Numerical Derivative Estimation for Improving the Performance of MPPT Algorithms in Photovoltaic Systems

Since photovoltaic (PV) solar energy is one of the most promising renewable energy sources, its production is witnessing an on-going performance improvement. Increasing the efficiency is usually accomplished using maximum power point tracking (MPPT) techniques. The latter require the determination of the derivative (of order one and two) of the power with respect to the voltage in order to perform accurately. This paper suggests incorporating with MPPT methods an algorithm for numerical derivative estimation to enhance the performance of the control strategy in photovoltaic power generation systems. The proposed technique is an online polynomial interpolation adjusted by a Recursive- Least-Square (RLS) algorithm. Without increasing the complexity of the control algorithm, the suggested approach shows promising results in the presence of noise on the measurements and guarantees the correct performance for MPPT technique in both simulation and practice. The global algorithm for maximum power point tracking is validated through Matlab/Simulink and implemented on the experimental test bench of the laboratory. The estimates are compared to the conventional Euler approximation algorithm usually integrated in this application. The efficiency of tracking is highly increased without any additional sensors or calculators.