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Modern power systems integrated with renewable energies (REs) contain many uncertainties. The proposed method introduces a novel approach to address the challenges associated with wind power generation uncertainty in probabilistic load flow (PLF) studies. Unlike conventional methods that use wind speed as an input, the paper advocates for utilizing wind generator output power (WGOP) as an input to the point estimate method (PEM) in solving PLF. The uniqueness lies in recognizing the distinct behavior of wind power uncertainty, where not all random samples of wind speed contribute to actual wind power production. The paper suggests a Nataf-KernelDensity-Spline-based PEM, combining the Nataf transformation, Kernel density estimation (KDE), and cubic spline interpolation. This innovative integration effectively manages wind power correlation within the analytical framework. By incorporating spline interpolation and kernel density estimation into the traditional PEM, the proposed method significantly enhances accuracy. To validate the effectiveness of the proposed approach, the method is applied to IEEE-9 and IEEE-57 bus test systems, considering uncertainties related to load, wind power generation (WPG), solar power generation (SPG), and conventional generator (CoG) outages. Comparative analysis with Monte Carlo simulation (MCS) results demonstrates that the proposed method outperforms the conventional PEM in terms of accuracy. Overall, the paper contributes a pioneering solution that not only highlights the importance of using WGOP as an input in PLF but also introduces a sophisticated method that surpasses traditional approaches, improving accuracy in power system studies involving renewable energy integration. The accuracy of the proposed method is validated by comparing its results with those obtained through Monte Carlo simulation (MCS), where the proposed method yields more accurate results than the conventional PEM. [ABSTRACT FROM AUTHOR]

In recent years, the proliferation of grid-connected microgrid systems has witnessed a remarkable surge, driven by the need to enhance the availability and reliability of renewable energy sources during peak demand periods. By reducing reliance on fossil fuels, these systems offer promising avenues for sustainable energy integration. To ensure seamless synchronization of renewable energy sources with the grid, Phase-Locked Loop (PLL) controllers have emerged as a key solution. However, the information available about these PLLs is limited. In this paper, the analysis, design, and comparison of PLLs, along with the exploration of a recently developed PLL synchronization method. Specifically, we evaluate the performance of prominent PLL techniques, including PSRF-PLL, SOGI-PLL, DSOGI-PLL, E-PLL, and IPT-PLL, under diverse test scenarios such as voltage sag, swell, unbalance, and harmonics. To assess their effectiveness, hardware-in-loop virtual and real-time test-beds are employed, enabling rigorous examination of the PLL techniques for grid synchronization. The reported results demonstrate the phase tracking capability when operating in grid-connected mode. Finally, conclusions are drawn from studies conducted in the electrical grid network's healthy and unhealthy environments. • The design and analysis of PLL synchronization methods are provided. • Performances of PSRF-PLL, SOGI-PLL, DSOGI-PLL, E-PLL, and IPT-PLL are examined. • The PSRF-PLL, SOGI-PLL, DSOGI-PLL, E-PLL, and IPT-PLL designs are briefly explained. • The directions of PLL preference in a healthy and unhealthy grid environment are listed. • The synchronization efficiency and distortion management capacity of PLLs are listed. [ABSTRACT FROM AUTHOR]