Development of Efficient MPPT Algorithms with Reduced Number of Sensors for Photovoltaic Systems

Abstract

The increased energy demand and shortage of fossil reserves motivated researchers to focus on renewable energy sources and photovoltaic (PV) power generation is evolving as one of the most remarkable renewable energy sources because of its benefits like eco-friendly nature, less maintenance, and no noise. This thesis is focussed on improvement of tracking performance of maximum power point tracking (MPPT) algorithms and development of MPPT and battery charge controller algorithms with minimum number of sensors to reduce the overall cost of the PV systems.
The Efficiency of the PV system primarily depends on the operating point on the characteristic curve of the PV module. So far, a large number of MPPT algorithms have been developed to increase the efficiency of the PV system. Among the existing MPPT algorithms, perturb and observe (P&O) is most widely utilized because it is a simple and efficient tracking algorithm. However, with P&O tracking method the operating point moves away from MPP (i.e., drift phenomena) in case of an increase in insolation and this drift effect is severe in case of a rapid increase in insolation. A modified P&O technique is proposed to avoid the drift problem and its tracking performance is validated through the designed prototype.
Although P&O algorithm is efficient, but it requires both voltage and current sensors for the implementation. To improve the tracking performance as well as to reduce the cost, a single voltage-sensor-based adaptive MPPT technique employing a variable scaling factor is developed. For a systematic design of adaptive technique, a voltage reference control technique with the association of PI-controller is introduced for the implementation of input voltage-sensor-based MPPT algorithm.
The PV systems generally contain a battery, where the output voltage and current are to be measured for the implementation of battery charge controller. By sensing only the output parameters (i.e., converter output voltage (V_0) and current (I_0)), the objectives such as MPPT and battery charge controller can be achieved. The mathematical validation for the output sensor based MPPT algorithms are presented in this thesis. The tracking performance of the output parameter based MPPT algorithm for solar insolation and load variation is investigated in this thesis.
Photovoltaic module mismatching and non-uniform insolation conditions are the major drawbacks of the PV systems. The distributed maximum power point tracking (DMPPT) method is an effective solution to mitigate these drawbacks but, the DMPPT with conventional algorithms requires more number of sensors to implement. An Output voltage or current sensor based DMPPT algorithm with parallel configuration is presented in this thesis. The DMPPT together with battery charge controller is implemented by considering the battery voltage and charging current. The objectives of peak power tracking and battery charge controller are achieved with less number of sensors with the proposed method.