Increase In Power Loss Research Articles

Impacts of Electric Vehicle Charging Station with Photovoltaic System and Battery Energy Storage System on Power Quality in Microgrid

The expected increase in electric vehicles necessitates an expansion in charging stations. However, this increase could introduce issues to the power grid, such as the deterioration of voltage stability and an increase in microgrid loading. To address these issues, innovative solutions are imperative. One potential solution is the implementation of charging control mechanisms. This paper analyzes the impact of a residential charging station on a low voltage microgrid from the power quality point of view using a one-year operation simulation. Thirty-seven charging station scenarios with different locations within the network were examined, including instances with no charging control and various combinations involving charging control, photovoltaic power plant, and battery energy storage system. The simulation results of the charging station without charging control show a decrease in some power quality indicators, such as exceeding voltage change thresholds after charging station connection and increasing power losses. On the contrary, the scenarios implementing charging control and local resources effectively mitigate the adverse effects of charging stations on the microgrid.

Combining multi-step reconfiguration with many-objective reduction as iterative bi-level scheduling for stochastic distribution network

With the increasing penetration of distributed renewable energy (DRE), problems such as voltage violation, increased power loss and load peak–valley fluctuation in distribution network are highlighted. In this paper, we combine multi-step reconfiguration with many-objective reduction to present an iterative bi-level scheduling for stochastic distribution network. In the upper level, a multi-step switching sequence exchange integrated distribution network reconfiguration strategy is developed based on minimization of power loss. In the lower level, a many-objective reduction optimization model is presented to enhance the economy and stability of stochastic distribution network, based on the topology derived in the upper level. The model develops a joint probability distribution using information on the forecast error and coupling to quantify the uncertain risks associated with DRE’s active and reactive power. Simulation of arithmetic cases based on IEEE 33-node, IEEE 84-node, IEEE 119-node and IEEE 136-node systems is carried out, and the simulation results show that the network loss of the two-layer iteration is reduced by 10.13 % and the voltage deviation is reduced by 13.05 %, and the peak shaving and valley filling are improved.

Influence of voltage unsymmetry on energy characteristics of vacuum pump

Deviation and asymmetry of the voltage have the greatest impact on electric drives of production machines and mechanisms. Voltage asymmetry leads to losses that have an electromagnetic and technological component. Studies on the effect of voltage asymmetry on the technological characteristics of working machines and mechanisms have shown that their productivity decreases with voltage asymmetry. However, there are no studies on the influence of spring asymmetry on the energy characteristics of working machines. The purpose of the research is to determine the influence of voltage asymmetry on the power characteristics of vacuum pumps. With voltage asymmetry, constant and variable losses in an asynchronous electric motor change, which cause an increase in energy losses in an asynchronous electric drive. The energy assessment of the electric drive of the vacuum pump was carried out according to the specific consumption of electricity. The influence of voltage asymmetry on the power characteristics of vacuum pumps was studied. The dependence of the specific power consumption on the change in stiffness of the mechanical characteristics of the electric motor, which is caused by voltage asymmetry, is obtained. It was established that slippage and power loss increase with voltage asymmetry. As a result, the specific loss of electricity in the electric drive of vacuum pumps increases.

A Thermal Hydrodynamic Model for Emulsified Oil-Lubricated Tilting-Pad Thrust Bearings

On maritime vessels, external factors such as explosions, collisions, and grounding can cause the emulsification of lubricating oil by seawater pollution, which can affect the lubrication of a ship’s thrust bearing. To explore the influence of the mixed emulsification of lubricating oil and seawater on the lubrication performance of thrust bearings, this study conducted an emulsification experiment, from which the viscosity equation of the oil–water mixture was obtained. A thermal hydrodynamic model (THD) of bearings considering oil–water mixed emulsification was established, and the Finite Difference Method (FDM) was used for analysis. The results show that according to the characteristics of the manifold, the mixture is divided into water-in-oil (W/O) and oil-in-water (O/W). In the W/O flow with higher viscosity, the film thickness becomes higher, but the power loss increases. In the O/W manifold with low viscosity, the thin film easily causes mixed friction. In the demulsification stage of the mixed liquid, the thickness loss of the film is huge, and the collision between the thrust-bearing pad and the inference plate may cause the pad to be ablated. The influence of specific heat capacity on temperature is greater than the temperature rise caused by viscosity.

Design and analysis of an improved voltage‐lift‐based extended quadratic gain boost converter with reduced voltage stress across components

SummaryIncreasing the voltage gain of traditional boost converter topologies necessitates an unsustainable increase in the operating duty ratio. Because of their inherent architecture, these topologies are incapable of shielding their individual components from the detrimental effects of extreme duty cycle operation, resulting in increased power loss and inefficient performance. With the objective of attaining a higher voltage gain at a lower duty cycle, this research presents a new quadratic type boost converter derived from an improved voltage‐lift (IVL) cell and the conventional boost converter (CBC). By including an IVL cell in CBC, the voltage conversion ratio is quadratic in nature, and the steady‐state performances are improved over those of CBC. This proposed architecture includes a few new parts, such as capacitors, diodes, and an inductor but no controllable switches, thus the close loop control stays the same. During the entire range of the duty cycle, the proposed boost topology outperforms the conventional quadratic boost converter (CQBC) in terms of dc voltage gain. In addition, the voltage stresses on devices (such as switch and diodes) and intermediate capacitors are reduced compared with CQBC. In steady‐state conditions, the voltage gain and design expressions of the storage elements are determined using time‐domain analysis. The suggested extended quadratic gain boost converter (EQGBC) stands out because of its multiple benefits over existing step‐up converter topologies. The suggested EQGBC has been tested by simulation and hardware implementation to ensure its key performance features. A laboratory‐scaled prototype is developed, which has the capability of boosting the low input voltage of 12 V to a higher value of 48 V at a switching frequency of 100 kHz. The experimental outputs are in close accord with the simulation findings and mathematical analysis.

Application of modified artificial hummingbird algorithm in optimal power flow and generation capacity in power networks considering renewable energy sources

Today's electrical power system is a complicated network that is expanding rapidly. The power transmission lines are more heavily loaded than ever before, which causes a host of problems like increased power losses, unstable voltage, and line overloads. Real and reactive power can be optimized by placing energy resources at appropriate locations. Congested networks benefit from this to reduce losses and enhance voltage profiles. Hence, the optimal power flow problem (OPF) is crucial for power system planning. As a result, electricity system operators can meet electricity demands efficiently and ensure the reliability of the power systems. The classical OPF problem ignores network emissions when dealing with thermal generators with limited fuel. Renewable energy sources are becoming more popular due to their sustainability, abundance, and environmental benefits. This paper examines modified IEEE-30 bus and IEEE-118 bus systems as case studies. Integrating renewable energy sources into the grid can negatively affect its performance without adequate planning. In this study, control variables were optimized to minimize fuel cost, real power losses, emission cost, and voltage deviation. It also met operating constraints, with and without renewable energy. This solution can be further enhanced by the placement of distributed generators (DGs). A modified Artificial Hummingbird Algorithm (mAHA) is presented here as an innovative and improved optimizer. In mAHA, local escape operator (LEO) and opposition-based learning (OBL) are integrated into the basic Artificial Hummingbird Algorithm (AHA). An improved version of AHA, mAHA, seeks to improve search efficiency and overcome limitations. With the CEC'2020 test suite, the mAHA has been compared to several other meta-heuristics for addressing global optimization challenges. To test the algorithm's feasibility, standard and modified test systems were used to solve the OPF problem. To assess the effectiveness of mAHA, the results were compared to those of seven other global optimization algorithms. According to simulation results, the proposed algorithm minimized the cost function and provided convergent solutions.

Profile Optimisation in Real Distribution Networks (Case Study Long MV Feeder)

Abstract In the dynamic field of power systems, integrating distributed generation (DG) sources like solar photovoltaic (PV) plants is crucial for enhancing reliability and fostering sustainability. However, this integration poses voltage profile management challenges in electrical grids. This study investigates voltage profile optimization in Bosnia and Herzegovina’s Gračanica network, focusing on a medium voltage feeder with 68 buses. Using DIgSILENT PowerFactory software, six scenarios with different configurations of solar plants are analyzed for their impact on voltage profiles and power losses. Results show that while DG integration offers benefits, incorrect sizing or placement can increase power losses. Optimal DG benefits are linked to specific sizes and locations. This research emphasizes the need for balancing PV generation with load demands and provides insights for optimal PV plant size and output to minimize negative impacts. These findings aid energy planners and policymakers in implementing distributed solar PV in medium voltage networks.

Resonant interaction between runaway electrons and the toroidal magnetic field ripple in TCV

This work explains the anomalously high runaway electron (RE) pitch angles inferred in the flat-top of dedicated Tokamak à Configuration Variable (TCV) experiments. Kinetic modelling shows that the resonant interaction between the gyromotion of the electrons and the toroidal magnetic field ripple will give rise to strong pitch angle scattering in TCV. The resulting increase in synchrotron radiation power losses acts as a RE energy barrier. These observations are tested experimentally by a magnetic field ramp-down, which gradually reduces the resonant parallel momentum at which the REs interact with the ripple. Resulting changes in synchrotron emission geometry and intensity are observed using three multi-spectral camera imaging systems, viewing the RE beam at distinct spatial angles in multiple wavelength ranges. Experimental reconstructions of the RE distribution in momentum- and real-space are consistent with kinetic model predictions.

Mitigating the impacts of geomagnetic disturbances on the small signal stability

Geomagnetically induced currents (GICs) caused by geomagnetic disturbances (GMDs) flow through the transformers, which lead to the increase of reactive power loss (QGIC). As reactive loads added to the system, QGIC causes the change of power flow distribution, which connects GMDs with small signal stability. Installing blocking devices (BDs) in the neutral points can reduce the negative effects on the grids. Obtaining the best effect is challenging, because the amplitude and direction of induced geoelectric fields (IGFs) are uncertain and non-stationary. Taking the credibility of damping ratio less than 0.05 as an index, the impact of GMDs on small signal stability is quantitatively evaluated. It is found that when intense GMDs occur, the risk of small signal instability increases significantly. Based on the voltage/damping ratio sensitivity joint feature space, the sensitivity scenario is obtained through scenario clustering. Moreover, upon optimal placement of BDs based on joint sensitivity (JS) scenarios, it is observed that the risk index can be significantly reduced compared to that in constant induced geoelectric fields (CIGF) and varying induced geoelectric fields (VIGF) scenarios.

Grain refinement and high-frequency properties of spark plasma sintered MnZn ferrite

MnZn soft magnetic ferrites are essential materials for energy conversion in power electronics. The rapid development of miniaturized and energy-saving electronics has put forth an urgent need for high-frequency MnZn ferrites. However, the current MnZn ferrites suffer from a rapid decline of permeability and a drastic increase in power loss at frequencies above 5 MHz, which severely limits their use in high-frequency power electronics. In this study, the Spark Plasma Sintering (SPS) technology was used to prepare high-frequency MnZn ferrites. Compared to samples prepared by traditional solid-state sintering, SPS ferrite exhibits superior high-frequency properties with cut-off frequency of 57 MHz, and a power loss of 169.6 kW/m3 at 20 MHz. The improved high-frequency performance is due to the monodomain structure which is induced by grain refinement via spark plasma sintering. This study presents an effective method for manufacturing high-frequency soft magnetic ferrite and will promote the development of high-performance power electronics.

Abstract 12955: Shear-Dependent Changes in Blood Viscosity Negatively Affect Energetic Efficiency in Patient-Specific Models of the Fontan Circulation

Introduction: Since blood flow through the lungs is passive in patients with the Fontan circulation, cardiac output is sensitive to power loss through the pulmonary vasculature. Prior small in vitro studies of how changes in blood viscosity at venous shear rates (“non-Newtonian behavior”) affect power loss have yielded conflicting results. The purpose of this study was to evaluate the extent to which non-Newtonian behavior contributes to power loss in a large number of pediatric patient-specific models of the Fontan circulation. Hypothesis: Shear-dependent changes in blood viscosity cause increased power loss in the low-shear Fontan circulation. Methods: Pulmonary vascular geometry was segmented from clinical cardiac MRI images. Pressure and velocity fields were then calculated using computational fluid dynamic simulations. Cardiac index was set at 2 L/min/m2 to simulate a low cardiac output state. A constant viscosity model (“Newtonian”) was compared to a shear-dependent viscosity model (“non-Newtonian”). Power loss was calculated by simplified power loss (using bulk flow and pressure changes) and viscous dissipation rate (using element-wise shear rates and viscosities). Both metrics were indexed to adjust for cardiac output and body surface area. Wilcoxon signed-rank test was used to compare differences between the two viscosity models. Results: Twenty patients (mean 10.9 years, 35% female) were included. Mean viscosity was nearly 10-fold higher in the non-Newtonian vs. Newtonian simulations (mean non-Newtonian to Newtonian viscosity ratio 9.7, SD 0.6). Accordingly, power loss by both metrics was significantly larger for the non-Newtonian simulations ( Figure ). Conclusions: Shear-dependent increases in blood viscosity cause increased power loss in computational models of the Fontan circulation under low cardiac output conditions. Further studies are needed to evaluate the degree to which this correlates with clinical outcomes.

Dynamic reconfiguration of three‐phase imbalanced distribution networks considering soft open points

AbstractThe characteristics of three‐phase imbalances are present in medium‐ and low‐voltage distribution networks. Integrating single‐phase distributed generation (DG) exacerbates network imbalances, resulting in increased power losses and potential safety hazards. To address these issues, a dynamic reconfiguration strategy (DNR) for three‐phase imbalanced distribution networks, considering soft open points (SOP), has been proposed. The objective is to alleviate the three‐phase imbalance and minimize the operational costs of the distribution network. Within the reconfiguration strategy, the constraints of DG current imbalance in practical system operations are considered. A three‐phase imbalanced DNR model that simultaneously considers the constraints of the SOP and DG current imbalances is introduced. This model aims to optimize the operation of all devices, including the SOP, to address the overall imbalance of the distribution network. This enables the authors to transform the non‐linear model into a mixed‐integer linear programming (MILP) model, significantly improving the solution efficiency. To validate the proposed strategy, simulations of a modified IEEE 34‐node distribution system and an actual 78‐node distribution system were conducted. The results demonstrate that this strategy offers significant economic benefits and ensures the security of the distribution network.

Multi-objective energy management of island microgrids with D-FACTS devices considering clean energy, storage systems and electric vehicles

Abstract The development of microgrids is progressing due to intelligent load demands, clean energy, batteries and electric vehicles. The presence of such systems in microgrids causes power balance inconsistency, leading to increased power losses and deviation in voltage. In this paper, a mixed-integer non-linear programming model is proposed for modelling island microgrid energy management considering smart loads, clean energy resources, electric vehicles and batteries. Similarly, a flexible distributed AC transmission system device is proposed to prevent voltage deviation and reduce power losses. A scenario-based multi-objective function has been proposed to decrease energy losses and voltage deviations and energy outages of clean energy resources, reduce emissions from fossil-fired distributed generation and finally decrease load outages to reduce the vulnerability of the islanded microgrid. Regarding the proposed mixed-integer non-linear model and the high number of variables and constraints, a modified evolutionary algorithm based on particle swarm optimization has been proposed to solve the proposed model, which can be more efficient than other algorithms to achieve global optimal solutions. The model presented is implemented on a 33-node island microgrid and the results illustrate that the proposed algorithm and model are effective in reducing energy losses and voltage deviation, as well as reducing the vulnerability of the microgrid. The simulation results demonstrate that the proposed approach can lead to significant improvements in the performance of the microgrid. Specifically, the approach can result in a 27% reduction in losses, a 6% reduction in pollution and a 31% improvement in voltage. Additionally, the approach allows maximum utilization of renewable energy sources, making it a promising solution for sustainable energy management.

ZVS Soft Switching Operation Region Analysis of Modular Multi Active Bridge Converter Under Single Phase Shift Control

Modular multi active bridge (MMAB) converter can provide multiple dc ports using modular H-bridge. When voltage conversion ratios of each port are not equally balanced, zero-voltage-switching (ZVS) turn-on of power semiconductors in the MMAB converter cannot be secured under single phase shift (SPS) control, increasing power loss and leading to lower efficiency. To estimate the efficiency of the converter in various conditions, ZVS operation region of MMAB converters under SPS is comprehensively derived based on steady-state time domain with superposition theorem. Voltage conversion ratios are taken as main variables for ZVS region analysis and influences of them are comprehensively analyzed. Full ZVS regions and constrained ZVS regions are obtained by ZVS discriminants. Simulation and experimental results for a three-port MMAB prototype are given to verify the theoretical analysis of ZVS operation region.

A new study on the prediction of the effects of road gradient and coolant flow on electric vehicle battery power electronics components using machine learning approach

Transistor and diode junction temperature is an important factor in battery electric vehicle systems. High junction temperatures can lead to increased power losses and reduce the efficiency of the power conversion process. Additionally, high junction temperatures can accelerate the degradation rate of lithium-ion batteries, leading to capacity loss, increased internal resistance, and reduced overall battery life. In this study, the parameters affecting the transistor and diode junction temperatures of the battery group, which is the most important component of a battery electric vehicle, have been extensively analyzed and estimated by the machine learning approach. An artificial neural network (ANN) model has been established to estimate the parameters affecting the transistor and diode junction temperatures. The Bayesian regularization algorithm is preferred as the training algorithm in the ANN structure with multilayer perceptron architecture. There are 20 neurons in the hidden layer of the neural network established with a total of 242 data sets obtained from the literature. 80 % of the data set was employed for the training of the model and 20 % for the testing phase. The ANN model's calculated performance parameters were 8.81E-01 for mean squared error (MSE) and 0.91739 for coefficient of determination (R) value. The proposed ANN model was able to successfully predict the parameters affecting the transistor and diode junction temperatures with an average proportional deviation of less than 0.038 % from the actual values. This study can be considered a pioneering study both in terms of cost and time for production practice and in terms of its contribution to the literature.

Vortex model of the aerodynamic wake of airborne wind energy systems

Abstract. Understanding and modeling the aerodynamic wake of airborne wind energy systems (AWESs) is crucial for estimating the performance and defining the design of such systems, as tight trajectories increase induced velocities and thus decrease the available power, while unnecessarily large trajectories increase power losses due to the gravitational potential energy exchange. The aerodynamic wake of crosswind AWESs flying circular trajectories is studied here with vortex methods. The velocities induced at the AWES from a generic helicoidal vortex filament, trailed by a position on the AWES wing, are modeled with an expression for the near vortex filament and one for the far vortex filament. The near vortex filament is modeled as the first half rotation of the helicoidal filament, with its axial component being neglected. The induced drag due to the near wake, built up from near vortex filaments, is found to be similar to the induced drag the AWES would have in forward flight. The far wake is modeled as two semi-infinite vortex ring cascades with opposite intensity. An approximate solution for the axial induced velocity at the AWES is given as a function of the radial (known) and axial (unknown) position of the vortex rings. An explicit and an implicit closure model are introduced to link the axial position of the vortex rings with the other quantities of the model. The aerodynamic model, using the implicit closure model for the far wake, is validated with the lifting-line free-vortex wake method implemented in QBlade. The model is suitable to be used in time-marching aero-servo-elastic simulations and in design and optimization studies.

Разработка системы управления компенсатором реактивной мощности преобразователя частоты для управления гребным электродвигателем

Object and purpose of research. The control of the operating modes of the propulsion electric motor (PEM) is carried out by semiconductor frequency converters, the use of which significantly worsens the quality of electricity on the common buses of the Marine Power Systems. The main reasons are a decrease in the power factor and the appearance of higher harmonics in the consumed current. As a result of this, the reliability of consumers' operation decreases, and power losses increase. Therefore, reducing these negative consequences is an urgent task. Materials and methods. Methods of theoretical electrical engineering, power theory were used. Main results. The method of operation of the reactive power control device for ensuring the quality of electricity, increasing the power factor and filtering higher harmonics in Marine Power Systems was considered and proposed. Conclusion. To ensure the quality of electrical energy of the reactive power compensator, it is necessary to use modern pulse-modulation control algorithms with direct microprocessor control.

Degradation-Sensitive Control Algorithm Based on Phase Optimization for Interleaved DC–DC Converters

As the use of interleaved DC–DC converters in electric vehicles (EVs) increases, research on reliability improvement is required. In the case of interleaved DC–DC converters, degradation occurs between transistors and capacitors. In particular, transistor degradation imbalances cause an increase in output capacitor RMS current, which increases power loss and accelerates capacitor degradation. This degradation affects system reliability by increasing thermal stress. In this paper, based on a degraded 2-leg interleaved DC–DC boost converter, research to reduce the converter’s output capacitor RMS current was conducted. The output capacitor RMS current according to the transistor degradation imbalance was analyzed. As a result, it was confirmed that the transistor degradation imbalance causes an increase in the capacitor RMS current. To address this issue, a phase optimization algorithm for reducing increased capacitor RMS current is presented in this paper. Next, the phase optimization algorithm is mathematically analyzed. Finally, its efficacy is proved through simulations and experiments.

Optimization for position and rating of distributed generating units using bacteria foraging algorithm to reduce power losses

Distributed generation (DG) units, which include solar panels, wind turbines, and fuel cells, are gaining in popularity as a result of the fact that they are dependable and produce no harmful emissions when they generate electricity. However, the integration of these new power sources into the current power grid may result in several technical difficulties, including voltage fluctuations, power imbalances, and increased power losses. The use of optimization methods may assist to solve these difficulties by determining the best position and size of DG units. This will help to reduce the amount of power that is lost and will enhance the power system's overall performance. Therefore, the Bacteria Foraging Optimization (BFO) method was used for DG in this study. This approach helps to decrease phase jump during symmetrical and unsymmetrical faults, as well as power losses, controls voltage magnitude and angle, and regulates voltage magnitude. In addition, nonlinear restrictions that are regarded to be forward factors include voltage limitation, DG capacity limitation, and phase jump limitation. On the IEEE 69 bus radial distribution scheme, both single and double DGs are taken into consideration for the allocation process. Because of its worldwide convergence and decreased calculation liability, the BFO algorithm is used in the optimization process for both position and rating. The suggested procedure is tested on the IEEE 69 bus radial distribution system in a MATLAB environment; the results demonstrate the efficiency of the suggested approach. In this case, the proposed system was successful in achieving the triple line-to-ground fault-based phase jump of 26.3° without DG and 0.52° with DG; the line-to-line (AB) fault-based phase jump of 0.01° without DG and 0.001° with DG; the single line (A) to ground fault-based phase jump of 0.0027° without DG and 0.001° with DG; and the line to ground fault-based phase jump of 0.001° with DG.

A novel hybrid algorithm based optimal planning of solar PV and battery energy storage systems

The adoption of renewable energy sources (RES) such as solar photovoltaic distributed generation (SPVDG) has been at its peak in the present decade owing to their positive impact on the environment and the grid. However, these sources’ ratings and placement need to be optimally estimated before their accommodation in the power distribution system (PDS) to prevent increased power loss and voltage profile aberrations. In this article, SPVDG is integrated with battery energy storage systems (BESS) to compensate for the shortcomings of SPVDG, such as intermittency and uncertainty, and to reduce peak demand. This paper presented a novel hybrid algorithm, which is a combination of the enhanced elephant herding algorithm and the Jaya algorithm. This developed algorithm properly controls the searching algorithm from global exploration to local exploitation to obtain the near-global optimum solution. The problem formulation is centered on the optimal accommodation of SPVDG and BESS to alleviate the power loss and improve the voltage profile of the PDS. Further, the voltage limits, maximum current limits, and BESS charge–discharge constraints are validated throughout the optimization process. Moreover, the hourly variation of SPVDG generation and demand profile with seasonal impact is examined in this study. IEEE 69 bus PDS is tested for the development of the presented work. The suggested algorithm demonstrated its effectiveness and accuracy when compared to different optimization approaches in the literature.