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.
This work presents a methodology to estimate solar irradiance using Kalman filter for systems with unknown inputs, an approach more adequate to system characteristics than the standard formulation of this tool. A system with photovoltaic panel, dc-dc converter and load was modeled and simulated in order to analyze the proposed methodology in situations of clear, almost clear and cloudy sky days. The proposed estimator and an analytical method are compared with respect to the ability to compute the irradiance and tested against uncertainties in modeling parameters and noise in the voltage and current measurements of the system. The results show that, through a single sensor, the developed methodology allows to estimate and filter not only solar irradiance, but also output current of photovoltaic system and output voltage of converter. This brings benefits in reducing costs with sensors, allows real-time measurements and avoids propagating noisy measures in the management of a solar system.
Neste trabalho é apresentada uma nova formulação para o projeto de controladores ótimos quadráticos com ação integral para sistemas sujeitos a distúrbios externos não mensuráveis, que são conhecidos como entradas desconhecidas. Para isso é feita a combinação entre um regulador linear quadrático com ação integral para sistemas espaço de estados com parâmetro para distúrbios externos e um filtro de Kalman para sistemas com entradas desconhecidas. A metodologia inclui uma melhoria na resposta transitória em sistemas com ação integral. Os resultados de simulações realizadas mostram que o método é capaz de reduzir o erro entre referência e resposta do sistema e rejeitar de distúrbios de uma maneira mais eficaz que a formulação clássica.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.