System Load Research Articles

Dynamic prediction of overhead transmission line ampacity based on the BP neural network using Bayesian optimization

Traditionally, the ampacity of an overhead transmission line (OHTL) is a static value obtained based on adverse weather conditions, which constrains the transmission capacity. With the continuous growth of power system load, it is increasingly necessary to dynamically adjust the ampacity based on weather conditions. To this end, this paper models the heat balance relationship of the OHTL based on a BP neural network using Bayesian optimization (BO-BP). On this basis, an OHTL ampacity prediction method considering the model error is proposed. First, a two-stage current-stepping ampacity prediction model is established to obtain the initial ampacity prediction results. Then, the risk control strategy of ampacity prediction considering the model error is proposed to correct the ampacity based on the quartile of the model error to reduce the risk of the conductor overheating caused by the model error. Finally, a simulation is carried out based on the operation data of a 220-kV transmission line. The simulation results show that the accuracy of the BO-BP model is improved by more than 20% compared with the traditional heat balance equation. The proposed ampacity prediction method can improve the transmission capacity by more than 150% compared with the original static ampacity.

Study on the coupling mechanism and reinforcement effect of a shield tunnel reinforced by channel steel under side pit excavation

To investigate the internal force and deformation response law and reinforcement effect of a shield tunnel reinforced by channel steel in a pit excavation, a self-developed “hydraulic loading system” is used to conduct a full-size test and numerical simulation analysis on a three-ring staggered-seam assembled tube sheet. The results show that the internal force response of the tube sheet on the excavation side of the pit is complex and sensitive, the internal force is transformed in the direction under different load levels, and the bearing capacity can be effectively increased by 62.5 % through the channel steel reinforcement; the channel steel fails due to weld cracking, and the nonstructural bonding surface is damaged by sliding; and the maximum reinforcing efficiency of the combination of the channel steel and steel plate reaches 45.8 %, making it an economical and reliable reinforcing program.

Future Parabolic Trough Collector Absorber Coating Development and Service Lifetime Estimation

This work presents a study on the optical and mechanical degradation of parabolic trough collector absorber coatings produced through the spray coating application technique of in-house developed paint. The main aim of this investigation is to prepare, cure, load, and analyze the absorber coating on the substrate under conditions that mimic the on-field thermal properties. This research incorporates predicted isothermal and cyclic loads for parabolic trough systems as stresses. Biweekly inspections of loaded, identical samples monitored the degradation process. We further used the cascade of data from optical, oxide-thickening, crack length, and pull-off force measurements in mathematical modelling to predict the service life of the parabolic trough collector. The results collected and used in modelling suggested that cyclic load in combination with iso-thermal load is responsible for coating fatigue, influencing the solar absorber optical values and resulting in lower energy transformation efficiency. Finally, easy-to-apply coatings made out of spinel-structured black pigment and durable binder could serve as a low-cost absorber coating replacement for a new generation of parabolic trough collectors, making it possible to harvest solar energy to provide medium-temperature heat to decarbonize future food, tobacco, and paint production industrial processes.

Strengthening of RC Beam with GFRP Composites in Shear N. B. Bhopale

The rehabilitation, repair and strengthening of existing reinforced concrete (RC) structures is essential due to factors such as aging, steel reinforcement corrosion, construction/design defects, increased service loads demand, seismic events, and advancements in design guidelines. Fiber-reinforced polymers (FRP) are now being recognized as a promising material for the rehabilitation of such structures, through strengthening or repairing. In buildings and bridges, RC sections are commonly found in the form of beams and girders. Shear failure of RC beams is particularly due to its sudden occurrence without warning. Therefore, the utilization of externally bonded (EB) FRP composites for shear strengthening of RC beams has gathered popularity as a structural enhancement technique, primarily due to advantages of FRP composites, such as high strength-to- weight ratio and exceptional corrosion resistance. In addition, FRP repair systems give a cost-saving choice to traditional repair methods and materials. A study was performed to analyse the shear characteristics of RC beams enhanced with continuous glass fiber-reinforced polymer (GFRP) sheets. Reinforced concrete beams externally bonded GFRP sheets subjected to failure using a symmetrical two-point concentrated static loading system. The experimental data obtained included load, deflection, and failure modes of each beam, along with the effect of the number of GFRP layers on the beams The failures observed in strengthened beams typically commence with the debonding of the FRP sheets, followed by brittle shear failure. The shear capacities of these beams were higher than that of the control beam.

Key technologies and applications of collaboration between digital power grid and Internet of Things

AbstractThe integration of electricity technology and information technology, such as the Internet of Things (IoT), enables the construction of new power systems, along with the innovation of application scenarios and business scope. The key technologies of power IoT and the data flow process are summarised first. The IoT technology and application scenario requirements of power generation, transmission, loading, and storage of new power systems are studied. Thus, the nature of the collaborative development of the digital power grid and the IoT is demonstrated from the perspective of data processing in power IoT and application requirements in power systems. The key problems and solutions faced by the power IoT under the digital transformation are described, and the cross‐integration of key technologies and promotion of application scenario innovation are prospected. Finally, the key issues of future technological development were discussed, providing reference ideas for fully leveraging the value of energy and electricity data production factors and promoting the construction of a digital electricity ecosystem.

Hi‐Z fault location identification on low voltage distribution systems using IoT‐based digital twin model computation

AbstractDistribution feeders carry and supply power to industrial, commercial and residential loads from the point where sub‐transmission (33 kV level) ends after stepping down to suitable voltages, such as 11 kV and further down to 400/230 V. In recent times, high impedance (Hi‐Z) faults on distribution systems are creating unique challenges to utilities both from operational and safety perspectives. Most of these Hi‐Z faults occur at distribution voltages of 15 kV or below, with the problem being worse at lower voltages. Hi‐Z fault detection technologies emerged and were developed and incorporated on embedded platforms, such as relays, reclosers and sensors, which protect and monitor distribution systems. Although these technologies can detect Hi‐Z fault on feeders, most of them cannot identify the exact location of the fault. Specifically, there is no solution available in literature for detecting Hi‐Z fault location on low voltage (LV) circuits like 3‐phase 4‐wire 400 V distribution network. In this paper, we introduce a novel and a unique algorithm to identify the location of Hi‐Z faults using proposed smart metres IoT data‐based distribution system load flow and digital twin model representation of the network. Furthermore, a case study on the standard 33 bus LV system clearly depicts the functionality of the proposed algorithm.

The optimization problem of system load balancing and its solution for industrial Internet-of-Things data management

The optimization problem of system load balancing and its solution for industrial Internet-of-Things data management

Online control parameter optimization design for multi-machine coordinated loading system of hazardous substances

To address the parameter instability issues in hazardous materials handling during multi-machine loading and unloading operations, we propose a Full-Scale Smart Parameter Optimization Control (FSPOC) system specifically designed for multi-machine coordination. This system leverages a novel fish scale prediction algorithm tailored for cooperative multi-machine environments. Initially, the fish scale prediction algorithm, inspired by bionic fish scales, is developed to predict future system behavior by analyzing historical data. Building on this algorithm, we introduce a disturbance cancellation control theorem and design a parameter optimization controller to enhance stability in high-dimensional nonlinear spaces. The FSPOC method is then applied to a multi-machine cooperative system, enabling online distributed parameter optimization for complex systems with multiple degrees of freedom. The effectiveness of the proposed method was validated through simulations, where it was compared with two other optimization techniques: Genetic Algorithm-based PID (GAPID) and Chaotic Atomic Search Algorithm-based PID (CHASO). The simulation results confirm the superiority of the FSPOC method.

Dynamic Adaptative Surveillance Training in a Virtual Environment Using Real-Time Cognitive Load and Performance

Dynamic difficulty adjustment of serious games is a field of research seeking to assist participants attain an ideal learning state. To achieve this, the difficulty of a game is adjusted in real-time to approach the capabilities of the player. Many dynamic difficulty adjustment systems only measure a few variables, often solely player performance, and adjust a limited number of in-game aspects. Little research has sought to ascertain if measuring a combination of cognitive load with measures of performance in real-time leads to a more effective dynamic difficulty adjustment system. Building on research which defined ‘mental efficiency’, we conducted a novel experiment to address this gap. This is achieved by comparing two versions of a surveillance training serious game; one a linear approach and the other with our unique cognitive load and performance-based dynamic difficulty adjustment system. Our experiment included n=52 participants (26 per treatment group). The experiment demonstrates that our approach achieved similar performance outcomes with lower cognitive load, in less time than the linear difficulty approach. These results indicate that our system enhances learning capacity and may prove beneficial for future serious games.

Handling Qualities Assessment and Discussion for Helicopter with Slung Load Systems Utilizing Various Sling Configurations

Sling configurations significantly influence the coupled dynamics of the helicopter with slung load system (HSLS), resulting in alterations to handling qualities (HQs) that remain inadequately understood. This study introduces a computer-oriented, generalized method for constructing the HSLS model with various sling configurations. To evaluate the HQs of 1-point, 2-point, and 4-point sling configurations, both the stability and response criteria outlined in ADS-33E and a newly proposed criterion for slung loads towards the updated ADS-33F were employed. Modal analysis was conducted to elucidate the coupled mechanisms of the HSLS under different sling configurations. The findings reveal that the dynamics of the main rotor can attenuate the lateral swing motions of the load in the 4-point sling configuration. While multiple-point sling configurations can enhance the helicopter’s bandwidth, they also amplify the magnitude notch in the helicopter’s response. Nevertheless, when a larger hook distance is employed, the notch frequency is sufficiently distant from the load swing bandwidth, leading to a reduced degradation in HQs. A 4-point configuration with lateral and longitudinal hook distances equal to twice the width and length of the slung load is recommended in practice to achieve sufficient swing stability and mitigate HQ degradation.

A novel order characteristic load shifting policy for load factor improvement, peak reduction, and economical operation of distribution systems

Demand side management (DSM) and demand response programs (DRPs) are widely used economic strategies that insist customers shift or curtail loads to economize the generation cost of the distribution system. These policies often involve tedious calculation processes or optimization tools to calculate the apt amount of load to be shredded or shifted to get a new modified load profile. This paper proposes an order characterized load-shifting policy (OCLSP), which is very easy to calculate and yields a considerable decrease in the peak demand, eventually improving the distribution system's load factor, also known as the peak-to-average ratio (PAR). Unlike other DSM and DR strategies, the proposed approach requires no parameters except the forecasted load demand. The proposed OCLSP is implemented on ten distribution systems from the literature which consists of a 3-, 6-, 7-, 10-, 15- units system, one islanded microgrid (MG) system and four grid-connected MG systems. Initially, the load demand of these test systems is restructured using OCLSP, and thereafter, dynamic economic load dispatch (DELD) is performed to minimize the generation cost of the system. A latest circle search algorithm (CSA) is utilized as the optimization tool. Results show that the generation cost of all ten test systems has been decreased by a considerable amount when their load demand is restructured using the proposed OCLSP. The minimum percentage improvement in the PAR of the ten systems was 2 % and maximum improvement was 60 %. Likewise, the percentage decrement in the peak demand was within 2 % to 37.5 % for the ten test systems and the decrement in generation cost rose up to 16 %. All these parameters were in comparison with the base load demand. Numerical results also corroborate to the efficiency and robustness of proposed CSA.

Development of a loading and diagnostic system to study laboratory earthquakes

Development of a loading and diagnostic system to study laboratory earthquakes

Sharp Waiting-Time Bounds for Multiserver Jobs

Multiserver jobs, which are jobs that occupy multiple servers simultaneously during service, are prevalent in today’s computing clusters. But, little is known about the delay performance of systems with multiserver jobs. We consider queueing models for multiserver jobs in scaling regimes where the system load becomes heavy and meanwhile, the total number of servers in the system and the number of servers that a job needs become large. Prior work has derived upper bounds on the queueing probability in this scaling regime. However, without proper lower bounds, the existing results cannot be used to differentiate between policies. In this paper, we study the delay performance by establishing sharp bounds on the steady-state mean waiting time of multiserver jobs, where the waiting time of a job is the time spent in queueing rather than in service. We first characterize the exact order of the mean waiting time under the first come, first serve (FCFS) policy. Then, we prove a lower bound on the mean waiting time of all policies, which has an order gap with the mean waiting time under FCFS. We show that the lower bound is achievable by a priority policy that we call smallest need first (SNF). Funding: This research was supported in part by the National Science Foundation [Grant ECCS-2145713]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/stsy.2023.0006 .

Development of a Cost-Driven, Real-Time Management Strategy for e-Mobility Hubs Including Islanded Operation

The installation of electric vehicle supply equipment (EVSE) increases demand and peak loads, potentially straining existing energy distribution infrastructure. Dispersed and inadequately planned placement of charging points (CPs) can disrupt the electrical grid, surpass contracted demand thresholds, and require infrastructure upgrades, thereby incurring unfeasible costs for Distribution System Operators (DSOs). In this context, it is necessary to recognize the role of business models in enabling effective electrification of the transportation sector. In response to these challenges, this paper introduces a novel e-mobility hub management strategy, tailored for implementation in the Brazilian context. The proposed strategy revolves around a microgrid configuration encompassing dispatchable and photovoltaic generation, a battery energy storage system (BESS), EVSE infrastructure, and local loads. Moreover, this centralized controller facilitates the implementation of dynamic pricing and demand-response mechanisms, integral to business models seeking to integrate EVSE into the distribution grid. To validate the efficacy of the proposed solution, hardware-in-the-loop (HIL) simulations of the microgrid system are conducted. These simulations, incorporating the centralized controller, serve as a tool for assessing system performance and viability before on-site equipment deployment. Finally, this paper concludes with the insights gleaned from test analysis and its discussion through a selection of the most expressive scenarios, including islanded and connected operation modes.

Justification of the need to search and use pre-nosological markers of functional deviations of posture of children 6-7 years at the stage of formation of student skills

The problem of forming a healthy posture of schoolchildren is in dire need of an effective solution over the past decades. So according to K.I. Khodatskaya, A.A. Kuts, 2020 and others, posture disorders in children of primary school age are 62.8%, and among adolescents 11-15 years old they reach 80-90% of the total number of students. Purpose: theoretically and experimentally substantiate the feasibility of finding and using pre-nosological markers of posture disorders of students 6-7 years old at the stage of adaptation of the musculoskeletal system for school educational loads. The methodological basis of the study was the component analysis of the second variant of the Romberg test, on the basis of which the indicators of stability coefficients of the equilibrium function (EMF) and asymmetry of the equilibrium function (EDF) were calculated. Research methods: theoretical analysis of scientific and methodological literature, dynamic pedagogical observation, Romberg functional test (second option), goniometry of the spine according to V. A. Hamburtsev, stating experiment, statistical methods. Contingent of subjects: the study involved 12 boys 6-7 years old, first grade students of secondary schools of the city, who were assigned to the main group for health reasons. Scientific novelty: for the first time developed a complex of pre-nosological markers of posture for students 6-7 years old, who start school load; A preventive approach to the formation of posture of students 6-7 years old at the stage of adaptation to educational loads is substantiated, criteria that determine the risk group regarding the predicted occurrence of certain functional deviations in the posture state are worked out. The effectiveness of the goniometry method for studying the dynamics of indicators of the morphofunctional state of the spine of students 6-7 years old during the first year of school has been confirmed. The practical significance of the results obtained is that primary school teachers and parents will receive a ready-made toolkit based on innovative technologies for carrying out specific health-saving work in the direction of forming the posture of children 6-7 years old during the first year of schooling and the entire period of schooling.

Effect of adhesive ductility on the bond behavior of CFRP-steel cohesive interfaces made with toughened epoxy resin

The strengthening of steel structures can be effectively performed using carbon fiber-reinforced polymers (CFRP) plates. Specifically, the behavior of corroded and fatigue damaged steel bridges can be significantly improved using externally bonded (EB) or unbonded composite reinforcements. For bonded composites, the bond between the reinforcement and the steel substrate is the weak link of the system. Indeed, cohesive failure within the adhesive layer represents the main failure mode, which makes the selection of a proper adhesive fundamental to achieve an improvement of the system load carrying capacity and fatigue resistance. Within this context, the use of toughened adhesives represents a promising solution. However, research regarding these adhesives is still limited. In this paper, 18 single-lap direct shear tests are performed to evaluate the cohesive behavior of toughened and traditional adhesives. For some specimens, the full-range bond behavior, including the load response snap-back, was experimentally captured. The digital image correlation (DIC) technique is adopted to evaluate the adhesives cohesive material law (CML). The effect of adhesive ductility, plate stiffness, and bonded length on the joint load response is investigated. Finally, experimental results are validated and discussed against the analytical predictions of a cohesive model based on a trapezoidal CML.

Design of a liposome casein hydrogel as an efficient front-end homeostatic anthocyanin loading system

Proteins have been studied and applied to improve the stability of anthocyanins (ACNs), but the changes in the pH microenvironment during the preparation of steady-state systems are often ignored, and more attention is given to the stability of the system after preparation. In this study, we propose the “anthocyanin front-end homeostasis strategy”, which involves designing a system can protect anthocyanins under acidic conditions so that more anthocyanin prototypes can be loaded inside the protein. Anthocyanins are encapsulated in liposomes (Lip) at pH 3.0 and combined with casein methacrylate (CSMA) to form Anthocyanin-loaded liposomes/CSMA hydrogel (Lip@ACNs/CSMA), with good physical properties and good blood compatibility. The system increased the hydrogen peroxide scavenging capacity by 1.16 mg Vc equiv./mg ACNs and the cellular antioxidant activity by 17.55 μM quercetin/100 mg ACNs, the photo and thermal storage stability increased by 36.50 % and 30.71 %, the digestive rate increased by 17.50 %, and the biological availability increased by 0.0049 mg/mL. This study designed a liposome casein hydrogel as an efficient front-end homeostatic anthocyanin loading system and provided a new approach for improving the stability of anthocyanins.

Adsorption of dinotefuran using TpBDMe COF nanoparticles for soil leaching reduction and bee safety

Dinotefuran (DIN) contaminates groundwater and is toxic to bees, so designing a novel pesticide loading system for dinotefuran is of great significance. In this paper, dinotefuran was loaded into TpBDMe COF with a mesoporous hollow structure, and the TpBDMe COF loaded with dinotefuran exhibited initial burst and subsequent sustained release behavior. The results showed that the product effectively suppresses wheat aphid development, with virtually no infestation occurring for 7–14 days, whereas other commercially available formulation had lost their usefulness. Our TpBDMe COF carrier effectively immobilizes dinotefuran, reducing pesticide leaching in soil by 70 % and enhancing the application efficiency of neonicotinoid insecticides. The LD50 of this product for acute exposure of honey bees doubled the LD50 of the original furosemide at 24 h and was equally effective at 48 h, reducing the toxicity to bees and promoting ecological safety. The results of this work show that this nanocarrier system is highly stable, loadable, insecticidal active, and environmentally friendly, showing great potential in the development of new nanocarriers for use.

Evaluation of bacterial and fungal load of different air conditioning systems in various operating conditions and quantitative microbial risk assessment

Constant monitoring of indoor microbial contamination is crucial due to its direct impact on individuals' health through the inhalation of bioaerosols. This study assessed the bioaerosol content of outlet air from evaporative cooling systems (ECS) and air conditioning splits (ACS) at the Qom School of Health under various operating conditions. The microbial load (CFU m⁻³) was analyzed using the Andersen method, employing separate media cultures for bacteria and fungi. Fungal species and density were determined through staining with Lactophenol cotton blue and microscopic observation. The average fungal load in ECS outlet air (54.56 CFU m⁻³) significantly exceeded the bacterial load (20.30 CFU m⁻³) (p-value <0.01). Increased ECS fan speed correlated with a higher bacterial load, while high salinity and total dissolved solids (TDS) in ECS water reduced microbial growth. Changes to wetted screens increased the microbial load. Aspergillus versicolor and Aspergillus Niger were the prevalent fungal species in ECS, with higher fan speeds associated with increased fungal load. An elevation in ACS temperature significantly reduced the bacterial load in outlet air. Cladosporium and Aspergillus species dominated fungal density in ACS. A comparison between coolers indicated a higher bacterial load in ACS and a higher fungal load in ECS. Washing internal filters reduced the cumulative annual risk of disease according to quantitative microbial risk assessment (QMRA). Given the considerable time spent indoors, indoor contamination poses significant health risks, necessitating continuous monitoring of indoor microbial loads.

Designing an explainable bio-inspired model for suspended sediment load estimation: eXtreme Gradient Boosting coupled with Marine Predators Algorithm

This study aimed to develop an accurate and reliable model for predicting suspended sediment load (SL) in river systems, which is crucial for water resource management and environmental protection. While Xtreme Gradient Boosting (XGB), a powerful ensemble machine learning (ML) model, has been employed in previous studies, the novelty of this research lies in the introduction of a hybrid approach that synergistically combines XGB with the bio-inspired Marine Predators Algorithm (XGB-MPA) to estimate SL in the Yeşilirmak River (Turkey). To this end, streamflow (Q) and sediment concentration (SC) values as well as their lag times (1 to 3 month lag times) were fed as input variables – under 9 scenarios – into ML models. A time series of datasets from March 1973 to December 2011 and January 2012 to March 2023 were used for training and testing of ML models, respectively. The superiority of the proposed model (XGB-MPA) compared to two other hybrid models, including XGB-PSO (Particle Swarm Optimization) and XGB-GWO (Grey Wolf Optimization) was also investigated. According to the results, the simultaneous application of Q and SC lag time values as inputs has led to the best SL estimates by XGB-MPA, with XGB-MPA9 (RMSE = 103.7 ton/day; NSE = 0.96) exhibiting the lowest error rates. In addition, XGB-MPA has performed better than XGB in all scenarios, with the lowest and highest reduction in RMSE being 19.3% (scenario 5) and 97.4% (scenario 1), respectively. When comparing the performance of hybrid models, the proposed XGB-MPA model has performed best with MAE, RMSE and NSE of 40.94, 103.7 and 0.96, respectively, in comparison with 816.02, 1063.74 and −2.94 for XGB-PSO and 693.16, 981.68 and −2.37 for XGB-GWO. Further research can include the use of time series of efficient variables extracted from satellite images (e.g. land cover, river morphology, etc.) as model inputs. Highlights Improvement of SL estimation by coupling MPA with XGB model Using delayed combinations of streamflow and sediment concentration as model inputs Superiority of MPA compare to PSO and GWO in SL estimation Greater variations in SHAP caused by sediment concentration compared to streamflow Further studies required on the effects of hydrological and topographical features