Integration of Solar PV With Low-Voltage Weak Grid System: Using Maximize-M Kalman Filter and Self-Tuned P&O Algorithm

This paper introduces a novel self-tuned perturb and observe (SPO) algorithm for quick maximum power point tracking (MPPT) and a novel maximize-M Kalman filter (MMKF)-based control technique for optimal operation of grid-integrated solar photovoltaic (PV) energy conversion system, where linear/nonlinear loads are attached at point of common coupling (PCC). The proposed SPO is the improved form of perturb and observe (P&O) algorithm, where inherent problems of traditional P&O such as steady-state oscillation, slow dynamic responses, and fixed step size issues, are successfully mitigated. Therefore, SPO tracks maximum power peak (MPP) very rapidly, and it very accurately extracts maximum power from the PV array. The extracted power is used to meet the active power requirement of loads, and after meeting the load demand, the excess power is supplied to the grid. During power feeding, the power quality and power management are maintained by the MMKF-based control technique. In control strategy, the MMKF is used for fundamental harmonic component extraction from the grid voltage and load current, even when the grid voltage is characterized by adverse situations, such as sag, swell, harmonic distortion, dc offset, etc. Here, the SPO MPPT algorithm and MMKF-based control techniques are tested on a developed prototype. The efficient and reliable performances of SPO MPPT algorithm and MMKF-based control algorithm, in dynamic as well as in steady-state condition, are demonstrated under insolation variation conditions, nonlinear loading, as well as in different grid disturbances such as overvoltage, undervoltage, phase imbalance, harmonics distortion in the grid voltage, etc.