Since the search of the energy source considered as one of the main problems in this era, then it will be still one of the most important concerns of the countries. The renewable energy became one of the faster-growing trends in industrial societies since it becomes used for solving shortfall problem in the energy source. In the meantime, the sun is responsible for almost all the energy available on the earth. Photovoltaic systems, which gets the energy from the sun and convert it to electrical energy is one of the best solutions to solve the shortage problems. In this system, there is one point called Maximum Power Point (MPP) representing the maximum output power that can be generated from the system, but the system will be disturbed by changing the environment factors like irradiance and temperature. Therefore, the changing of environment factors will effect on the value of MPP, and make the system back to a maximum value by using the tracking methods. It is called Maximum Power Point Tracking Method (MPPT). There are many methods in this field with a different performance because this variation leads to confusion in the selection of the suitable Maximum Power Point Tracking Methods. This research has reviewed many types of tracking methods and classified them according to the accuracy, tracking speed, and complexity, by considering the Perturbation and Observation (PO) and Incremental Conductance (IC) methods being as the most commonly methods in order to choose the most suitable maximum tracking method to be applied in Malaysia. The modeling technique has been made and tested to compare between these two methods. This model uses the irradiation and temperature as inputs parameters to give a performance indication between the variations of output power with respect to time. MATLAB have been used in this research. The result shows better time response and smooths performance while applying Incremental Conductance (IC) method than Perturbation and Observation (PO) for Malaysia. Towards completion of this project, the project aimed to create a comparative model, for the two selected methods. The project other aims included adding the time response and stability factors while testing the two methods using the models based on the inputs from different states in Malaysia. When using the model for Malaysian data and taking the average irradiance and temperature for the two proposed methods, it is recommended to use the INC method, which shows faster response and better stability.
