In a car under summer solar radiation, the surface and air temperatures become very high, for example the air temperature around driver's seat was over 65 degree C. Thus, a ventilation system is one of the important methods for keeping comfortable thermal environment. In this study, in order to clarify the effect of temperature reduction in a car cabin by changing ventilation methods, the numerical simulation in a car cabin were conducted. In the case of ventilation flow rate of 100 m3/h, it was found that the effects of air temperature reduction around driver's head with FACE-CLR mode ventilation and on driver's seat with FACE-DP mode ventilation were better than FACE mode ventilation. Moreover it was found that the effects of air temperature reduction around driver's head and around rear seat with FACE-CLR+DP mode ventilation were better than FACE mode ventilation.
Based on the database (ver-1, ver-2) of a spectral irradiance for all weather conditions, which was released by the New Energy and Industrial Technology Development Organization (NEDO), the solar spectral irradiance from the relation among spectral irradiance, global irradiance, sunshine ratio, solar altitude and precipitation was investigated. The data were recorded from sunrise to sunset, at each time interval of 10 minute JST. These data were divided by an one-hour datum, as average of the seven original data by per one hour. By mean of normalized spectral irradiance the peak energy of the solar spectral irradiance, it can made of expect global solar irradiance and weather conditions on solar spectral irradiance. The normalized solar irradiance of stable fine day was defined as a standard normalized spectral irradiance (HYst). By this additional method, it was cleared that the correlation between the global solar radiation and the peak energy of solar spectral irradiance.
To attain 80% reduction of CO2 emission from fossil energy consumption (FEC) of the year 2013 (19.339 EJ) in 2050, the FEC must be less than 3.868 EJ in 2050. Assuming the following three paradigm shifts (PS), 1) reduction of energy demand of all energy consuming sections (including the loss of material production processes but except the energy used for materials themselves) to 70% of those of 2013 in 2050, 2) electrification of all of the transportation, and 3) introduction of CO2 non-emitting electricity generation that is equivalent to 1000 GW photovoltaic power plant (PVPP), and the expected population reduction to 80% of that in 2013, the energy demand of Japan in 2050 still exceed 1.818 EJ from the energy supply of FEC (3.868 EJ) added to the energy from the PVPP (3.600 EJ). The fourth PS, substitution of part of iron and cement mainly used for construction by 16 million tons of cutting edge woody biomass materials such as cross laminated timber (CLT) that could be used for mid-to-high rise buildings, could reduce another 0.845 EJ for materials leaving 0.973 EJ of energy demand that should be supplied by non fossil energy or eliminated by carbon capture and carbon fixing technologies in the future.
One method for the maintenance and inspection of photovoltaic power generation systems is to confirm the shape change of their I-V characteristics. In this study, we propose a method to represent the shape of the I-V characteristic by FF and determine the shape change based on the numerical value of FF. The determination condition of the shape change is derived based on the relationship between FF, irradiance, and module temperature, and the data outside this condition are eliminated. The determination condition is derived again from the remaining data, and the data outside this condition are eliminated. This is repeated until there are no data outside the determination condition. The eliminated data are considered to exhibit a shape change. By applying this method to mega photovoltaic systems, it is possible to determine the shape change of their I-V characteristics.
For photovoltaic power generation prediction, it is necessary to calculate a cloud shadow vector before the arrival of a cloud shadow. The cloud shadow vector is calculated based on the difference of timing for the signal intensity changes of solar radiation sensors arranged on the ground. In this study, signal intensity changes and cloud shadow shapes are measured using some solar radiation sensors and a camera, and the change patterns of the sensor signals are analyzed. The determination value of the sensor signal for the shadow-in and shadow-out of a cloud is proposed based on the change pattern of the signals. The change patterns of sensor signals were categorized into three types. The calculation accuracy of the cloud shadow vector improved by using the 5-min moving-average value of measured solar radiation intensity as the determination value for the shadow-in and shadow-out of a cloud compared with the theoretical solar radiation intensity.