Over the last decade, flexible alternating current transmission systems (FACTS) have been crucial in ensuring optimal power distribution within modern power systems. A vital component of FACTS devices is the distribution static compensator (DSTATCOM), which is essential for maintaining a reliable power supply. It is commonly used for reactive power compensation, voltage regulation, and harmonic reduction. Determining the appropriate size and placement of DSTATCOMs is vital to ensuring their efficiency. This study introduces the improved gray wolf optimizer (I-GWO), a refined version of the classical gray wolf optimization (GWO) method. The I-GWO incorporates a dimension learning-based hunting (DLH) strategy to preserve population diversity, balance exploration and exploitation, and prevent the premature convergence of classical GWO. In this research, the I-GWO was applied to determine the optimum allocation and sizing of the DSTATCOMs, considering system constraints, including those presented by the intermittent and stochastic nature of the load and renewable energy resources, specifically wind and solar energy. The suggested approach was successfully tested on 33-, 69-, and 85-bus distribution systems and then compared with existing studies. The results demonstrated the I-GWO-based approach’s superiority in terms of reducing power losses, improving voltage profiles, and enhancing voltage stability.

Model predictive control (MPC) is a powerful strategy for tackling multiobjective control challenges, but it often involves a laborious process of tuning weighting factors. This article proposes a gain-free MPC method for a recently developed nine-level T-type converter (9L-T2C), which offers advantages over traditional topologies, such as fewer components and improved efficiency. Drawing inspiration from Lyapunov's theory, this method avoids the use of weighting factors while effectively handling three targets, including current tracking, balancing of flying capacitors (FCs), and regulation of the neutral point (NP). Comparable with the traditional finite-control-set MPC (FCS-MPC), the proposed controller demonstrates high performance concerning all objectives. Additionally, it showcases superior resilience against model uncertainties when compared with the traditional approach. Experimental validation of the proposed MPC method is conducted in grid-connected operation under several conditions. The proposed method is subjected to a comparative analysis via the experimental implementation, where it is compared with a proportional-resonant (PR) controller and other state-of-the-art MPC methods. This analysis reveals the advantages of the proposed method, including eliminating the need for gains or weighting factors, improved robustness, and effective control of the FCs.

Rectangular Hollow Flange (RHF) steel beams may have openings drilled in their top surface to pass some plumbing and electrical wiring inside the RHF cavity. These openings affect the behavior of these steel beams and may reduce their resistance to bending moment. To investigate this effect, Finite Element Modeling (FEM) was used to simulate RHF steel beams with and without flange openings with several variables in geometric di mensions. The FEM results were examined using 8 experimental test specimens of RHF steel beams obtained from previous studies without flange openings. The results showed high accuracy in modeling these RHF steel beams in structural behavior and ultimate bending moment capacity. Current design codes were applied to predict the capacity of these RHF steel beams without flange openings, both from FEM results and experimental tests. The prediction values were always less than the ultimate capacity of RHF steel beams without flange openings. After verifying the results, 98 RHF steel beams with different flange opening diameters were modeled. The reduction ratios in ultimate capacity in steel beams with hollow flange openings are directly proportional to the opening diameter, hollow flange height, and steel yield stress, while they are inversely proportional to the thickness and width of the hollow flange and the steel beam web height. The reduction ratios in the ultimate capacity for RHF steel beams with flange openings are small in the compact category, and these ratios increase with the non compact and slender categories.

External loads applied to a box-section steel column before it is filled with concrete to increase its efficiency due to modifications in structural systems or design errors may reduce its ultimate capacity and change its structural behavior. To examine this effect, finite element modeling (FEM) has been used to simulate these columns under preloading at different ratios with many variables in the geometric dimensions of the columns. The FEM results have been investigated using 38 experimental specimens obtained from previous studies without preloading. The results demonstrated high accuracy in modeling these columns in structural behavior and ultimate load capacity. After verifying the results, 84 Concrete-Filled Steel Columns (CFSC) were modeled under different preload ratios. The results indicated that some variables have directly affected the value of the decrease in column capacity in terms of its height, wall thickness, yield stress, and preload ratios, while others were inversely proportional in terms of the cross-section dimensions and concrete strength. The preload effect ratio had two separate limits, where when it reached 70%, the maximum value of the decrease in column capacity was 10.90%. The value increased sharply reaching 19.90% when there was a preload equal to 80%. New equations have been proposed to predict the ultimate capacity of CFSC under preloading with suitable accuracy with a correlation coefficient of no less than 0.949.