Spatial Average Irradiance Fluctuation Characteristics in Chubu Region Considering Smoothing Effect around Observation Points

Usability of AMeDAS Sunshine Duration Data for Statistical Evaluation of Spatial Average Irradiance Fluctuation Characteristics

“…Each AMeDAS point is associated with the daily relative sunlight duration and daily average air temperature, needed for the evaluation of insolation from sunlight duration (explained below), as well as the altitude above sea level, needed for air mass calculation . In addition, as shown in the diagram, the areas represented by all the AMeDAS points are defined by Voronoi tessellation using perpendicular bisectors between adjacent points .…”

“…We calculated 1‐min spatial average irradiance fluctuation values using the total solar irradiance observed in 1 s sampling at 61 locations in the Chubu region, shown in Fig. . In this investigation, we used spatial average irradiance fluctuation characteristics calculated in the same period (September 1, 2010 to August 31, 2011) for comparison with the fluctuation characteristics estimated from the AMeDAS sunlight duration.…”

“…In this investigation, we used spatial average irradiance fluctuation characteristics calculated in the same period (September 1, 2010 to August 31, 2011) for comparison with the fluctuation characteristics estimated from the AMeDAS sunlight duration. In the previous investigation , the areas represented by every point were defined by Voronoi tessellation as shown in Fig. , and a low‐pass filter (LPF) whose gain depended on the area size was applied to express the smoothing effect of insolation fluctuations around every point .…”

“…Thus, in this investigation we attempt to achieve higher accuracy in estimating the characteristics of spatial average irradiance fluctuations by using a modification of the previous method ; in addition, we try to verify the effectiveness of the AMeDAS sunlight duration data for evaluation of the daily maximum fluctuation width (MFW) with a 120‐min window by comparison with the characteristics of spatial average irradiance fluctuations based on multipoint irradiance observations in the Chubu region .…”

Short-run fluctuation of residual load by high penetration photovoltaic power generation system

“…I(t) is the weighted average of 58 points irradiance according to the number of detached houses in the observation pointrepresentative area. The low-pass filter, of which the filter gain is determined according to the size of the observation pointrepresentative area, is applied to each observed irradiance so that the smoothing effect of irradiance fluctuation around individual observation point is taken into account [4]. This study utilizes I(t) during 8 hours (8:00 -15:59) in 378 days (Feb/2012 -May/2013) excluding the days in which the electricity demand data is not available (Apr/2012 -Jun/2012).…”