Abstract
PV (Photovoltaic) cells have nonlinear current-voltage (I − V) and power-voltage (P − V) characteristics with a distinct maximum power point (MPP) that entirely depends on the ambient meteorological conditions (i.e. solar irradiance and temperature). Hence, to continuously extract and deliver the maximum possible power from the PV system, under given meteorological conditions, the maximum power point tracking (MPPT) control strategy needs to be formulated that continuously operates the PV system at its MPP. To achieve this goal, a hybrid nonlinear, very fast and efficient MPPT control strategy, based on the robust integral backstepping (RIB) control, is formulated in this research article. The simulation testbed comprises a standalone PV array, a non-inverting buck-boost (NIBB) DC-DC power converter, a purely resistive and a dynamic load (sound system). The proposed MPPT control scheme consists of two loops, where the first loop generates the real-time offline reference peak power voltage through an adaptive neuro-fuzzy inference system (ANFIS) network, which is then utilized in the second loop as a set-point value for generating a control signal and then forcing the PV system to be operated at this set-point by continuously adjusting the duty ratio of the power converter. This control strategy exhibits no overshoot, fast convergence, good transient response, fast rising and settling times and minimum output tracking error. The MATLAB/Simulink platform is used to test the performance of the proposed MPPT strategy against varying meteorological conditions, plant current and voltage faults and plant parametric uncertainties. To validate the superiority of the proposed control strategy, a comparative analysis of the proposed control strategy is presented with the nonlinear backstepping (B), integral backstepping controller (IB) and conventional PID and P&O based MPPT controllers.
Highlights
The estimated reference peak power voltage is used as a set-point for generating the control signal, u, and forcing the PV system to be operated at this set-point by continuously adjusting the duty ratio, d, of the power electronic interface
The second loop uses the estimated value of the maximum power point (MPP) as a set-point for the robust integral backstepping strategy to generate the control signal, u, and forcing the PV system to be operated at this set-point by continuously adjusting the duty ratio, d, of the non-inverting buck-boost (NIBB) diode that generates electricity (DC)-DC power electronic converter
The block diagram of the overall proposed control system used in this study is depicted in Fig 3 that comprises a standalone PV array, a NIBB DC-DC power converter, a resistive load, a dynamic load and an robust integral backstepping (RIB) based maximum power point tracking (MPPT) controller
Summary
Worldwide energy demand has increased exponentially. More than 70% of the globally generated electricity is supplied by the fossil fuels (namely natural gas, coal and petroleum) [1]. Several MPPT regarding articles have been reported to have focused on the online techniques, such as extremely seeking control (ESC) method [13,14,15], perturb and observe (P&O) strategy [16,17,18] and incremental conductance (IC) method [19, 20] These control schemes usually use PV current and voltage in real-time to achieve the MPP. To mitigate the stated problems of the recently proposed backstepping and integral backstepping techniques [27, 28], a hybrid nonlinear robust integral backstepping (RIB) based MPPT control strategy is formulated in this research work. The second loop uses the estimated value of the MPP as a set-point for the robust integral backstepping strategy to generate the control signal, u, and forcing the PV system to be operated at this set-point by continuously adjusting the duty ratio, d, of the NIBB DC-DC power electronic converter
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