Errors-in-Variables Model for Photovoltaic Cell

The contribution of solar energy to the world's total energy supply has grown significantly. Energy from the sun is the most abundant and freely available energy on the planet. So, the importance of modelling the photovoltaic cell also increased remarkably. Many models for photovoltaic cell had been proposed since the beginning of the solar energy exploitation. Electronic equivalent circuit models, First-principles models and Empirical models are the different modelling techniques used for a PV cell. In Electronic equivalent circuit modelling, the equivalent model of the PV cell is developed using electronic components. The First-principles modelling technique is purely theoretical modelling. This model is designed from the basic laws of physics and chemistry. An empirical model is developed by implementing a relationship between the input and output of the system. Its main advantage is that it doesnâ€™t consider any internal state or characteristics of the system. It is also known as Data-driven modelling or System identification. Presently available empirical models are classical models. Such models consider errors only in the output. But in the case of PV cells, the input is also known with errors. So, the proposed model considered errors in both input and output. Such models are called Errors-in-Variables (EIV) model. Dynamic Iterative Principal Component Analysis (DIPCA) is used for modelling. By using DIPCA, the order of process and error covariance can also be calculated. Keywords - Iterative, Empirical, EIV, DIPCA.