Power, Control, and Data Processing Systems

Abstract Nowadays, the gimbal stabilizes the line of sight and eliminates vibration in systems such as imaging, radar line of sight, and position stabilizers. The gimbal system tries to maintain the system's current state by dealing with the changes made in the system's current state. This system reduces unwanted motion disturbances and vibrations. The most common use of the gimbal system is in modern photography equipment. In this article, a single-axis gimbal stabilizer system that uses a PD_PI fuzzy controller has been investigated and the PSO algorithm has been used to optimize and calculate controller coefficients. The dynamic relations of the gimbal are described and the proposed control system based on the PD_PI fuzzy controller is optimized using the PSO algorithm. The controller coefficients have been optimized with the lowest possible settling time. The comparison of the obtained results shows that this controller has less settling time and much less overshoot than other controllers such as PID and fuzzy PID controllers.

Abstract In this research, optical emission spectroscopy measurement technique OES was used to determine and calculate the electron density parameter of the low pressure cold glow discharge Ar plasma. For achieve this purpose, the Stark broadening of Balmer line of hydrogen spectrum Hβ obtained from plasma system in different pressure conditions were used to calculate the electron density. By calculating the electron density values obtained at different plasma pressures of 0.05, 0.13, and 0.65 Torr, it was found that there is a significant relationship between the plasma pressure and its electron density. The results showed that with the increase in the plasma pressure, its electron density also increases. Therefore, for use of this plasma system in different applications such as in industrial applications, treatment of biomaterials, medicine or print and packaging of polymers, by changing the pressure parameter of plasma system, the optimum conditions of surface plasma treatment can be obtained plasma system, the optimum conditions of surface plasma treatment can be obtained.

Abstract Microfluidics has a wide range of applications in various fields, especially experimental sciences, chemical industries, microelectronics and pharmaceuticals. Given flow chemistry's advantages over traditional batch approach and wide applications, continuous-flow approaches using microreactors and other microfluidic devices have gained significant attention in recent years from academia and industries. This research studied the design and simulation of the proposed micromixers and microreactors using computational fluid dynamics (CFD) and COMSOL Multiphysics software. During the simulations, transport of dilute species and laminar flow physics were applied, with water used as the operational fluid, entering the microchannels with two different concentrations. Additionally, the mixing index was used as the objective function to quantitatively compare the performance of the microchips, which were calculated at four residence time levels: 20, 30, 40, and 100 minutes for each design. Based on the simulation results, microreactor 1 demonstrated a significantly better mixing index compared to microreactor 2, with its mixing index reaching 92.6% and 99.8% at residence times of 40 and 100 minutes, respectively. Following, microchips that indicated better performance were selected for the fabrication process using glass and CO2 laser engraving technique. After that, a leakage test was performed to ensure the appropriate fabrication method. Finally, an experimental mixing test was performed on the fabricated micromixer to show the good agreement between experimental and simulation outcomes.

Abstract One of the most pressing challenges in power systems is the environmental impact, which is so critical that the Smart Grid (SG) includes it as one of the three key pillars in its framework. Renewable energy sources offer a potential solution by reducing reliance on fossil fuels and lowering carbon dioxide emissions, which are detrimental to the environment and contribute to global warming. However, certain renewable sources, such as photovoltaic (PV) cells, have uncontrollable power generation, posing a new challenge for grid stability. A viable solution to this issue is the implementation of Energy Storage Systems (ESS). These systems can store excess energy produced by renewables during periods of overproduction and release it when needed to enhance economic operation. In this paper, a Unit Commitment (UC) problem is performed in the presence of PV cells, ESS (in the form of batteries), and imported power from neighboring grids. The problem is modeled and simulated in MATLAB, where the inherent nonlinearity is managed by applying a Mixed-Integer Linear Programming (MILP) approach. Also, the simulation framework is designed with flexibility, enabling it to accommodate various piecewise linearization and different configurations of thermal units in the grid. The simulation results demonstrate an optimal economic operation with a total cost of approximately 124.57 $/MWh achieved through effective integration of solar energy and energy storage systems.

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This paper proposes a plenary structure of an energy hub system to combine electrical, thermal, cooling, and water infrastructures to promote modern distribution systems and increase flexibility and efficiency. The LSTM neural network predicts electrical loads with controlling variables such as air temperature, wind speed, humidity, holidays, and weekends. It is assumed that the system operator likes to use groundwater sources better. However, climate change, land subsidence, droughts, destruction of glaciers and lakes, dust storms, and inadequate water and food sources for future generations are the main challenges of unsustainable use of groundwater sources. A multi-objective optimization is proposed to simultaneously keep down the total operating costs and use of groundwater sources in the system. Renewable energy resources, electric vehicles, responsive electrical and thermal load programs, and energy storage systems have been developed to increase flexibility in the proposed system and are tried out in a standard case study. The simulation results show that the proposed approach reduces groundwater extraction by 26.88%.

Abstract In this paper, we introduce a novel Delay-Weight-Sum (DWS) beamforming technique for defect detection in non-destructive testing (NDT). This method offers improved accuracy over traditional Total Focusing Method (TFM) and its weighted variants. The proposed technique enhances defect detection and imaging quality through an advanced DWS beamforming approach based on a minimum variance method. The minimum variance approach utilizes the Newton-Schulz iterative method for efficient matrix inverse approximation. Additionally, a new non-linear weighting mechanism, based on a sigmoid function, is introduced to refine the matrix inverse approximation for DWS beamforming. This mechanism dynamically adjusts the weighting to enhance reflective points while reducing background noise. Comparative analyses demonstrate the superior imaging resolution and reduced background noise achieved by the proposed method compared to existing TFM-based techniques. Despite its computational demands, simulation results show that the method significantly improves ultrasonic image quality and contrast, holding promise for advancements in ultrasonic NDT, especially in heterogeneous and noisy environments.