A model-based algorithm for maximum power point tracking of PV systems using exact analytical solution of single-diode equivalent model

• Published in: Solar energy Vol. 162; pp. 117 - 131
• Main Authors: Moshksar, Ehsan, Ghanbari, Teymoor
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.03.2018; Pergamon Press Inc
• Subjects: Algorithms; Analytical approach; Diodes; Electric potential; Environmental conditions; Gradient-based algorithm; Irradiance estimation; Irradiation; Maximum power; Model-based MPPT; Parameter estimation; Parameter identification; Photovoltaic cells; Photovoltaics; Solar cells; Solar energy; Tracking; Voltage; Irradiance estimation; Gradient-based algorithm; Parameter estimation; Analytical approach; Model-based MPPT
• ISSN: 0038-092X; 1471-1257
• DOI: 10.1016/j.solener.2017.12.054

•Adaptive technique is utilized to estimate five unknown parameters from datasheet.•MPPT algorithm is designed to find maximum power from exact single-diode PV model.•The exponential convergence and strongly concavity of P-V characteristic are stated.•Online irradiance estimation based on voltage and current measurements is considered.•The complex Lambert W-function is approximated with simple logarithmic functions. A novel model-based technique is presented for maximum power point tracking (MPPT) of photovoltaic (PV) systems. In this paper, an exact single-diode circuit model without any simplification or approximation is considered. Using datasheet information, an adaptive identification technique is utilized to find the electrical parameters uniquely and precisely. After this offline identification scheme, an estimation of solar irradiation is achieved from real-time measurements of PV voltage and current. In the next step, the gradient function of power with respect to voltage is represented from strongly concave mapping between power and voltage. Since the nonlinear gradient consists the complex Lambert W-function, a mathematical formulation is derived to approximate it with conventional logarithmic functions. Finally, a gradient update law is derived to find the unknown optimal voltage value, which results in maximum power generation for any environmental condition. The proposed approach guarantees exponential convergence with highly accurate steady-state performance.