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Usually, a LPF (low pass filter) is used in the feedback loop of a SRF (synchronous reference frame) -PLL (phase locked loop) system because the measured grid voltage contains harmonic distortions and sensor noises. In this paper, it is shown that the cut-off frequency of the LPF should be designed to suppress the harmonic ripples contained in the measured voltage. Also, a new design method for the loop gain of the PI-type controller in the SRF-PLL is proposed with consideration of the dynamics of the LPF. As a result, a better transient response can be obtained with the proposed design method. The LPF frequency and the PI controller gain are designed in coordination according to the steady state and dynamic performance requirements. Furthermore, in the proposed method, the controller gain and the LPF cut-off frequency are changed from their normal value to a transient value when a voltage disturbance is detected. This paper shows the feasibility and usefulness of the proposed methods through the computer simulations and experimental results.

In this study, optimal decision-making process in photovoltaic (PV) system location selection in Saudi Arabia is described. First, to identify the criteria that influence the decision of selecting a suitable location for the PV system, the geographical information system (GIS)-based multi-criteria decision making (MCDM) approach is used. Next, to assess the weights of the criteria that present different aspects of the investigated locations, four major criteria and 11 sub-criteria are proposed, and analytic hierarchy process (AHP) is applied to develop comparison decision matrix. Finally, the order preference by similarity to ideal solution (TOPSIS) technique evaluates and classifies 17 cities (such as Riyadh, Jeddah) in Saudi Arabia. The result shows that Tabuk city in the northern of Saudi Arabia is the best location. Among the 17 cities, the performance score of seven cities is above or equal 80%, and Tabuk city has the highest score with 87%. This analytical approach could contribute as an early planning to locate suitable sites for the selection of PV system region in Saudi Arabia.

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An effective maximum power point tracking (MPPT) technique plays a crucial role in improving the efficiency and performance of grid-connected renewable energy sources (RESs). This paper uses the African Vulture Optimization Algorithm (AVOA), a metaheuristic technique inspired by nature, to tune the proportional–integral (PI)-based MPPT controllers for hybrid RESs of solar photovoltaic (PV) and wind systems, as well as the PI controllers in a storage system that are used to smooth the output fluctuations of those RESs in a hybrid system. The performance of the AVOA is compared with that of the widely used the particle swarm optimization (PSO) technique, which is commonly acknowledged as the foundation of swarm intelligence. As a result, this technique is introduced in this study to draw a comparison. It is observed that the proposed algorithm outperformed the PSO algorithm in terms of the tracking speed, robustness, and best convergence to the minimum value. A MATLAB/Simulink model was built, and optimization and simulation for the proposed system were carried out to verify the introduced algorithms. In conclusion, the optimization and simulation results showed that the AVOA is a promising method for solving a variety of engineering problems.