2017/04/18 by Enrica Scolari, Scolari, Enrica, Fabrizio Sossan +3
Computer Science · Energy · Engineering · #Energy Load and Power Forecasting #FOS: Electrical engineering #Photovoltaic System Optimization Techniques #Solar Radiation and Photovoltaics #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1705.04132
openalex publication_date 2017/04/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Due to the increasing proportion of distributed photovoltaic (PV) production\nin the generation mix, the knowledge of the PV generation capacity has become a\nkey factor. In this work, we propose to compute the PV plant maximum power\nstarting from the indirectly-estimated irradiance. Three estimators are\ncompared in terms of i) ability to compute the PV plant maximum power, ii)\nbandwidth and iii) robustness against measurements noise. The approaches rely\non measurements of the DC voltage, current, and cell temperature and on a model\nof the PV array. We show that the considered methods can accurately reconstruct\nthe PV maximum generation even during curtailment periods, i.e. when the\nmeasured PV power is not representative of the maximum potential of the PV\narray. Performance evaluation is carried out by using a dedicated experimental\nsetup on a 14.3 kWp rooftop PV installation. Results also proved that the\nanalyzed methods can outperform pyranometer-based estimations, with a less\ncomplex sensing system. We show how the obtained PV maximum power values can be\napplied to train time series-based solar maximum power forecasting techniques.\nThis is beneficial when the measured power values, commonly used as training,\nare not representative of the maximum PV potential.\n