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Abstract One of the main objectives of this work is to achieve optimal sizing of a stand- alone PV system to cover a load and achieving the optimal cost of the overall system. The proposed analysis is based on developing a mathematical model of the PV system includes PV array, batteries, battery chargers, controllers and inverters. Two proposed objective functions are developed; the first one is the PV module output power which is required to be maximized. Then, after the maximum power is expressed the corresponding optimal tilt angle of the module can be obtained. Two different optimization techniques are used to solve the problem; Lagrange Multiplier Algorithm and Genetic Algorithm (GA). The results of both methods are compared and show that the GA is better than Lagrange Multiplier in so.lving the concerned problem. The analysis is performed for a selected day and complete month for different types ofPV modules. So we can summarized the proposed constrained optimization problem 111 the following steps: Identifying the PV system dummy variables and classifying them into two main categories; independent and dependant variables. Constructing a proposed objective function represents the PV output power based on the independent and dependant variables. Constructing the proposed constraints either equality or inequality that control the operation of the PV module. 4. Solving the constrained optimization problem. Maximum Power Point Tracking (MPPT) based on Fuzzy Logic Control (FLC) and Adaptive Neuro Fuzzy Inference System (ANFIS) is simulated and compared |