Monthly energy yield assessment of solar photovoltaic system under uniform irradiance and partial shaded condition

Abstract

The energy yield of an installed solar photovoltaic (PV) system depends on the environmental and climatic conditions of the location. Since an installed PV module experiences different conditions of temperature, irradiance, wind speed, solar spectrum, etc., therefore how much energy a PV module will generate in the field is not fully understood by its nameplate rating. This is because PV manufacturers rate the modules at only standard test conditions (STC) of 1000 W/m2 and 25oC. Estimating PV energy yield is of practical importance, especially from the point of view of solar project developers and end customers. Moreover, partial shading conditions which is an inevitable situation for the PV panels installed in the field can lower the energy yield. The main objective of the present work is to assess the energy yield of the photovoltaic system under uniform irradiance and partial shading condition. The work highlights the adverse impact of partial shading on energy yield. For this purpose, an experimental setup of a PV system of polycrystalline silicon of rating 135 Wp has been established in the National Institute of Solar Energy, Gurugram, India. An artificially generated scenario of inter-row or self-shading of the modules has been considered for this work. I-V data has been collected in real operating conditions to estimate the PV maximum output power at different conditions of irradiance and temperature under uniform irradiance as well as partial shading condition. Further, weather data for one complete year for the location is also obtained. Using the obtained set of data, monthly PV energy yield is estimated under uniform irradiance and inter-row partial shading condition. It is found that maximum energy is generated in March and least in July under uniform as well as considered partial shading condition. But under long-term considered partial shading condition, the monthly energy yield is reduced to more than 54% every month.