Series compensations are implemented to reduce line reactance, improve voltage profiles, and boost power transfer capacity in long-distance transmissions. This study evaluates the effects of series compensation on load flows, voltage stability, transmission losses, and power transfer using PSS®E simulations coupled with Newton-Raphson load flow analysis. The study used a systematic placement methodology combining Voltage Sensitivity Analysis and Line Reactance Screening to identify optimal capacitor locations in the IEEE 14-bus network, specifically targeting Lines 13 - 14 and 9 - 14, both directly connected to the weakest bus. Simulation scenarios across 0% - 50% compensation levels reveal improvements of up to +1.1% in weakest-node voltage, approximately 15% - 16% increase in power transfer capacity, and measurable reductions in line losses in both lines. These outcomes highlight significant system performance gains even in lightly loaded networks. A first-level SSR frequency screening is also reported to verify that the 20% - 50% compensation range does not introduce an obvious resonance concern for the benchmark case.

Thermoplastic elastomers (TPEs) are increasingly explored for structural and energy-related engineering applications due to their recyclability and processing versatility. However, their mechanical limitations restrict wider utilization in high-performance environments. This study examines the combined effects of silica reinforcement and electron beam (EB) irradiation on the mechanical, structural, and morphological properties of natural rubber/high-density polyethylene (NR/HDPE) composites. NR and HDPE were melt-blended with silica loadings of 2 and 10 phr, followed by compounding and subsequent EB irradiation at 50 and 100 kGy. Results show that silica significantly enhances tensile strength, from 5.25 MPa (0 phr) to 18.53 MPa (2 phr) and 25.65 MPa (10 phr), while EB irradiation further increases tensile performance by up to 87.2% at 2 phr and 77.5% at 10 phr. Fourier transform infrared spectroscopy (FTIR) analysis confirms the presence of Si-O-Si and Si-OH bonding structures, while scanning electron microscopic (SEM) observations reveal a transition from ductile to brittle fracture morphology with increasing irradiation, indicating higher crosslink density. The findings demonstrate that silica-polymer interactions, combined with EB-induced crosslinking, provide an effective pathway for producing stronger and more durable NR/HDPE-based TPEs suitable for engineering applications requiring improved mechanical integrity and long-term performance. These results highlight the synergistic role of silica loading and EB irradiation in tailoring the stiffness and deformation behavior of NR/HDPE composites for demanding engineering applications.

The PMU’s performance relies on its ability to detect and provide accurate measurements of both steady-state and dynamic conditions. The phasor estimation algorithm assesses the accuracy and quality of measuring grid parameters under various operating conditions. The Discrete Fourier Transform (DFT) algorithm is the most commonly used because of its low computational complexity and ease of implementation on any hardware. However, DFT has limitations in accurately obtaining a phasor during off-nominal grid frequency conditions caused by inter-harmonics, intermodulation, and frequency ramps. This paper introduces the design of a Hybrid DFT-ADALINE model. The ADALINE is a linear activation function where the input is directly proportional to the output, and it can learn from its environment and adjust its weights to minimize errors. Recently, many researchers have focused on applying an adaptive linear neural network (ADALINE) for parameter estimation due to its low computational complexity, minimal tracking error, and faster convergence rate. ADALINE is widely used as a harmonic estimator because of its simple structure and ability to track nonstationary signal parameters. A key feature of this approach is the integration of ADALINE, which tracks the estimated frequency and the phase angle error output of the PMU, converting it into a correlation coefficient. The ADALINE deep learning AI analyzes the changing pattern of frequency relative to the nominal grid frequency, comparing it to the phase angle error to determine the average correlation. The model is calibrated so that it reflects the average correlation for frequencies between 49.5 Hz and 50.5 Hz as normal grid conditions, ensuring the PMU does not generate alarms under these off-nominal conditions. This study demonstrates how a single PMU measurement parameter, the correlation coefficient, can be used to predict the behavior of the power grid under dynamic conditions, and how it can trigger grid voltage and frequency adjustments, significantly simplifying the fault detection logic of the power system and reducing computation latency.

The increasing integration of photovoltaic (PV) systems and electric vehicles (EVs) into distribution networks (DNs) presents significant operational challenges, including voltage fluctuations, reverse power flow, and rapid PV ramp rates. This paper proposes a rule-based strategy for deploying battery energy storage systems (BESS) to mitigate these issues and enhance the overall performance of the DN. The study evaluates the impacts of high PV and EV penetration on distribution network, performance using simulation models in OpenDSS, an open-source electric power distribution system simulator. A rule-based approach is then developed to determine strategic BESS dispatch strategies and sizing, targeting improvements in voltage stability, power quality, and system reliability. The proposed methodology is validated on a modified IEEE 33-bus radial distribution system comprising mixed loads (residential, industrial, and commercial) under PV penetration levels of 25% and 50%, with an EV penetration level of 10%. The optimal BESS allocations are identified at buses 18 and 33, with capacities of 1436 kW/5526 kWh and 1816 kW/10,854 kWh, respectively. Results indicate that higher PV penetration (50%) necessitates larger BESS capacities to sustain network reliability. The proposed allocation strategy ensures that bus voltages and PV ramp rates remain within permissible limits, while reverse power flow (RPF) is substantially mitigated. The proposed method offers a practical framework for grid operators to manage distributed energy resources efficiently, contributing to a more resilient and sustainable power system.

The operating conditions of a nuclear reactor vessel are characterized by high values of pressure and temperature of the fluid along the primary circuit, variable loads, intense neutron fluxes and a corrosively aggressive environment. All these factors cause aging of the Reactor Pressure Vessel (RPV) Internals metal. The mechanisms of degradation of the mechanical properties are neutron and thermal brittleness, corrosion, erosion, fatigue and wear. Corrosion of the metal is caused by the fluid along the primary circuit of the nuclear power plant. The high values of the reactor temperatures and the operating stresses cause stress corrosion and corrosion fatigue. Neutron flux causes the most damaging effect on the metal structure. After prolonged periods of exposure to high-energy neutrons (several decades), the metal of the reactor vessel becomes brittle and strengthened. Temperature and dose load gradients can cause swelling of the metal of the reactor internals. Swelling is an increase in the external dimension of solid materials after irradiation and is an extremely dangerous condition of the metal structure, because it reduces the bearing capacity of structures. In addition, the change in the geometric dimensions of the RPV Internals may disturb the movement of the heat carrier and the heat balance, to obtain jamming and blocking of units of the reactor control and protection system. This article discusses the reasons for the degradation of the mechanical properties of RPV Internals. Two methods for studying the effects of aging on objects are presented—visual method for monitoring the condition of the metal and method for measuring geometric dimensions, as well as the results obtained.

The increasing global demand for sustainable energy solutions has driven research into pico-hydropower systems as an efficient and environmentally friendly method for harnessing renewable energy. This study focuses on the optimization of free-flow water turbine applications using Computational Fluid Dynamics (CFD) analysis. Free-flow turbines, which operate in rivers or channels without the need for large-scale infrastructure, offer significant advantages in terms of cost, ecological impact, and ease of deployment. The research employs advanced CFD techniques to evaluate and enhance the performance of a turbine under various conditions. Key design parameters, including water flow rates of 2 L/s, water heads of less 5 m, turbine diameters of 0.75 m and 1 m, nozzle sizes at 10 mm, 12 mm and 15 mm and the pipe diameters setting of 0.75 inch and 1 inch. Optimization algorithms are integrated with CFD simulations to identify the most efficient configurations. The findings reveal the critical role of hydrodynamic optimization in improving the energy conversion efficiency of pico-hydropower turbines. The results identified the 1 m turbine with 0.75 inch pipe size at 12 mm nozzle diameter give the optimal design, achieving a maximum power out at 100 W with 5 m and 3 m water head. The optimized turbine design demonstrated a significant improvement in performance compared to existing models, validating the potential of CFD as a powerful tool for innovation in hydropower technology.

Dust accumulation on photovoltaic (PV) panels significantly reduces energy output, particularly in areas with high particulate matter from natural or industrial sources. This study aims to evaluate the effects of sand, cement, and charcoal dust on short-circuit current (Isc), open-circuit voltage (Voc), and panel surface temperature, identifying which parameters are most affected and which dust types pose the greatest risk to efficiency. Controlled laboratory experiments were conducted with dust mass of 30 g, 40 g, and 50 g applied uniformly to PV panels, and performance metrics were measured relative to clean-panel baselines. Results indicate that Isc is highly sensitive to dust, with sand causing a 40% reduction at 30 g and up to 85% at 50 g, while cement and charcoal consistently cause severe 80% - 100% reductions at all weights. Voc remains largely stable, with only minor variations such as a 5% - 8% drop for cement at 40 g, confirming that current loss is the primary cause of power degradation. Panel temperature generally rises with dust, with charcoal showing the highest increase at heavier loads due to greater heat absorption. These findings underscore the importance of frequent cleaning and mitigation strategies in dust-prone environments, especially where fine industrial particulates are present.

The increasing demand for reliable electricity in off-grid regions, particularly in remote areas, calls for innovative solutions. This project focuses on the integration of Pumped Storage Hydropower (PSH) with solar photovoltaic (PV) systems, aiming to provide a clean, sustainable, and stable energy solution. The primary goal is to design and develop a small-scale hybrid system that utilizes solar energy to pump water into an elevated reservoir, which can then be released to generate electricity via a turbine when solar generation is low or unavailable. An Arduino-based monitoring system was developed to track the performance of both the solar panel and the hydro generator. The system was designed, simulated, and tested under real-world conditions. Results indicate that although the system demonstrates potential for off-grid applications, the small-scale PSH prototype is less efficient compared to direct battery-based solar storage in terms of consistency and output power. The findings suggest that improvements in system design, turbine efficiency, and storage capacity are required to enhance the performance and reliability of the hybrid system. The outcomes highlight the viability of hybrid renewable systems for sustainable off-grid electrification but also indicate areas for future research, particularly in optimizing system design and scaling for broader applications.

This manuscript proposed three closed-loop strategies using Hysteresis Current Control (HCC) for PV-inverter application. A string-PV arrangement of parallel and series-PV connection (Np = 6 and Ns = 10) aims for target input voltage of ±400 V, intended for Off-grid PV (OGPV) system. The PV-system design is tested under Standard Test Condition (STC) where the irradiance and temperature are kept constant at 1000 W/m2 and 25˚C, respectively. Full-bridge inverter is chosen as the PV-inverter since it is commonly used inverter for unfolding purposes in the PV application. The proposed PV-inverter with HCC strategy was designed and compared with the PV-inverter using conventional Bipolar Pulse Width Modulation (PWM). These proposed blocks were designed and simulated using MATLAB/Simulink software. Performance improvement of the power quality was measured in terms of current and voltage harmonic percentage, where the PV-inverter with HCC produced slightly lower current harmonic percentage of THDi = 25.45% compared to THDi = 29.19% from the conventional strategy. The proposed HCC technique resulted in a 3.74% improvement in power quality. When combined with an additional LC-filter, the power quality was further enhanced, achieving improvements of 74% in voltage and 82% in current harmonic reduction, respectively.

This paper presents the performance of a three-phase three-wire SAPFs controlled with p-q theory and hysteresis current control. The reference harmonic currents are obtained using p-q theory, while a proportional-integral (PI) controller is used to keep the DC-link voltage constant. The hysteresis control generates switching signals for the inverter to inject compensating currents into the system. A MATLAB/Simulink model was built and tested with different nonlinear loads, such as resistive, inductive, capacitive, and unbalanced loads. The simulation results prove that the SAPFs can reduce the Total Harmonic Distortion (THD) from more than 28% down to below 5%, which satisfies the IEEE-519 standard. The results also show that the proposed method has a fast response and stable operation under changing load conditions. This study confirms that the SAPFs with p-q theory and hysteresis control is a reliable solution for harmonic reduction in power distribution systems.