Hideaki Takenaka

This study describes the estimation of solar radiation from photovoltaic (PV) power generation in smart streetlights (SSL) with a heat transfer model. The distribution of solar radiation is important for managing PV power generation. In particular, the demand for electricity for air conditioners and lighting in urban areas is large, so it is a major target for reducing greenhouse gases by introducing PV power. Solar radiation data that includes information on building shadows and reflections can be obtained by high‐density sampling in urban areas using SSL. These data, which include the three‐dimensional effects of urban structures such as buildings, can help urban planning to incorporate PV power generation. Diverse monitoring data in addition to urban canopy top solar radiation data will accelerate the introduction of PV power. The thermal state of the PV panel is an uncertain factor that links solar radiation and PV power generation. Here, we investigate an hourly constant model, a steady‐state model, and two nonsteady state models with daily and monthly intervals for predicting solar radiation from PV power generation at two locations over one winter month. Solar radiation is estimated by evaluating solar cell temperature, except for the hourly constant model. For the nonsteady‐state model, two types of heat transfer model, which consider only wind speed or both wind speed and direction for convection, are used. The model that includes wind speed and direction calculated by a Joukowski transform is effective, and the highest model accuracy is a mean absolute percentage error of less than 6.3% for the monthly average.