System Load Research Articles

Optimization Method for Topology Identification of Port Microgrid Based on Line Disconnection

Regarding the static voltage stability issue of microgrids, by considering the control of line disconnections to enhance the system load margin, an identification and optimization approach for grid topology control measures based on the parameters of disconnected lines is put forward. Linear sensitivity is employed to scan and filter the measures; nonlinear fitting is utilized for ranking the measures; the leading control measures are calculated to determine the optimal line disconnection control measure. With the real lines and equipment conditions of LEKKI Port in Nigeria as a reference, experiments and simulations are conducted using ETAP and tested in the actual engineering of the port. The results indicate that the optimization method can significantly reduce the time required for load margin calculations in the project, and the effect of the method is similar to that of the traditional continuation power flow (CPFLOW) method. The method is more suitable for the application of online algorithms, which requires speed.

A nano drug delivery system loading drugs and chlorin e6 separately to achieve photodynamic-chemo combination therapy.

To develop a new drug delivery system (DDS) that can load chemotherapy agents and photosensitizer chlorin e6 (Ce6) onto the pores and surfaces of mesoporous silica nanoparticle (MSN) separately. Doxorubicin (DOX) was loaded into the pores of MSNs. Then, polyethyleneimine (PEI) was used to coat the surface of MSN to protect DOX, and then manganese dioxide (MnO2) nanoparticles were loaded through adding potassium permanganate (KMnO4) to bind with Ce6. Finally, polydopamine (PDA) was coated and coupled with hyaluronic acid (HA). The synthesized versatile nanoparticle was pH-sensitive and exhibited positive photodynamic therapy (PDT) performance. Besides, it could be observed that the nanoparticles were efficiently taken up by tumor cells through confocal laser scanning microscopy (CLSM) and flow cytometry. Additionally, in vitro experiments suggested that the nanoparticles had pleasing toxicity to various tumor cells and equally positive therapeutic effect when curcumin replaced DOX. Our work suggests that the nanoparticles designed by our strategy have satisfactory combination therapy performance and can enable more chemotherapy drugs to be used in photodynamic-chemo combination therapy.

Optimal turning of a 2-DOF proportional-integral-derivative controller based on a chess algorithm for load frequency control

Load frequency control is necessary for power system management. The power system must maintain a frequency range to ensure power supply stability. System faults and demand fluctuations may cause frequencies to change quickly. System stability and integrity suffer. We are optimizing the two-degree-of-freedom (2-DOF) proportional-integral-derivative (PID) controllers chess algorithm. This article addresses electrical load frequency regulation. We employ classical control theory and current adjustment. It aims for electrical system efficiency and dependability. It checks for errors using integral absolute error (IAE), integral squared error (ISE), integral of time multiply absolute error (ITAE), and integral time squared error (ITSE). Particle swarm algorithm (PSO) compares performance. The IAE of 0.03364, nearly identical to it, shows that chess trumps other algorithms in many scenarios. The chess algorithm's ISE was 0.00035, like PSO's 0.03363. The ISE was 0.00036, indicating PSO's error-reduction capabilities. For the chess algorithm, PSO is 0.07929, and ITAE is 0.07647. This indicates the PSO responds faster to system breakdowns and load changes. Finally, the chess algorithm's ITSE is 0.00072, below the PSO 0.00076. The chess algorithm is better at managing long-term load frequency.

Fractal Characterization and Pore Evolution in Coal Under Tri-Axial Cyclic Loading–Unloading: Insights from Low-Field NMR Imaging and Analysis

Coal resource extraction and utilization are essential for sustainable development and economic growth. This study integrates a pseudo-triaxial mechanical loading system with low-field nuclear magnetic resonance (NMR) to enable the preliminary visualization of coal’s pore-fracture structure (PFS) under mechanical stress. Pseudo-triaxial and cyclic loading–unloading tests were combined with real-time NMR monitoring to model porosity recovery, pore size evolution, and energy dissipation, while also calculating the fractal dimensions of pores in relation to stress. The results show that during the compaction phase, primary pores are compressed with limited recovery after unloading. In the elastic phase, both adsorption and seepage pores transform significantly, with most recovering post-unloading. After yield stress, new fractures and pores form, and unloading enhances fracture connectivity. Seepage pore porosity shows a negative exponential relationship with axial strain before yielding, and a logarithmic relationship afterward. The fractal dimension of adsorption pores decreases during compaction and increases afterward, while the fractal dimension of seepage pores decreases before yielding and increases post-yielding. These findings provide new insights into the flow patterns of methane in coal seams.

An in vitro nanocarrier-based B cell antigen loading system; tumor growth suppression via transfusion of the antigen-loaded B cells in vivo.

B cell-based vaccines are expected to provide an alternative to DC-based vaccines. However, the efficacy of antigen uptake by B cells in vitro is relatively low, and efficient antigen-loading methods must be established before B cell-based vaccines are viable in clinical settings. We recently developed an in vitro system that efficiently loads antigens into isolated splenic B cells via liposomes decorated with hydroxyl PEG (HO-PEG-Lips). Therefore, the purpose of this study was to expand this system in order to achieve another approach to in vivo tumor growth suppression. By using HO-PEG-Lips as a carrier for model antigen OVA along with an adjuvant, α-galactosylceramide (GC), the amount of antigen loading to the B cells in vitro was increased compared with that of both free OVA and free GC. Transfusion of B cells treated with HO-PEG-Lips that encapsulated OVA and GC suppressed the growth of OVA-expressing murine thymoma (E.G7-OVA) tumors in vivo through strong induction of OVA-specific T cells. Under fluorescence microscopic observation, migration of the transfused B cells in the spleens of recipient mice were confirmed. Our results indicate that our novel antigen-loading system could become a promising approach to facilitate the development of cell-based therapeutic cancer vaccines utilizing B cells as alternative APCs.

Universal Analysis Method for Metamaterial-Based Wireless Power Transfer with Arbitrary Energy Source Waveforms: Application to Triboelectric Nanogenerators.

Metamaterial-based wireless power transfer (MM-WPT) analysis has attracted substantial attention due to its great application potential. However, traditional MM-WPT analysis is constrained by frequency domain approaches which are suitable only for infinitely extended periodic signals or fixed-frequency sine waves but not suitable for complex waveforms of various energy sources. This paper presents an innovative time-domain system analysis method for MM-WPT systems tailored to evaluate energy sources with arbitrary waveforms. The foundation of the method is to use the unit impulse response. By convolving this impulse response with any type of excitation source, a temporal waveform of the voltage across the system's load can be obtained. It has demonstrated a high degree of correlation and agreement between theoretical calculations and experimental results for various input waveforms, affirming its validity, precision, and universality. Based on the framework, it is shown that triboelectric nanogenerators can efficiently self-powered transfer wireless energy through MM-WPT systems. Experiments reveal that the energy received is up to 59.6 times higher compared with that of WPT systems without metamaterials. When this system is applied in an implant, it demonstrates a remarkable energy transfer efficiency of 51% through biological tissues. These findings represent a significant breakthrough in optimizing WPT systems for compact and efficient self-powered energy applications.

Voltage profile enhancement of an AVR system using ant lion optimization algorithm

Abstract This paper addresses voltage regulation, which is a critical issue in power systems. The automatic voltage regulator (AVR) plays a crucial role in maintaining voltage regulation within permissible limits The AVR system's dynamic behaviour is improved by applying the Proportional (KP) Integral (KI) Derivative (KD) (PID) controller. The primary challenges of using a PID controller in AVR include difficulties in tuning parameters to handle nonlinearities, load disturbances, and system dynamics, leading to potential instability, overshoot, or slow response. The controller parameters are tuned with Ant Lion Optimisation (ALO) algorithm and Integral Time Absolute Error (ITAE) as an objective function. Also, the proposed system has the ability to improve the transient response of AVR by decreasing the maximum overshoot, settling time, rise time, and peak time magnitudes of the generator terminal voltage with eliminating the steady state error. Once the suggested method had produced the best values for the three gains i.e., KP, KI, and KD of the PID controller, a transient response analysis is examined and compared with some of the existing techniques such as Bat Algorithm (BA), Grey Wolf Optimisation (GWO) and Biogeography Based Optimisation (BBO) algorithm to highlight the novelty of the proposed ALO optimized PID controller. Transient response analysis, root locus analysis, and bode analysis are used to assess the AVR system's stability. Comparisons to three well-known optimization techniques corroborate the findings. The results show that this new suggested method performs exceptionally well even when there are significant variations in power system parameters and load uncertainties.

“One Pot” Enzymatic Synthesis of Caffeic Acid Phenethyl Ester in Deep Eutectic Solvent

Caffeic acid phenethyl ester (CAPE) represents a valuable ester of caffeic acid, which, over time, has demonstrated remarkable pharmacological properties. In general, the ester is obtained in organic solvents, especially by the esterification reaction of caffeic acid (CA) and 2-phenylethanol (PE). In this context, the purpose of this study was the use of the “one pot” system to synthesize CAPE through biocatalysis with various lipases in a choline-chloride-based DES system, employing the “2-in-1” concept, where one of the substrates functions as both reactant and solvent. The synthesis process of CAPE is contingent on the molar ratio between CA and PE; thus, this factor was the primary subject of investigation, with different molar ratios of CA and PE being studied. Furthermore, the impact of temperature, time, the nature of the biocatalyst, and the water loading of the DES system was also examined. This ‘green’ synthesis method, which has demonstrated encouraging reaction yields (%), could secure and maintain the therapeutic potential of CAPE, mainly due to the non-toxic character of the reaction medium.

Horizontal Cyclic Bearing Characteristics of Bucket Foundation in Sand for Offshore Wind Turbines

During the service period, the offshore wind turbine foundation mainly bears the wind load from the upper structure and the periodic loads such as wave load and sea currents from the lower structure. Long-term cyclic loads have an important impact on the cumulative deformation, foundation stiffness changes, and horizontal ultimate bearing capacity of the offshore wind turbine bucket foundation. This paper conducts cyclic loading tests on mono-bucket foundations under unidirectional and multidirectional cyclic loading conditions based on the multidirectional intelligent cyclic loading system of offshore wind turbine foundations and analyzes the cumulative effects of the loading direction, vertical load, and drainage status on the mono-bucket foundation during the cyclic loading process, effects of rotation angle, cyclic stiffness, and monotonic bearing capacity of foundation after cycles. The research results show that multidirectional cyclic loading significantly reduces the cyclic cumulative rotation angle of the mono-bucket foundation, and the maximum reduction rate can reach more than 50%. After unidirectional and multidirectional cyclic loading, the bearing capacity of the bucket foundation can be increased by up to 30% and 20%, respectively. At the same time, this paper proposes calculation formulas for vertical load, number of cyclic loading, and normalized cumulative rotation and establishes a calculation method for vertical load and bearing capacity of the foundation after cycles.

Research on optimization of power system load response strategy and cost–benefit analysis based on electricity price algorithm model

Abstract This article proposes an innovative framework that amalgamates deep reinforcement learning (DRL) with cost–benefit analysis (CBA). The enhanced actor–critic DRL algorithm simultaneously addresses short-term price fluctuations and long-term system benefits, facilitating optimization across multiple time scales. Furthermore, it establishes a dynamic, multidimensional CBA model that encompasses a comprehensive evaluation of economic, social, and technological benefits, employing a fuzzy comprehensive evaluation method for quantitative analysis. The integration of DRL and CBA forms a closed-loop system that continuously refines strategy optimization through real-time adjustments of the reward function and evaluation weights. Experimental results validate the efficacy of this approach.

Longitudinal joint in decked bulb‐tee beams for accelerated bridge construction with ribbed GFRP bars: Ultimate load and fatigue evaluation

AbstractAccelerated bridge construction (ABC) techniques have gained prominence due to their potential to minimize construction time and traffic disruptions while enhancing sustainability. This study investigates the use of ultra‐high‐performance concrete (UHPC) and glass fiber‐reinforced polymer (GFRP) bars to address critical challenges in bridge durability and longevity. A novel UHPC‐filled precast deck joint was developed for a decked bulb‐tee (DBT) girder system, utilizing GFRP bars to eliminate corrosion‐related issues typical of steel reinforcement. Two actual‐size, GFRP‐reinforced, precast concrete deck slabs were erected to perform fatigue tests using the footprint of the Canadian Highway Bridge Design Code (CHBDC) truck wheel loading to verify the design. Each slab had 200 mm thickness, 2500 mm width, and 3500 mm length in the direction of traffic and rest over braced twin steel girders. The closure strip between connected precast slabs has a width of 125 mm with a vertical shear key. GFRP bars in the precast slab projected into the closure strip with a headed end to provide a 100 mm embedment length. Two types of fatigue tests were performed (i) accelerated variable amplitude cyclic loading and (ii) constant amplitude cyclic loading, followed by loading the slab monotonically to failure. Results demonstrated the system's superior fatigue performance and high ultimate load capacity, making it a promising solution for durable, efficient bridge construction.

Optimal On-Load Tap Changer Tap Control Method for Voltage Compliance Rate Improvement in Distribution Systems, Based on Field Measurement Data

This paper proposes an optimal control method for the on-load tap changer (OLTC) of a substation’s main transformer (M.TR), to maximize the voltage compliance rate (VCR) in distribution system feeders. The conventional auto voltage regulator (AVR)’s line-drop compensation (LDC) control method struggles with accurately determining load centers and has limitations in managing voltage due to the variability of distributed energy resources (DERs). To address these challenges, this study defines sample number-based VCR (SNB-VCR) as the performance index function to be maximized. The optimal tap positions for the OLTC are obtained using the gradient ascent method. Since the SNB-VCR evaluates voltage compliance using 15 min interval data collected from all the load and DER connection points in the distribution system, the tap position obtained by the gradient ascent method maximizes voltage quality for every feeder included in the system. Using a simulation, it is verified that the proposed tap control method improves the overall voltage quality and reduces the occurrence of overvoltage or undervoltage compared to LDC control. The proposed control strategy offers a practical solution for enhancing voltage management efficiency in modern distribution systems, particularly those with high penetration of DERs.

Analysis of power load composition and study on countermeasures for orderly use of electricity

The electric power industry is the foundational industry of national economic construction and is closely associated with people's lives. The development and improvement of the economy have led to this. Moreover, society has increasingly higher demands for the reliability of power supply and the qualification rate of voltage. Power load control technology is a comprehensive use of modern management, automatic control, computer application and other disciplines to carry out power marketing management, power marketing monitoring, business copy and collection, data collection and other activities of a technology, and substation as a local industrial and agricultural production, life power supply base, the rationality of its design will directly affect the local economic development. To build a new type of power system, achieve the goal of carbon peaking and carbon neutrality, realize the flexible interaction of the new type of power system load, and meet the requirements of the digital transformation of power load management, this paper examines the architecture of the new type of power load management system from the perspective of the concept of the new type of power load management system. Then it focuses on the analysis of several key information and communication technologies, including cloud computing technology and artificial intelligence technology, which support the new power load management system in the power load management system, and introduces the composition of the load management system and the application algorithm, and finally puts forward the future development of the new power

Asymmetry Between Queues with Correlated Service and Correlated Arrivals

It is known that a correlation in either the service or interarrival times causes a deterioration in the performance of a queuing system. This study aimed to determine which of the two correlations—in the service times or in the interarrival times—has a stronger influence on the expected queue length, assuming an identical autocorrelation function in both cases. To achieve this goal, a formula for the expected queue length in a system with correlated arrivals was derived first. This new formula, along with a known formula for the expected queue length in a system with correlated service, was used to compare the influence of the two correlations. Various scenarios were studied, such as cases where the common correlation was positive or negative, where the variance of the service or interarrival time was low or high, and where the system load was low or high. Furthermore, both the time-dependent and the steady-state behaviors of the systems were compared. The following two key observations were made. If the impact of other factors on the queue length is minor, then a positive correlation has a worse effect on the queue length when present in service times than in arrival times. On the contrary, a negative correlation has a worse effect on the queue length when present in arrival times than in service times.

Trading Incentive Mechanism and Response Model for High-Frequency Interaction Between Virtual Power Plants and Main Grid Under Spot Markets

As the energy market moves toward decentralization and high-frequency trading, virtual power plants’ (VPP) involvement in and responsiveness to the spot market — an integration platform for dispersed and renewable energy resources — has grown significantly. The response model and trading incentive mechanism for high-frequency interactions between VPPs and the main grid under the spot market are covered in this study. First, a theoretical analysis of market participation incentives is conducted, taking into account variables, including market participation, response speed, and influence, as well as the design principles of reward and compensation schemes. Second, a data-driven forecasting and optimization model is put out to address how VPPs react in real time to variations in energy prices and system load. There is more discussion about the significance of technical infrastructure, focusing on the integration and optimization of data processing and communication systems. To ensure that VPPs participate in market transactions fairly and transparently, the critical responsibilities of market risk management and regulatory compliance are finally examined. This study combines the viewpoints of market regulation, technology innovation, and economics to offer theoretical underpinning and useful advice for comprehending and maximizing the functions and effects of VPPs in contemporary energy markets.

Leveraging Machine Learning for Enhanced Cloud Computing Load Balancing: A Comprehensive Review

Popularized especially throughout the last decade, cloud computing has significantly changed the approach to the use of computational resources. But load balancing still persists as a very important issue of concern to achieve the right balance in order to optimize the various resources. This review paper aims at discussing the various Machine Learning (ML) techniques that can be used for the improvement of load balancing in cloud computing systems. Therefore, the analysis of the current methods is intended to reveal the advantages of the modern approaches to load balancing and put focus on the shortcomings of the traditional algorithms and the contribution of new machine learning approaches. ML techniques offer dynamic load balancing solutions which can handle the variance of the system load. These techniques mainly involve the use of historical data and applying statistical analysis to arrive at the best decisions thus reducing the time response, server usage, and resource utilization. Further, this paper presents how the state-of-the-art machine learning models can be implemented in the context of cloud environments focusing on the complexity and overhead, data protection, and scalability questions. It continues the review of the most advanced machine learning algorithms in the context of load balancing. Adding several examples of the current case studies and experiment results from the published researches of the recent years, the effectiveness of these techniques has been illustrated in the real cloud context. This paper is concluded with the generalization for the future works where the emphasis is placed for the improvement of load balance of machine learning for more demanding and secured cloud computing service.

Microbial Nitrogen Removal in South San Francisco Bay: Does It Play a Role in Eutrophication Resistance?

The ecosystem response to anthropogenic nitrogen (N) loading in estuarine systems is determined by hydrodynamics, biogeochemical transformation rates, and other system-specific characteristics. Historically, San Francisco (SF) Bay has been an outlier from other estuaries with an unusual resistance to eutrophication, despite having extremely high rates of nitrogen loading. Recent increases in phytoplankton biomass and an unprecedented harmful algal bloom, however, have increased the urgency to understand rates and drivers of nitrogen removal in the system. To assess benthic N cycling rates, we conducted seasonal measurements across nine sites in South and Lower South SF Bay, the two sub-embayments with the highest rates of area-normalized N loading, to determine the rates and potential drivers of denitrification and dissimilatory nitrate reduction to ammonium (DNRA). Denitrification rates averaged 60.6 ± 8.1 µmol m−2 h−1 and were primarily coupled to nitrification. Denitrification rates were positively correlated with DNRA rates and % clay. DNRA rates ranged from 0 to 20 µmol m−2 h−1 and on an annual basis averaged ~ 10% of total benthic nitrate reduction, with a negative correlation to % clay content in the surface sediment. The measured denitrification rates account for the removal of, on average, 14% of N loaded annually to South SF Bay, leaving a sizeable portion for alternate fates (e.g., recycling, export, or burial) and potential for substantial temporal and spatial variability (1–79%). This identifies the relative importance of sediment denitrification in ecosystems characterized by high nutrients and low productivity.

Analysis of the Pollution Load Contribution Rate of Inflowing Tributaries for the Sustainable Management of the Seomjin River (Seombon D)

The total maximum daily load (TMDL) system divides the watershed into unit basins for implementation and evaluates water quality by assessing whether targets have been achieved based on investigated data through continuous monitoring. River water quality is influenced by the amount and type of pollutants entering the river, making continuous monitoring, along with analysis and evaluation, essential for the ongoing development of policies and systems aimed at improving water quality. In this study, basic data for water quality management were gathered by analyzing the pollution contributions of the main river (the Seomjin River) and its tributaries, identifying major pollutant sources, and conducting trend analyses. The delivery pollution load of the Seombon D unit basin, one of the main watersheds of the Seomjin River in South Korea, shows a rapid increasing trend (BOD, 1.2–2.4, 2020), which is different from the trend in the B unit watershed of the Boseong River, also a tributary. The rapid increase is presumed to be due to the characteristics of Seombon D, including the inflow of pollution sources of Seombon C, an upstream point. The D unit basin of Seombon is located in the middle of the unit watersheds that divide the main stream of the Seomjin River in Korea into A, B, C, D, E, and F. This increase is thought to be due to the inflow of pollutants specific to Seombon D’s characteristics and the influence of the upstream Seombon C unit basin. In the pollution load contribution rate analysis of Seombon D, it was found that the contribution rate from Seombon C, the upstream area (BOD, 38.42–120.08%), was higher than that of the Boseong B unit basin tributary. The self-purification capacity of Seombon D is believed to have contributed to the improvement in its water quality. It is essential to manage the upstream Seombon C unit basin to sustainably improve the water quality of the Seombon D unit basin. Therefore, managing Seombon C is deemed necessary to further enhance the water quality of Seombon D.

Flex vs. Vantage Pipeline™ Flow Diverters: Technical analysis in treating complex fusiform basilar artery aneurysm.

We present a case of an adult patient with a large symptomatic fusiform basilar artery aneurysm. This video demonstrates the ease of deploying the new Pipeline™ Vantage Flow Diverter compared to the Flex model in the same vessel. The Flex and Vantage have different deployment techniques-as using the Flex maneuvering technique on the Vantage may damage the braid. The Vantage stent does not require resheathing, dragging, or system loading. The video shows the operator's hands making multiple adjustments to deploy the Flex, while they deploy two Vantage stents and a LOBO® device occluder before fully deploying the Flex. The Vantage appears to offer a simpler, more streamlined deployment process of mostly unsheathing compared to the Flex flow diverter. Also, the Vantage design might offer a higher aneurysmal occlusion rate with a shorter course of anti-platelet regimen.1 Of note, the Pipeline™ Shield may be a more appropriate option in some cases.

Influence of Potting Radius on the Structural Performance and Failure Mechanism of Inserts in Sandwich Structures

In this study, the mechanical performance and failure modes of cold-potted inserts within sandwich structures were examined, focusing on the influence of the potting radius, while maintaining constant insert radius and specimen characteristics. In this research, destructive testing was used to evaluate the pull out, load-carrying capacity, and failure mechanisms of the inserts. The methods of stiffness degradation and acoustic emissions (AE) were employed for structural health monitoring to capture real-time data on failure progression, including core buckling, core rupture, and skin delamination. The results indicated that increasing the potting radius significantly altered the failure modes and critical failure load of the insert system. A critical potting radius was identified where maximum stiffness was achieved. Beyond this point, insert fracture became the dominant failure mode, with minimal damage to the surrounding core and CFRP skins. Larger potting radii also led to reduced displacement at failure, increased ultimate loads, and elevated stiffness, which were maintained until sudden structural failure. Through detailed isolation and observation of each failure event and with the use of AE data, precise identification of system damage in real time was allowed, offering insights into the progression and causes of failure.