System Load Research Articles

A Swarm Intelligent Metaheuristic Approach for Efficient Series Compensation Resulting in System Loadability Enhancement

A Swarm Intelligent Metaheuristic Approach for Efficient Series Compensation Resulting in System Loadability Enhancement

Flexural Behaviour and Environmental Impact of African Fan Palm Reinforced Concrete Beams under Symmetrical Loading Conditions

The paper presents the results of investigation on reinforced beams adopting eco-friendly materials for sustainable concrete. The use of African fan palm is explored to mitigate the environmental impact aimed at reducing carbon emissions associated with the production and use of steel reinforcement. The beams were tested under a four -point loading system with the ends simply supported. The test comprised twenty-three beams that were reinforced with African fan palm bars whilst two beams were reinforced with mild steel bars to serve as control beams. The study investigated the flexural strength and deformation characteristics of the beams under monotonic loading. Two concrete strengths of 15.34N/mm2 or 22.37N/mm2 were adopted and proposed optimal tensile ratios for an under reinforced fan palm section. The parameters considered included the tension bars ratio (ρ), concrete compressive strength, span-to-effective-depth ratio and loading conditions. A linear elastic behaviour of both fan palm and steel reinforced concrete beams was observed to the point of first crack load beyond which the beam stiffness continued to reduce until failure. A comparison of the experimental results with results of theoretical analysis of the beams revealed that a 1.22% increase in the tensile ratio of steel in the control beams increased the cracking moment (Mcr) to 36%, while the fan palm beam of the same size and same concrete strength with a higher tensile ratio of 9.69% exhibited a lower Mcr of 11.86%. This shows a significant effect of reinforcing steel bars on concrete cracking compared to the fan palm. The averages of experimental to theoretical failure loads of fan palm to steel were compared with failure loads of 36.52kN to 20.19kN and 32kN to 19.78kN respectively. These results of the study based on the failure mode, and failure loads, highlights the suitability of using African fan palm as substitute reinforcing material for low rise buildings. Furthermore, the study also proposed minimum and maximum tensile ratio of 0.76% and 5.60% respectively for fan palm reinforced concrete beams based on the Indian Standard and modulus of elasticity of steel.

Experimental study of performance of building heating system based on HPS and equipped with thermal potential recovery system and heat load prediction

The results of experimental studies of the heating system performance of a building located in the area of temperate continental climate with temperatures in the heating period down to −30 °C are discussed. The studied heating system comprises an air–liquid heat pump, a liquid–liquid heat pump with a ground circuit, and an electric boiler for peak demands.The paper presents the results of the influence of the ground thermal potential recovery system on the liquid–liquid heat pump performance. Also the influence of the used method of heat load prediction on the system efficiency and indoor air temperature stability is shown.Implementation of the thermal potential recovery system allows to increase the average value of the transformation coefficient for the liquid–liquid heat pump from 2.7 to 2.9 during three years of operation.Heat load prediction leads to stable indoor air temperature in the range of 22 ± 1 °C. Also it allows to level out the dependence of indoor temperature fluctuations on outdoor air temperature fluctuations.

High loading and sustained-release system of doxorubicin-carbon dots as nanocarriers for cancer therapeutics

Nanocarriers for drugs have been investigated for decades, yet it is still challenging to achieve sustained release from nanomaterials due to drug loading inefficiency and burst release. In this study, we developed novel functional carbon dots (CDs) and investigated the therapeutic efficacy by studying the loading efficiency and release behavior of the anticancer drug doxorubicin (DOX). CDs were successfully synthesized using a one-step pyrolysis method with varying concentrations of citric acid (CA) and thiourea (TU). Functional groups, morphology, particle size, and zeta potential of synthesized CT-CDs and DOX loaded CT-CDs were investigated by UV-visible, Fluorescence, dynamic light scattering, Zeta Potential measurements, FTIR, and transmission electron microscopy. The zeta potential data revealed DOX loading onto CT-CDs by charge difference, i.e. -24.6 ± 0.44 mV (CT-CDs) and 20.57 ± 0.55 mV (DOX-CT-CDs). DOX was loaded on CDs with a loading efficiency of 88.67 ± 0.36%.In vitrodrug release studies confirmed pH-dependent biphasic drug release, with an initial burst effect and sustained release of DOX was found to be 21.42 ± 0.28% (pH 5), 13.30 ± 0.03% (pH 7.4), and 13.95 ± 0.18% (pH 9) even after 144 h at 37 °C. The CT-CDs were non-toxic and biocompatible with L929 Fibroblasts cells. The cytotoxic effect of DOX-CT-CDs showed a concentration-dependent effect after 48 h with Glioblastoma U251 cells. Flow cytometry was used to examine the cellular uptake of CT-CDs and DOX-CT-CDs in L929 and U251 cells. It was observed that the maximum CT-CDs uptake was around 75% at the end of 24 h. This study showed that the synthesized fluorescent CT-CDs demonstrated a high drug loading capacity, pH-dependent sustained release of DOX, and high cellular uptake by mammalian cells. We believe this work provides practical and biocompatible CDs for chemotherapeutic drug delivery that can be applied to other drugs for certain therapeutic aims.

Steam Pressure Control of Marine Boiler Based on AFSA-PSO-LSSVM

Abstract To solve the problem that the main steam pressure fluctuates greatly when the load of the combustion control system of the marine main boiler changes suddenly, present a combined inverse control system of Support vector machine and PID to control the steam pressure intelligently. The inverse model of the nonlinear system identified by LSSVM is used as the feedforward controller and the PID controller is used as the feedback controller. The hybrid intelligent algorithm of artificial fish swarm Algorithm and particle swarm optimization is used to optimize the parameters of the control system. The AFSA algorithm is used to search the initial values of the parameters and the PSO algorithm is locally updated. Finally, the mechanism of the steam pressure control system of the marine boiler is modeled and simulated, and the algorithm models of AFSA-PSO-LSSVM-PID, AFSA-LSSVM-PID, PSO-LSSVM-PID and LSSVM-PID are established. The experimental results show that the AFSA-PSO-LSSVM-PID model has a good dynamic, stability, anti-interference ability and robustness.

PlugGuard: A Neural Network-Based Power Quality Control System for Plug Loads

PlugGuard: A Neural Network-Based Power Quality Control System for Plug Loads

Behind-the-Meter Load and PV Disaggregation via Deep Spatiotemporal Graph Generative Sparse Coding With Capsule Network.

Nowadays, rooftop photovoltaic (PV) panels are getting enormous attention as clean and sustainable sources of energy due to the increasing energy demand, depreciating physical assets, and global environmental challenges. In residential areas, the large-scale integration of these generation resources influences the customer load profile and introduces uncertainty to the distribution system's net load. Since such resources are typically located behind the meter (BtM), an accurate estimation of BtM load and PV power will be crucial for distribution network operation. This article proposes the spatiotemporal graph sparse coding (SC) capsule network that incorporates SC into deep generative graph modeling and capsule networks for accurate BtM load and PV generation estimation. A set of neighboring residential units are modeled as a dynamic graph in which the edges represent the correlation among their net demands. A generative encoder-decoder model, i.e., spectral graph convolution (SGC) attention peephole long short-term memory (PLSTM), is devised to extract the highly nonlinear spatiotemporal patterns from the formed dynamic graph. Later, to enrich the latent space sparsity, a dictionary is learned in the hidden layer of the proposed encoder-decoder, and the corresponding sparse codes are procured. Such sparse representation is used by a capsule network to estimate the BtM PV generation and the load of the entire residential units. Experimental results on two real-world energy disaggregation (ED) datasets, Pecan Street and Ausgrid, demonstrate more than 9.8% and 6.3% root mean square error (RMSE) improvements in BtM PV and load estimation over the state-of-the-art, respectively.

Reliability-constrained configuration optimization for integrated power and natural gas energy systems: A stochastic approach

With the escalating dependence on electricity and natural gas infrastructure, ensuring both reliability and economic efficiency becomes paramount. It necessitates reliability centric measures to mitigate disruptions that could cascade between these interconnected systems. To address this challenges, this paper introduces a reliability-constrained two-stage stochastic model to optimize power-to-gas (P2 G) and gas-to-power (G2P) unit placement and sizing, aiming to enhance the reliability of both systems under stochastic scenarios. The proposed model, employing Sequential Monte Carlo (SMC) within its optimization framework, seeks to minimize investment, operation, and reliability costs. By addressing temporal uncertainties in component outages for both systems and considering uncertainties in power and gas system loads with a high temporal resolution and annual load growth, the model provides a comprehensive reliability perspective. Furthermore, sensitivity analysis is conducted to explore the impact of varying Values of Lost Load (VOLL) on the planning results. Numerical evaluation, using two integrated energy systems including IEEE 14-bus-10-gas node, and large-scale energy systems including IEEE 118-bus-85-gas node integrated power-gas system (IPGS), demonstrates a significant 12.53 % improvement in overall system reliability. Furthermore, a 2.81 % reduction in operation costs and a substantial 26.3 % reduction in reliability costs, validating the effectiveness of the proposed model.

A Biomechanical Analysis of Oblique Metacarpal Metadiaphyseal Fracture Fixation in a Cadaver Model

Although metacarpal fractures are typically managed nonoperatively, when surgical management is indicated, metacarpal fractures are commonly treated with crossed Kirschner wires (K-wires), which may limit early range of motion. Intramedullary implants are increasing in use with the potential advantage of early range of motion; however, stability in oblique metacarpal neck fractures remains a theoretical concern. The purpose of this study was to determine the biomechanical stability of noncompressive intramedullary fixation for oblique metacarpal neck fractures compared with crossed K-wire fixation. The index, long, and small metacarpals were harvested from three matched pairs of fresh-frozen cadavers. Oblique fractures at the metadiaphyseal region were created in each metacarpal. Each metacarpal was randomized to noncompressive, threaded intramedullary nail fixation or fixation with two crossed K-wires. Specimens were mounted in a Materials Testing System load frame and axially loaded until failure. Load to failure (LTF), stiffness, and load to 2 mm displacement were calculated from load-displacement curves. Differences in peak LTF, stiffness, and load to 2 mm displacement between noncompressive intramedullary fixation and crossed K-wire fixation were evaluated. The noncompressive intramedullary fixation cohort had a significantly higher LTF (1,190.9 ± 534.7 N vs 297.0 ± 156.0 N) and stiffness (551.3 ± 164.6 N/mm vs 283.0 ± 194.5 N/mm) when compared with the crossed K-wire fixation cohort. Load at 2 mm displacement was greater in the noncompressive intramedullary fixation cohort compared with crossed K-wire fixation (820.5 ± 203.9 vs 514.1 ± 259.6). For oblique metadiaphyseal metacarpal fractures, noncompressive intramedullary fixation provides a biomechanically superior construct under axial loading in terms of LTF, stiffness, and load to 2 mm of displacement compared with crossed K-wire fixation. Noncompressive intramedullary nails may be an alternative to K-wire fixation for the treatment of oblique metadiaphyseal metacarpal fractures.

Loss characteristics and optimization method of a compressed air energy storage radial turbine with nozzle governing

During the operation of the compressed air energy storage (CAES) system, a discrepancy exists between the air storage pressure and the turbine inlet pressure. At the same time, to ensure that the turbine operates efficiently when the system load varies, the turbine needs to be regulated reasonably. In this paper, the influence of three nozzle governing (NG) parameters on turbine performance during the NG process is investigated: the inlet pressure of the NG region, the area of the NG region, and the base pressure. The flow characteristics and loss mechanisms under partial admission conditions and NG conditions are also analyzed. Furthermore, the NG process is optimized by using a transition section. The results show that the loss under the NG condition with low inlet pressure at the NG region is similar to the partial admission loss, both of which are mainly affected by the area of the NG region. In both working conditions, vortex structures appear at the stator outlet of the NG region. At the same time, the mixing of different airflows and the flow separation phenomenon within the rotor leads to a significant increase in entropy production rate. The transition section can attenuate the leakage and reduce the entropy production rate in the radial gap between the stator and rotor, increasing turbine efficiency by up to 1.1 % at maximum when using the transition section.

Ground test modeling of cylindrical aero-engine casing under high-temperature and high-pressure aerodynamic load

The aero-engine casing is subjected to high-temperature and high-pressure aerodynamic loads during operation. It is essential to perform the ground strength tests for the casing. To optimize the ground strength test and to improve the accuracy of temperature and pressure loading during the test, a mathematical model of high-temperature and high-pressure aerodynamic loading system for simulating the ground strength test of typical aero-engine casing is established to study the actual temperature and pressure loads on casing during ground test. The temperature and pressure results calculated by the mathematical model under typical loads matched well with the experimental measurements. The verification results show that under the test conditions, the thermal inertia of the heater, the radiation heating of the gas in the test chamber by the heater, and the heat transfer of gas mixing in the pressure process can be ignored. The sensitivity analysis of the parameters affecting the accuracy of pressure and temperature loading is carried out. We show that the pressure can be controlled quantitatively by adjusting the inlet and exhaust pipe parameters, and accurate temperature control can be achieved by designing reasonable heater power and selecting appropriate heating control parameters.

Experimental and numerical investigation on rock fracturing and fragmentation under coupled static pressure and blasting

The blasting technique is widely adopted to break rock in civil and mining engineering, and its operation is generally subjected to static pressure due to tectonic and gravitational stresses. In the present study, the rock fracturing and fragmentation under coupled static pressure (uniaxial pressure and confining pressure) and blasting are experimentally and numerically investigated. First, 11 blast tests with 100-mm cubic red sandstone samples are carried out based on a biaxial loading system. Then, the blast-produced rock fragmentation in blast testing is numerically modeled using finite element method with LS-DYNA, and the explosion pressure attenuation and fracture evolution in rock samples are numerically reproduced. The simulated rock fragmentation data are obtained by image processing in ImageJ, and the fragment size distribution of red sandstone under combined static stress and blasting is characterized using Weibull distribution. Accordingly, the effects of uniaxial pressure and confining pressure on blast-created rock fragmentation are quantitatively compared and analyzed, and the corresponding mechanisms are discussed and revealed. The current findings indicate that the static pressure plays a role in increasing blast-induced compressive stress and reducing tensile stress in both radial and hoop directions and thus results in a decrease in the length and number of fractures propagating vertically to the direction of applied pressure, further leading to the creation of coarser fragmentation. Blasting under confining pressure produces larger fragments than that under uniaxial pressure. The average fragment size increases quickly at first and then increases slowly with the increase of static stress, which can be well characterized using a logarithm equation. Based on current findings, increasing the free surface is crucial in practical blasting to improve rock fragmentation performance under blasting.

Parameter adaptive stochastic model predictive control for wind–solar–hydrogen coupled power system

With the increasing global energy scarcity and environmental concerns, the wind–solar–hydrogen (WSH) coupled system has garnered widespread attention as an efficient and eco-friendly renewable energy solution. Addressing the impact of uncertainty on the source and load of the coupled system concerning its power balance, a parameter adaptive stochastic model predictive control (PAS-MPC) power regulation strategy based on the scenario analysis method is proposed herein. In order to characterize the probabilistic information about the uncertainty on both sides of the system, scenario generation and reduction techniques are used to obtain classical scenarios of wind and solar outputs as well as electrical loads as inputs to PAS-MPC. With the aim of optimizing the computational time constant of SMPC, the parameter adaptive method is proposed to change the prediction time domain and control time domain of the system. Simulation results demonstrate the effectiveness of PAS-MPC in addressing uncertainties on the source and load sides of the WSH coupled system. Optimization results reveal that PAS-MPC considerably improves the system power balance compared to SMPC. Compared to the conventional model predictive control (MPC), PAS-MPC effectively mitigates high-power state of the controllable equipment of the system, thereby enhancing its lifecycle.

OPTIMIZING PROCESSOR WORKLOADS AND SYSTEM EFFICIENCY THROUGH GAME-THEORETIC MODELS IN DISTRIBUTED SYSTEMS

The primary goal of this research is to examine how different strategic behaviors adopted by processors affect the workload management and overall efficiency of the system. Specifically, the study focuses on the attainment of a pure strategy Nash Equilibrium and explores its implications on system performance. In this context, Nash Equilibrium is considered as a state where no player has anything to gain by changing only their own strategy unilaterally, suggesting a stable, yet not necessarily optimal, configuration under strategic interactions. The paper rigorously develops a formal mathematical model and employs extensive simulations to validate the theoretical findings, thus ensuring the reliability of the proposed model. Additionally, adaptive algorithms for dynamic task allocation are proposed, aimed at enhancing system flexibility and efficiency in real-time processing environments. Key results from this study highlight that while Nash Equilibrium fosters stability within the system, the adoption of optimal cooperative strategies significantly improves operational efficiency and minimizes transaction costs. These findings are illustrated through detailed 3D plots and tabulated results, which provide a detailed examination of how strategic decisions influence system performance under varying conditions, such as fluctuating system loads and migration costs. The analysis also examines the balance between individual processor job satisfaction and overall system performance, highlighting the effect of rigid task reallocation frameworks. Through this study, the paper not only improves our understanding of strategic interactions within computational systems but also provides key ideas that could guide the development of more efficient computational frameworks for various applications.

Application of artificial neural network for peak load forecasting in 150 kV Semarang power system

Accurate load forecasting is essential for reliable and efficient operation of power systems. Traditional forecasting methods often struggle with capturing complex nonlinear patterns in load data. Artificial neural networks (ANNs) have emerged as a promising alternative due to their ability to learn complex relationships from historical data (Syed et al. in IEEEA 9:54992–55008, 2021. https://doi.org/10.1109/ACCESS.2021.3071654). This study investigates the potential of ANNs for short-term peak load forecasting in a 150 kV power system in Semarang, Indonesia. The study examines the impact of different input variables, including historical peak load, minimum load, population, and energy production, on forecasting accuracy. Several ANN architectures are trained and evaluated using mean absolute percentage error (MAPE) and mean squared error (MSE) metrics as reported by Demuth and De Jesús (neural network design). The results indicate that ANNs can achieve high accuracy in predicting peak load, with MAPE values below 10%. The study also demonstrates the importance of carefully selecting input variables and training parameters for optimal model performance. The findings highlight the potential of ANNs for improving load forecasting accuracy in power systems, contributing to enhanced grid reliability and operational efficiency. The findings of this study contribute to a deeper understanding of the application of ANNs in power system load forecasting. They demonstrate the potential of ANNs to achieve high accuracy and provide valuable insights into the factors influencing model performance. The findings are relevant for power system operators, researchers, and policymakers working to improve grid reliability and efficiency as reported by Prabha Kundur and Malik (Power System Stability and Control, McGraw-Hill Education, New York, 2022. https://www.accessengineeringlibrary.com/content/book/9781260473544).

Synergetic UPQC Application for Power Quality Enhancement in Microgrid Distribution System: SCSO Approach

Nowadays, Hybrid renewable energy systems (HRES) are increasingly being integrated into grid-connected load systems to lower losses and boost dependability. When the HRES system is connected to the grid system to satisfy needed load demand, power quality issues arise because of imbalanced load circumstances, non-linear load, and critical load. So this manuscript proposed a synergetic Unified Power Quality Conditioner (UPQC) application for power quality enhancement in microgrid distribution systems. The Sand Cat Swarm Optimization (SCSO) technique is based on the proposed sand cat swarm optimization method. The proposed strategy's primary goal is to regulate power flow, minimize harmonic distortion in both voltage and current waveforms, and maximize UPQC. By then, the proposed method's performance has been implemented into practice on the MATLAB platform and contrasted with several currently used techniques. The proposed technique displays the low Total Harmonic Distortion (THD) and operation time in all existing approaches like Moth Flame Optimization (MFO), Genetic Algorithm (GA), Salp Swarm Algorithm (SSA), Ant Lion Optimizer (ALO), Improved Bat Search Algorithm (IBSA), Lion Algorithm (LA), Artificial Bee Colony (ABC), Atom Search Optimization (ASO) and Crow Search Algorithm (CSA). The proposed method attains THD as before UPQC is 31%, after UPQC is 3%, load current is 1.42%, and load voltage is 2%. It also achieves a low operation time of 506ms and a low settling time of 0.15s compared to the existing methods. The significant improvement in power quality metrics demonstrates the effectiveness of the proposed SCSO technique.

Weakening characteristics of pile group foundations in clayey soil under vertical cyclic loading: Experimental and numerical investigation

Long-term cyclic loading can substantially reduce the bearing capacity of pile foundations, potentially compromising the structural integrity of offshore foundations. A small-scale model test system for vertical cyclic loading of pile foundations is independently designed. Model experiments and numerical simulations were conducted to investigate the weakening characteristics of four foundation types (i.e., slab foundation, single pile with cap, 2 × 2 pile group foundation, and 3 × 3 pile group foundation) in clayey soil under cyclic loading. The results of both methods demonstrate that 3 × 3 pile group foundations exhibit the greatest resistance to deformation, followed by 2 × 2 pile groups, single piles with a cap, and slab foundations under cyclic loading. Furthermore, a 3D numerical model was developed to simulate the real-world behavior of a pile group foundation for an offshore wind turbine. Results reveal that although the ultimate compressive bearing capacity decreases with higher cyclic loading levels, typical cyclic loads (0.1–0.2) encountered in practice do not greatly affect the long-term bearing capacity of the foundations. The proposed experimental and numerical simulation methods offer valuable insights into the weakening characteristics of pile group foundations under cyclic loading.

Endogenous ethanol- and thermo-tolerant strain from Malaysia pineapple peel: Screening and molecular characterisation

The current study aims to identify an endogenous acetic acid bacterial strain isolated from a Malaysian pineapple capable of tolerating high ethanol and temperatures. A total of 23 strains of presumed acetic acid bacteria were isolated from the pineapple peel waste. Subsequently, three isolates with the highest acid yield were subjected to 16S rDNA sequencing; Acetobacter tropicalis (A. tropicalis), Staphylococcus haemolyticus, and Staphylococcus ureilyticus. Tolerance evaluations against pH, temperature, ethanol, sugar, and acetic acid demonstrated that all three strains tolerated significant temperatures, ethanol, and sugar levels. Based on the results, A. tropicalis possesses the potential to reduce cooling system load during acetic acid manufacture in hot climate regions with a notable acetic acid yield.

Vulnerability-based seismic resilience and post-earthquake recovery assessment for substation systems

The function of substation systems is significantly influenced by earthquakes. To assess the seismic resistance of substation systems and improve post-earthquake recovery efficiency, this study constructs a multi-module framework for seismic vulnerability assessment of substations. Based on the equipment functional status analysis module, a functional network model was established considering the structural function and electrical load of substation systems. The system functional state matrix was obtained through Monte Carlo simulation, and the seismic vulnerability was assessed from the aspects of electrical transmission reliability and the importance of power users. Subsequently, a substation functional index was established based on seismic vulnerability parameters. Post-earthquake functional recovery strategy analysis frameworks were constructed to quantitatively evaluate the recovery process. A stepped functional time-varying function was proposed through iterative analysis, thereby converting the probability parameters of functional status into seismic resilience deterministic indices. Through seismic resilience analysis of a typical 220 kV step-down substation, seismic vulnerability curves for both electrical transmission and power users were obtained. Furthermore, the seismic sensitive intervals of the substation and key equipment for post-earthquake recovery were clarified. Notably, the seismic resilience level and optimal recovery strategy of the typical 220 kV step-down substation were determined.

Integrated Energy System Load Forecasting with Spatially Transferable Loads

Integrated Energy System Load Forecasting with Spatially Transferable Loads