Comparative Study Of Maximum Power Point Tracking Algorithm Based On Bias Adjustment

In order to improve the efficiency and reduce the cost of photovoltaic powergeneration, maximum power point tracking (MPPT) has become the hot spot of researchscholars. MPPT algorithm ensures maximum power output of photovoltaic cells. Atpresent,a variety of algorithms has been proposed. Perturb and observe method is thewidely used method. In this paper, the perturb and observe algorithm is selected as thecomparison object, and on the basis of the equivalent impedance method (EIM), a doubleloop control algorithm of EIM is put forward. The algorithm’s dependence on theparameters of the converter is greatly reduced, and the tracking speed and steady stateaccuracy of the system is significantly improved.Firstly, the traditional perturb and observe method is analyzed in detail. Thetheoretical basis for the selection of control parameters is proposed, the control algorithmis optimized. And the tracking characteristics of the voltage perturb method and the dutycycle perturb method are compared and analyzed.Secondly, based on single loop control of EIM, a double loop control algorithm ofEIM with a internal voltage loop is proposed. In the voltage loop design, the small-signaltransfer function of duty cycle to converter input voltage is established, the design methodof the regulator is given. A double loop control algorithm of EIM is obtained after addingimpedance loop. Compared with the perturb and observe algorithm, the new algorithm’sdynamic characteristics and steady state characteristics have been greatly improved.Finally, a experimental platform of maximum power point tracking system isdesigned. The different maximum power tracking algorithms are compared in experiments.Compared with the conventional algorithms, the double-loop EIM control algorithm hashigher tracking speed and steady precision.