14, the photovoltaic power generation can meet 84.1%, 61.3% and 35.9% of the cooling energy consumption for high-density, low-density residential areas and commercial areas, respectively, during this heatwave event.

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Mitigating the warming in urban areas: Experimental study of different roof materials in a subtropical monsoon climate

10.5194/egusphere-egu2020-9117 ◽

2020 ◽

Author(s):

Xing Chen ◽

Sujong Jeong

Keyword(s):

Surface Temperature ◽

Urban Areas ◽

Field Experiments ◽

Solar Panel ◽

Urban Atmosphere ◽

Cooling Effect ◽

Monsoon Climate ◽

Urban Heat ◽

Cooling Effects ◽

Subtropical Monsoon Climate

Different roof materials are deployed for mitigating the urban heat, which significantly affects our life. However, the performance of specific roof materials could be influenced by the background climate. To evaluate the effectiveness of roof materials on temperature reductions in a subtropical monsoon climate region, this study performs field experiments using four different roof materials (gray and white surfaces, solar panel, and grass surface) from December 2017 to July 2018. The results show that the white surface reduced the average daily surface temperature by 3.37 &#176;C. This cooling effect increased with the increase in surface albedo and incoming solar radiation. However, the average cooling effect of the grass surface was much lower (0.43 &#176;C). This is attributable to the low soil moisture, which was influenced by the monsoon, thereby indicating that irrigation is required to improve the thermal performance of grass roofs even in humid regions. The solar panel reduced the daily surface temperature by 0.59 &#176;C but exerted strong warming (7.36 &#176;C) during midday and cooling effects (4.03 &#176;C) during midnight because of its low albedo, low emissivity, and low heat capacity. Our results suggest that, for the roof treatments explored here, white roofs are more effective for mitigating urban heat in a subtropical monsoon climate under the present climatic conditions and especially for drier climates predicted for the future, while grass roofs are not a sustainable method as they require irrigation to achieve a cooling effect and solar panels may heat the urban atmosphere.

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Solar Panel Performance Improvement using Heatsink Fan as the Cooling Effect

Journal of Physics Conference Series ◽

10.1088/1742-6596/1167/1/012031 ◽

2019 ◽

Vol 1167 ◽

pp. 012031

Author(s):

Efsilon K A Fatoni ◽

Ahmad Taqwa ◽

Rd Kusumanto

Keyword(s):

Performance Improvement ◽

Solar Panel ◽

Cooling Effect

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Irrigation cooling effect on temperature and heat index extremes

Geophysical Research Letters ◽

10.1029/2008gl034145 ◽

2008 ◽

Vol 35 (9) ◽

Cited By ~ 71

Author(s):

David B. Lobell ◽

Celine J. Bonfils ◽

Lara M. Kueppers ◽

Mark A. Snyder

Keyword(s):

Cooling Effect ◽

Heat Index

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Stochastic simulation of the spatio-temporal field of the average daily heat index in Southern Russia

Climate Research ◽

10.3354/cr01623 ◽

2020 ◽

Vol 82 ◽

pp. 149-160

Author(s):

N Kargapolova

Keyword(s):

Heat Waves ◽

Numerical Models ◽

Heat Index ◽

Real Field ◽

Gaussian Field ◽

The Real ◽

Southern Russia ◽

Weather Stations ◽

Spatio Temporal ◽

Temporal Field

Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.

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