Copper Loss Research Articles

Load forecasting based on multi-core learning Support Vector Machine (SVM)

Abstract The development of smart grids requires enhanced data integration, robust risk assessment, and dynamic response optimization. In this paper, a multi-core learning Support Vector Machine (SVM) model is presented to improve the accuracy and efficiency of load and photovoltaic output forecasting. The model leverages kernel function optimization and parallel computing frameworks to handle large-scale data efficiently. Additionally, a comprehensive risk assessment system is developed to quantify risks such as overvoltage, undervoltage, line overload, and load loss in distribution networks. An adaptive genetic algorithm-based risk control model is also proposed, optimized in two stages—day-ahead and intra-day—to achieve minimal comprehensive risk through real-time adjustments in distributed power output and electric vehicle charging strategies. Furthermore, an integrated virtual synchronous control online verification method for source-network-load-storage is introduced, enhancing system response speed and control accuracy. These innovations collectively provide a solid theoretical foundation and technical support for the efficient and safe operation of smart grids, addressing the increasing demands of modern energy systems.

Heat transfer study on a stator-permanent magnet electric motor: A hybrid estimation model for real-time temperature monitoring and predictive maintenance

When electrical machines operate without a specific cooling system, the surrounding environment plays a crucial role in the rise of temperature and the duty cycle of operation. More clearly, a natural convection cooling system with a low value of heat transfer coefficient carries the risk of thermal breakdown, insufficient safety, and reliability. This paper studies the heat transfer aspects of a low-power flux switching permanent magnet (FSPM) motor under natural convection cooling to implement a novel real-time sensor-less temperature monitoring system. Thermal and electromagnetic experiments are carried out to create foundations for transient and steady-state numerical models. A data-driven, deep learning algorithm estimates the core and permanent magnet (PM) eddy current losses in real-time, besides the already available copper and friction losses. Subsequently, a two-node thermal equivalent circuit in a hybrid model with a feed-forward neural network estimates the dynamic temperature profile of windings and PMs. It is indicated that the worst-case estimation error is below 7.5%, and the configuration is applicable under a wide range of operation states and environmental conditions. Lastly, the system, including the power source, FSPM motor, and hybrid temperature estimation unit, will be implemented in MATLAB/Simulink to investigate the fault prediction and operation management capabilities.

Plasmonic properties of silicon nitride encapsulated copper

We investigated the optical properties (i.e. plasmonic loss) of thin-film copper that was deposited and processed in a 300mm CMOS pilot line. The optical properties at 1550 nm (QSPP,Cu = 3921 ± 350) were evaluated by measuring the propagation loss of dielectric loaded plasmonic waveguides on samples with high and low root mean square surface roughness (Rq) with and without a silicon nitride diffusion barrier and at room temperature and cryogenic temperatures. In our fabrication result, the average grain size is 2.08±0.05μm, which is much larger than the mean free path of free electrons in copper, so the surface roughness becomes the main cause of the waveguide propagation loss from the fabrication constrains. Further, we show that copper can be encapsulated by a 15 nm silicon nitride diffusion and oxidation barrier without degrading the optical properties.

Joint optimal PMU and DULR placement in distribution network considering fault reconstruction and state estimation accuracy

Due to the rapid development of the distribution network, there is an urgent need for high-precision state estimation and safe and stable operation, this paper proposes a joint optimal placement method for Phasor Measurement Unit (PMU) and Dual Use Line Relay (DULR) in distribution networks considering fault reconstruction and state estimation accuracy. The proposed method aims to minimize the cost of PMU and DULR configuration. Based on the known pseudo-measurements and Supervisory Control and Data Acquisition (SCADA) measurements, we use the E-optimal standard design of the state estimation error covariance matrix to form the state estimation accuracy index and take the relay protection function of Feeder Terminal Unit (FTU) device and DULR device into consideration of the fault reconstruction. By solving the mixed integer semidefinite programming (MISDP) model, the optimal placement result is obtained, so that the network under normal condition and the network after multiple fault reconstruction can meet the constraints of state estimation accuracy and load loss rate respectively. The proposed method is tested on IEEE 33-node, 123-node systems as an example. The experimental results show that the proposed method is effective and practical.Note to Practitioners—This study is stimulated by the need for optimizing the placement of Micro-PMU (µPMU) in distribution network. Since the new µPMU device DULR has the same relay protection function as FTU, and distributed generation can supply power to the island after failure, this paper adds the load loss rate to the constraint conditions to study the influence of fault reconstruction on the placement scheme. A new two-step SE method considering mixed measurements was used in this paper to improve the computational efficiency of real-time SE of large-scale system while ensuring the accuracy of the calculation results. We have conducted tests in IEEE-33 and IEEE-123 systems. After preliminary verification, compared with the single fault scenario, we find that the placement scheme considering multiple fault scenarios can effectively improve the accuracy of state estimation and reduce the load loss rate of each fault scenario and only increase the cost a little. The increase in the number of DG and contact lines in the network will also effectively improve the feasibility of the placement scheme. The increase of the number of FTU configurations can effectively reduce the configuration of DULR by adding a small amount of µPMU, reduce the total cost as a result. In future studies, we will further consider the integrated configuration of µPMU, DULR and FTU, to meet more failure scenarios while reducing costs.

EXPERIMENTAL RESEARCH OF THE MAGNETIZATION AND DEMAGNETIZATION PROCESSES OF THE VECTOR-CONTROLLED INDUCTION MOTOR

Experimental research of the processes of magnetization and demagnetization for the motionless vector-controlled induction motor was performed, according to a linear law with a variation in the duration of these processes. The methodology of research during which the orthogonal components of the stator and rotor currents were recorded in the rotor flux reference frame, the rotor flux module and the energy of the total losses in the stator and rotor copper is described. The main characteristics and parameters of laboratory equipment and facilities are given. From the point of view of minimizing copper losses, the existence of the optimal duration of the investigated transient processes has been experimentally proven. The results of experimental studies with high accuracy coincide with calculations based on previously obtained analytical dependencies, which confirms the admissibility of the assumptions made during theoretical studies. References 10, figures 7, tables 2.

Optimized design of a fault-tolerant 12-slot/10-pole six-phase surface permanent magnet motor with asymmetrical winding configuration for electric vehicles

This paper presents a comprehensive methodology for optimizing the design of a 12-slot/10-pole permanent magnet (PM) motor with a six-phase winding configuration tailored for electric vehicles (EVs). The design aims to enhance motor performance under both healthy and fault conditions. While the single neutral configuration offers superior torque during faults, it also introduces zero sequence currents and additional space harmonics, which can lead to increased torque ripple that is difficult to control. This study addresses these challenges through innovative machine design optimization. The optimization process begins with sizing equations to establish an initial design. K-means clustering techniques are then employed to identify distinct loading points that accurately represent the full EV driving cycle, effectively minimizing computational power requirements. Following this, the Full Range Minimum Loss (FRML) strategy is applied to determine optimal current profiles across these loading points, significantly reducing copper losses. Finally, a multi-objective optimization approach is utilized to minimize torque ripple, enhance average torque, and optimize machine losses. The results demonstrate substantial improvements in torque and reduced ripple, validated through experiments conducted with a 2 kW lab-scale motor. This integrated approach not only ensures a robust and efficient motor design but also enhances fault tolerance, making it well-suited for advanced EV applications.

Cost-effective reliability level in 100% renewables-based standalone microgrids considering investment and expected energy not served costs

Loss of load probability (LOLP) and expected energy not served (EENS) are commonly used in electrical power systems to evaluate reliability. LOLP defined as the probability that available generation capacity will be inadequate to supply customer demand. EENS defined as the expected amount of energy not being served to consumers by the system during the period considered due to system capacity shortages or unexpected power outages. Loss of Load Frequency (LOLF) is referred to a number of loss of load (LOL) event happened in the operation life span of the SMG. Loss of Load Reduction (LOLR) is defined as the required reduction in LOLF to obtain a specific reliability level. While power systems are designed to minimize LOLP and EENS, this is constrained by the total cost: investment cost, operation and maintenance cost, and cost of customer interruption (CCI). This research considers Standalone Microgrid (SMG), also known as Autonomous Microgrid which only operates in off-grid mode and cannot be connected to wider electrical power system. When designing a 100 % renewable energy integrated SMGs, it is crucial to determine the cost-effective reliability level (CERL). The CERL occurs when the total cost is minimum. This research proposes an approach to calculate the CERL for a fully renewable SMG. An analytical formulation is proposed to represent the LOLR needed to obtain a specific reliability level as a function of the required size of reliability improvement alternatives. The CCI is evaluated using LOLF and EENS indices. Finally, the total cost of the SMG system is evaluated for each reliability level. Consequently, the total cost of the SMG system is expressed as a function of reliability levels, and the minimum value of total cost and the corresponding reliability level are evaluated. In this research, a Monte Carlo Simulation (MCS) approach is used to find hourly LOLF, considering 25 years (219,000 h) of SMG lifespan, regression analysis is used for an analytical formulation, and mixed integer linear programming (MILP) is used for the investment decision making based on a cost minimisation approach. The result demonstrates that the CERL of the SMG system evaluated in the case study is 98.71 %.

Modelling and optimization of TPMLMs with slotted stators based on Bayesian DNN

AbstractThe Permanent Magnet Linear Motor (TPMLM) is widely used in different industrial fields. TPMLMs with slots and iron cores have high power density, but their thrust fluctuations and copper losses are significant. Due to the nonlinearity and saturation of magnetic circuits, their electromagnetic models are complex and the accuracy of numerical methods is very inferior. Substantially accurate modelling is crucial for motor optimisation design. In this paper, a data‐driven modelling method based on Bayesian optimisation deep neural network (DNN) is proposed to improve the accuracy of the electromagnetic field. The finite element (FE) modelling under different structural parameters is analysed and provides a training dataset for DNN. Then, a multi‐objective optimisation problem for the slotted TPMLM is carried out based on the multi‐objective black hole algorithm. Compared to the original design, the average thrust of TPMLM increased by 49.37%, the thrust fluctuation percentage decreased by 9.59%, and the coil copper consumption percentage decreased by 2.64%. The results show that the improved DNN model has very high modelling accuracy, providing a new way for motor design and optimisation.

Seismic performance of Li-Tie type brick masonry infilled wooden frames considering joint damage: Degradation mechanism and hysteretic model

This paper investigated the influence of the damage to column-foot (C-F) joints and the gaps of mortise-tenon (M-T) joints on the seismic behavior of Li-Tie style timber frames with masonry-infilled wall. Five full-scale Li-Tie type brick masonry-infilled timber frames, two without the joint damage, two with the damage to C-F, and one with the gaps of M-T joints, were cyclically tested. The failure modes, mechanical and deformation mechanisms were revealed. The second-order effect, strength degradation law, and the changing laws of the equivalent viscous damping coefficient and strain of the specimens were analyzed. The results showed that when the maximum inter-layer drift ratio was less than 2.4 %, the second-order effect of Li-Tie type timber structure with the masonry infill can be ignored. The masonry infilled timber frames considering the joint deterioration suffered a large strength degradation degree, and a more significant loss of the peak load and ductility. The equivalent viscous damping coefficient of the masonry infilled timber frame considering C-F damage increased by up to 24.67 %, while that of the one including the gaps of M-T joint decreased by 6.67 %. The C-F damage led to an increase in the strain at the beam end, the damage to M-T joint resulted in an decrease in the strain at the beam end. However, the damage to C-F and the gaps in M-T joint had little influence on the strain distribution in the C-F area. Based on the hysteretic, stiffness and strength degradation characteristics, and tests results of the specimens, the new tri-linear hysteretic models of Li-Tie type brick masonry infilled wooden frames with and without the joint damage were established and verified. Good agreement between the model predictions and test results was observed.

NVH multiobjective and robust optimization of electric motor design, including power losses

As part of electric motor design, compromises between NVH considerations, electrotechnical design and performance targets must be made. Electromagnetic excitation within the airgap results in structure-borne and airborne noise transmission to the vehicle. High-frequency tones are characteristic of this noise. Efficient computation methods exist to estimate these vibration and noise levels. From the early design stage, NVH performance can be diagnosed and optimized. The focus on NVH can no longer be separated from efficiency optimization. Simulation workflows and optimization loops, developed for NVH-related targets, are updated to consider copper and iron losses. The modification of the geometrical design must be addressed to reduce both dynamic excitation and energy loss, or at least offer compromises. Electric motor design optimization requires the handling of multiple objectives and constraints from multiple physics. In addition, design robustness must be ensured as part of the industrial process: manufacturing tolerances have to be considered to define a robust optimized design.

Evaluation of AC Copper Loss Reduction Effect of Magnetic‐Coated Flat Wire

Evaluation of <scp>AC</scp> Copper Loss Reduction Effect of Magnetic‐Coated Flat Wire

Passive damping of several resonances using multi-branch resonant piezoelectric shunts

Vibration damping using resonant piezoelectric shunts is a method to reduce the amplitude of mechanical resonances by coupling an electrical circuit to a structure through a piezoelectric transducer. The shunt consists of an inductor which creates a resonator tuned to the frequency of the mode to be controlled. In order to damp several resonances simultaneously, multi-branch shunts can be used. Multiple electrical lines are then connected to a single piezoelectric patch. In this work, focused on purely passive control, a circuit involving resistors in series with the inductors is considered. Indeed, each wire wound inductor is usually associated with a non-negligible series resistance due to copper losses. Several multi-branch shunt architectures have been proposed in the literature. From a selection based on their feasibility in passive control, two solutions are retained: the Hollkamp shunt and the current blocking shunt. After numerical implementation, the two architectures are compared, notably by evaluating the effect of the inductance variations with respect to their nominal values and highlighting the influence of additional resistors.

Optimal Design and Analysis of High-Frequency Isolation Transformer for Switched-Mode Power Converters

High-frequency (HF) transformers have gained great interest in recent years due to the advent of powerful soft magnetic materials with low core loss in semiconductor power switches. Also, the optimal design of the HF transformer is a significant issue for high-performance energy conversion systems. In this paper, a 40W 50/12.5/25 V universal input and two output discontinuous-conduction mode (DCM) flyback transformer is designed by using mathematical calculations and analyzed via 3D ANSYS/Maxwell simulation including electromagnetic and loss analysis. It is shown that the simulation results accounting for hysteresis losses, eddy current losses, copper losses, and magnetic flux density determine the accuracy of the mathematical model calculation. Analyzes are performed at 100 kHz frequency levels. Results obtained will include core magnetic flux density, core/copper losses, leakage/magnetizing inductances, windings parasitic capacitances, input/output voltage, current values, and all design parameters. Finally, the proposed HF transformer's overall efficiency is calculated and presented. Significantly, the HF transformer achieves 97.8% efficiency thanks to the transformer's core and coil selection, B-H and B-P characteristics, one-to-one dimension design, and mesh operation. The dynamic and mathematical results of the designed transformer demonstrate the design and efficiency success

An Online Torque Sharing Function Method Based on Region Division for Reducing Torque Ripple and Copper Losses of Switched Reluctance Motors

An Online Torque Sharing Function Method Based on Region Division for Reducing Torque Ripple and Copper Losses of Switched Reluctance Motors

Multi-objective optimisation of hybrid renewable energy systems for Colombian non-interconnected zones

Colombia’s Atlantic coast wind and solar resources could enhance energy mix and self-generation. Renewable clean energy has been studied in response to fossil fuel pollution. Wind and solar photovoltaic systems have low initial, operational, and levelized energy costs. Variable wind and sun radiation may limit availability. In this regard, hybrid renewable energy systems (HRES) and energy storage have become crucial. These systems can effectively meet load demand by utilising complementary renewable resources. This study deals with sizing a wind and photovoltaic HRES with storage, using a Particle Swarm Optimisation algorithm for yearly variable resources in a non-interconnected zone in La Guajira, Colombia. The study evaluates the LCOE, probability of load loss, and the system’s CO2 emission. It develops a sensitivity analysis to determine the importance of each objective factor. From a life cycle analysis, an HRES configuration with low LCOE and environmental emission rates is associated with the size of the wind resource; the HRES configuration with minimum LCOE values is close to obtaining higher equivalent CO2e emissions. The study highlights the configuration obtained for the Colombian context, giving more importance to the environmental factor and reaching an LCOE of 0.754 USD/kWh and emission of 18.97 tCO2e/year; this configuration also increases the wind energy generation, reaching 41 % more share, compared to the configuration obtained when the economic factor is a priority.

Day-ahead optimal dispatch method of integrated electric-heat-cool-gas energy system based on N-1 safety criterion

With the continuous development of integrated energy system and the deepening of the coupling relationship between multiple energy flows, the safe and stable operation of the system has received widespread attention. At present, the security of integrated energy system is mostly researched from the perspective of power grid and rarely researched from the perspective of equipment. This study proposes a day-ahead optimal dispatch method of integrated electric-heat-cool-gas energy system based on N-1 safety criterion, which ensures the normal operation of integrated energy system after the failure of a power supply equipment by increasing appropriate amount of power supply. In this study, the changes in equipment power and operating cost before and after equipment failure under the dispatch method considering N-1 safety criterion and the changes in equipment power and operating cost before and after equipment failure under the dispatch method without considering N-1 safety criterion are investigated by numerical simulation. The results show that when a power supply equipment fails, the average daily loss of load is 6139.99 kW for the dispatch method without considering the N-1 safety criterion and the average daily loss of load is 0 kW for the dispatch method considering the N-1 safety criterion. Therefore, the dispatch method considering the N-1 safety criterion performs better in terms of reliability. When a power supply equipment fails, the average operating cost is 5127.71 USD for the dispatch method without considering the N-1 safety criterion and the average operating cost is 4125.56 USD for the dispatch method considering the N-1 safety criterion. Therefore, the dispatch method considering the N-1 safety criterion performs better in terms of economy.

GAS6 as a potential target to alleviate neuroinflammation during Japanese encephalitis in mouse models

Viral encephalitis is characterized by inflammation of the brain parenchyma caused by a variety of viruses, among which the Japanese encephalitis (JE) virus (JEV) is a typical representative arbovirus. Neuronal death, neuroinflammation, and breakdown of the blood brain barrier (BBB) constitute vicious circles of JE progression. Currently, there is no effective therapy to prevent this damage. Growth arrest specific gene 6 (GAS6) is a secreted growth factor that binds to the TYRO3, AXL, and MERTK (TAM) family of receptor tyrosine kinases and has been demonstrated to participate in neuroprotection and suppression of inflammation in many central nervous system (CNS) diseases which has great potential for JE intervention. In this study, we found that GAS6 expression in the brain was decreased and was reversely correlated with viral load and neuronal loss. Mice with GAS6/TAM signalling deficiency showed higher mortality and accelerated neuroinflammation during peripheral JEV infection, accompanied by BBB breakdown. GAS6 directly promoted the expression of tight junction proteins in bEnd.3 cells and strengthened BBB integrity, partly via AXL. Mice administered GAS6 were more resistant to JEV infection due to increased BBB integrity, as well as decreased viral load and neuroinflammation. Thus, targeted GAS6 delivery may represent a strategy for the prevention and treatment of JE especially in patients with impaired BBB.

Propagation Effect Analysis of Existing Cracks in Box Girder Bridges Based on the Criterion of Compound Crack Propagation

Cracking in concrete box girder bridges will have a significant impact on the safety and durability of the structure, and many box girder bridges which are in service have undergone varying degrees of cracking. Currently, the safety design of actual bridge projects place an emphasis on the stress or the load value of a cross section at the limit value specified in the code for safety control. This design method assumes that the member itself is of uniform and continuous material and is internally undamaged. However, the bridge structure is more or less cracked to varying degrees during the period from casting to construction to operation of the concrete members. In this paper, a finite element computational model of a three-span prestressed concrete box girder bridge with existing cracks is established based on the fracture mechanics theory, and the critical parameters of crack extension are introduced to evaluate the extension state of cracks. At the same time, the extended stability of the existing cracks of the box girder bridge is analyzed by considering the temperature effect, vehicle loading, and prestressing loss, and the sensitivity of crack extension under each working condition is investigated. The results show that, with the increase in crack length and depth, the crack expansion is promoted, but the effect is relatively small, and the maximum stress intensity factor is only 6.48 MPa mm1/2. Under the multi-factor coupling effect, the cracks show a composite crack expansion dominated by type I cracks, the longitudinal cracks of the existing base plate are in a stable state, the maximum value of the crack expansion critical parameter of the vertical cracks of the webs reaches 1.087, and there is a tendency to expand locally. The maximum value of the critical parameter for crack extension of the vertical crack in the web plate reaches 1.087, and there is a tendency towards local expansion. The crack extension evaluation criteria proposed in this paper have a certain reference value for crack extension research on similar concrete box girder bridges and provide a scientific basis for the optimized design of similar bridges.

Multi-objective-based economic and emission dispatch with integration of wind energy sources using different optimization algorithms

In this work, a study of economic and emission dispatch issues based on the multi-objective optimization is solved, and generation costs and emissions are reduced by utilizing multi-objective optimization techniques. This optimization is carried out in an IEEE-30 bus system, with and without the integration of wind energy sources, with equality and inequality constraints. The equality constraints are the power balance constraints, stipulating that to have an optimal solution, the generated power must be adequate to satisfy the load demand plus losses. The inequality constraints are a collection of limitations for active power generation, reactive power generation, generator bus voltage, and load bus voltage. To track the hourly load demand, a daily load profile is established using the IEEE-30 bus system. The generation costs and emissions in the system are optimized using multi-objective particle swarm optimization and multi-objective Ant–Lion Optimization approaches. In order to determine the goals’ minimum values, a fuzzy min–max technique is applied. The values that have been minimized are then compared to determine how well wind energy integration has reduced the generation costs and emissions. Two case studies are performed in this work. For Case 1, the total generation costs and emissions using MOPSO are less, with a difference of $42.763, while MOALO has lower emissions, with a difference of 157.337 tons. For Case 2, with the implementation of wind energy, MOPSO has lower total generation costs, with a difference of $51.678, and lower emissions, with a difference of 459.446 tons.

Robust Optimization Research of Cyber-Physical Power System Considering Wind Power Uncertainty and Coupled Relationship.

To mitigate the impact of wind power uncertainty and power-communication coupling on the robustness of a new power system, a bi-level mixed-integer robust optimization strategy is proposed. Firstly, a coupled network model is constructed based on complex network theory, taking into account the coupled relationship of energy supply and control dependencies between the power and communication networks. Next, a bi-level mixed-integer robust optimization model is developed to improve power system resilience, incorporating constraints related to the coupling strength, electrical characteristics, and traffic characteristics of the information network. The upper-level model seeks to minimize load shedding by optimizing DC power flow using fuzzy chance constraints, thereby reducing the risk of power imbalances caused by random fluctuations in wind power generation. Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology-function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. Finally, a modified IEEE 39-bus test system with intermittent wind power is used as a case study. Random attack simulations demonstrate that, under the highest link failure rate and wind power penetration, Model 2 outperforms Model 1 by reducing the load loss ratio by 23.6% and improving the node survival ratio by 5.3%.