A variable step size perturb and observe algorithm for photovoltaic maximum power point tracking

Photovoltaic (PV) panels are devices that convert sun light into electrical energy and are considered to be one of the major ways of producing clean and inexhaustible renewable energy. However, these devices do not always naturally operate at maximum efficiency due to the nonlinearity of their output current-voltage characteristic which is affected by the panel temperature and irradiance. Hence, the addition of a high performance maximum-power-point tracking, MPPT, power converter interface is the key to keeping the PV system operating at the optimum power point which then gives maximum efficiency. Many MPPT power-converters and different types of control techniques have been considered in the past. This paper primarily considers the MPPT power-converter control method or algorithm. A so called perturb and observe (P&O) technique is considered in this work. This technique is widely used due to its low cost and ease of implementation. With conventional P&O algorithms using fixed iteration step-size, it is impossible to satisfy both performance requirements of fast dynamic response and good accuracy during the steady state at the same time. This is because, if the step-size is set to be big enough for a fast dynamic response, the oscillation around the maximum-power operating point will increase during the steady state leading to lost power generation, and if the step size is too small optimum generation is not quickly restored during changing operating conditions. To overcome these limitations a new adaptive P&O method with variable step size has been investigated which has been implemented using fuzzy logic control. The proposed method has been evaluated by simulation using MATLAB and compared with the conventional P&O under different insolation, or sun-light intensity, levels. The obtained results illustrate the effectiveness of the proposed technique and its ability for practical and efficient tracking of maximum power.