Irradiance Estimation Using Kalman Filter for State-space Systems with Unknown Inputs

This work presents a method for solar irradiance estimation based on Kalman filter for systems subject to unknown inputs. A system composed of a photovoltaic panel, a dc-dc converter and a load was modeled as state space subject to unknown input. The results of the simulated case studies presents a normalized root mean square error (nRMSE) between 0.93% and 14.23% for irradiance estimates, the latter value corresponding to a case that considers adverse situations in applications. In addition, the proposed methodology also estimates the output voltage (nRMSE between 5.66% and 13.15%) and output current (nRMSE between 0.65% and 12.46%) of photovoltaic panels. All these estimates are based on the measurement of a single voltage sensor at the dc-dc converter output. Thus, the KFUI based irradiance estimation is a low cost alternative to the use of pyranometers and has good perspectives for new works on filtering and control of photovoltaic systems.