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A mechanical method is presented which helps to recover asphalt mastic from asphalt mixture without any chemical agent. It may be used as a surrogate to the current chemical extraction method when asphalt mastic shall be recovered from the asphalt mixture. The presented approach is based on granulation and sieving techniques. For the purpose of validation, the method is compared to the standard chemical extraction method which uses a chemical agent to recover the asphalt binder from the mineral aggregates. Both methods are compared in terms of recoverable amount of mastic, and of filler/binder ratio, of reproducibility, and of suitability of the recovered mastic sample for subsequent temperature and frequency sweep (T-f sweep) tests using a Dynamic Shear Rheometer (DSR). [ABSTRACT FROM AUTHOR]

Breakdown (BD) voltage is significant in high-voltage power electric machines. Currently, BD voltages are mainly predicted by the semi-empirical formula in strongly inhomogeneous electric fields. However, the equation could not be applied for electrodes with weakly inhomogeneous electric fields. In this paper, positive lightning impulse BD voltages are predicted in various sphere-to-plane air gaps using forms of machine learning such as support vector regression (SVR), Bayesian regression (BR) and multilayer perceptron (MLP). Unlike previous studies, a method is also proposed by introducing streamer propagation characteristics as new features and by removing electric field gradients as unnecessary features to find out how to reduce the feature dimension. The streamer propagation characteristics are suggested to reflect the possibility of a discharge process between electrodes. Predicted voltages from machine learning algorithms are compared with the experimental results and calculated voltages from the semi-empirical formula. Firstly, the predictions from each model agreed well with the datasets. New features were observed to be applied for machine learning algorithms and to be as important as known electrostatic features before discharge. Secondly, predicted BD voltages were more accurate than calculated voltages from the semi-empirical equation in strongly inhomogeneous electric fields. Predictions from each model also agreed well with the experimental results in weakly inhomogeneous electric fields. The prediction accuracy of SVR was better than those of BR and MLP. Machine learning algorithms were also shown to be applied for electrodes with a wide range of inhomogeneities, unlike a semi-empirical method. We expect that the suggested features and machine learning algorithms can be used for accurately calculating BD voltages. [ABSTRACT FROM AUTHOR]

The exponential growth of unpredictable renewable power production sources in the power grid results in difficult-to-regulate reactive power. The ultimate goal of optimal reactive power dispatch (ORPD) is to find the optimal voltage level of all the generators, the transformer tap ratio, and the MVAR injection of shunt VAR compensators (SVC). More realistically, the ORPD problem is a nonlinear multi-objective optimization problem. Therefore, in this paper, the multi-objective ORPD problem is formulated and solved considering the simultaneous minimization of the active power loss, voltage deviation, emission, and the operating cost of renewable and thermal generators. Usually, renewable power generators such as wind and solar are uncertain; therefore, Weibull and lognormal probability distribution functions are considered to model wind and solar power, respectively. Due to the unavailability and uncertainty of wind and solar power, appropriate PDFs have been used to generate 1000 scenarios with the help of Monte Carlo simulation techniques. Practically, it is not possible to solve the problem considering all the scenarios. Therefore, the scenario reduction technique based on the distance metric is applied to select the 24 representative scenarios to reduce the size of the problem. Moreover, the efficient non-dominated sorting genetic algorithm II-based bidirectional co-evolutionary algorithm (BiCo), along with the constraint domination principle, is adopted to solve the multi-objective ORPD problem. Furthermore, a modified IEEE standard 30-bus system is employed to show the performance and superiority of the proposed algorithm. Simulation results indicate that the proposed algorithm finds uniformly distributed and near-global final non-dominated solutions compared to the recently available state-of-the-art multi-objective algorithms in the literature. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) need to be recharged at intermediate locations, such as shopping malls, restaurants, and parking lots, to meet the daily commute requirements of their users. Currently, public electric vehicle supply equipment (EVSE) serve EVs by conventional methods, which can result in long waiting time for users. This issue reduces the travel efficiency of EVs and thus affects user comfort. Most previous research has studied energy consumption and charging cost optimization; however, comparatively less work has focused on waiting time optimization despite its great importance from the EV user’s perspective. In this paper, we formulate the waiting time optimization as a fuzzy integer linear programming problem and propose a novel heuristic fuzzy inference system-based algorithm (FISA) that resolves the objective function and minimizes the waiting time of EVs at public EVSE installations. We developed the underlying fuzzy inference system by defining the membership functions, expert rules, and formulation for obtaining the optimal solution. The novel FISA automates the correlations of the uncertain and independent input parameters into weighted control variables and resolves the objective function in each sampling period to optimize the waiting time for EVs with the most urgent service requirements. A java language-based simulator is developed for a parking lot to evaluate the effectiveness of the proposed FISA. The simulation results indicate higher efficiency of the proposed FISA compared with state-of-art scheduling algorithms. [ABSTRACT FROM AUTHOR]

Improving efficiency with sustainable radial distribution networks (RDNs) is challenging for larger systems and small grid-connected RDNs. In this paper, the optimal placement of DGs with the Harris hawks optimizer (HHO) under seasonal load demands is proposed to simultaneously reduce total active and reactive power losses and minimize bus voltage drops with the consideration of operational constraints of RDNs. HHO is a newly inspired metaheuristic optimization algorithm primarily based on the Harris hawks' intelligent behaviors during the chasing of the prey. Furthermore, the authors have investigated four stages of DGs. The first stage involves the optimal allocation of one DG. The second stage includes an investigation with two DGs, the third stage considers three DGs, and the fourth stage investigates the integration of four DGs. The effectiveness of the applied HHO is validated on IEEE 33 and 69 bus RDNs, and results are analyzed by comparing with the standard optimization methods. The Big-O test is also executed for statistical analysis with standard algorithms. The simulation results reveal the better performance of the applied HHO under different circumstances than other algorithms. Furthermore, the total active and reactive power losses and bus voltage drops are improved by adding more DGs into IEEE 33 and 69 bus RDNs. [ABSTRACT FROM AUTHOR]

The exhaustion of fossil fuel and the greenhouse gas emission are one of the most significant energy and environmental issues, respectively. Photovoltaic (PV) generators and battery energy storage systems (BESSs) have been significantly increased for recent years. The BESSs are mainly used for smoothing active power fluctuation of the PV. In this paper, PV–BESSs integration of two DC/DC converters and one AC/DC converter is investigated and DC-link voltage control to compensate the AC voltage deviation is proposed for the PV‒BESS system in low-voltage (LV) networks.

In this article, a machine learning algorithm is applied for the first time in inductive power transfer (IPT) to find a ferrite core structure with high magnetic coupling between transmitting (Tx) and receiving (Rx) coils for an electric vehicle (EV) wireless charging system. Since formula-based theoretical design is not available due to the nonlinear magnetic field distortion stemming from the presence of the ferrite core in an IPT system, the proposed core structure design has been achieved through finite-element analysis simulation-based data learning. The proposed design methods are so general that they can be applied to any conventional IPT coil design. Furthermore, it can optimize the core structures for high coupling coefficient, mutual inductance, desired magnetic flux density in the specific area, etc. By training only 0.011% data out of the total possible cases, it is verified by simulation and experiment that the ferrite core structure obtained by the proposed method has a mutual inductance that is 0.6% higher than that of the conventional design level in the case of 15 cm distance between the Tx and Rx coils, even though the volume of the ferrite cores are reduced to 90%. Also, a prototype 3.0 kW stationary EV wireless charging system was implemented and showed fairly better performance than a conventional case. [ABSTRACT FROM AUTHOR]

This article presents a current injection power flow analysis and optimal generation dispatch method for bipolar DC microgrids. In bipolar DC systems, despite a certain local voltage being balanced by the converter control, voltage unbalance can occur at buses that are electrically far from the balanced voltage. In addition, from the aspect of system operation, the optimization of operation cost and voltage unbalance has not been fully investigated yet. Herein, for steady-state analysis, the current injection Newton-Raphson power flow for a bipolar DC microgrid is developed using static models of the network, voltage balancer, sources, and loads. Afterwards, the optimization problem is formulated based on voltage sensitivity, which can be obtained from the Jacobian matrix, to reduce the operation cost while resolving the voltage unbalance. The problem of quadratic programming can be solved sequentially to find the final optimal solution. The case study validates that the power flow method is sufficiently accurate compared to the simulation in PSCAD/EMTDC and that optimal generation can be achieved while reducing the operation cost and mitigating voltage unbalance. [ABSTRACT FROM AUTHOR]

In this article, a novel method to calculate the current distribution, which enables the active sidelobe suppression of the magnetic flux density in an synthesized magnetic field focusing (SMF) system, is proposed for the first time. The proposed method calculates the current distribution, which enables further sidelobe suppression and keeping the resolution at the same time, by changing the target magnetic flux density distribution with only one varying parameter. The proposed calculation method is very intuitive and time-efficient compared with the other calculation methods, as it only changes one variable to control the sidelobe with one step of matrix multiplication. With the finite element method simulation, it is verified that the proposed method can suppress the sidelobe with any target Rx point when the SMF system has 14 coils with size of 10 cm × 10 cm, and the synthesis distance is 30 cm. When the field is synthesized at the center, over 90% of the sidelobe is suppressed for maximum case. An figure-of-merit (FoM) is constructed to optimize the system between the resolution increment and the sidelobe suppression, and 79% of the sidelobe is suppressed for the optimized case while keeping the resolution increment ratio below 30%. In addition, it is verified that the method can also be applied to the two-dimensional (2-D) SMF systems. The experimental results were in good agreement with the simulated results when the experimental prototype of the same condition with simulation was utilized, including a case in which the magnetic field is focused at the Rx point other than the center. [ABSTRACT FROM AUTHOR]

A new conductive-plate-integrated inductive power transfer (IPT) system for automated guided vehicles with little output power variation according to air-gap changes between the transmitter (Tx) and receiver (Rx) is proposed. The inductance change of the ferrite core due to variations in the air gap is nullified by a corresponding change in an aluminum plate. Compared to conventional ferrite IPT systems, self-inductance of the proposed Tx coil is little changed against air-gap variations, which results in robust resonant frequency and output voltage. The self-inductance was experimentally verified to remain within 0.45% even when the air gap changes by fivefold from 10 to 50 mm. The output power variation became a twelfth of that of the conventional ferrite IPT for air-gap variations of 30 ∼ 50 mm, where the efficiency was found to be 96.0% when the output power was 1 kW. [ABSTRACT FROM AUTHOR]

In this article, a novel structure of a receiving (Rx) coil with only two coils, which enables omnidirectional wireless power transfer (WPT) for any type of transmitting (Tx) system, is proposed for the first time. The coil adopts each coils into plane cross-shaped ferrite core, with each leg of the ferrite core intersecting both coils. The intersecting direction of the ferrite core for one coil is identical to that of the other one when it is rotated 90 degrees. It is verified that voltage will be induced on at least one coil with any direction of magnetic flux. With an analysis of circuit diagram, it is shown that a high quality factor of each coil can guarantee an omnidirectional power transfer even when the coupling coefficient between two coils has a nonzero value. A simulation model and an experimental prototype is built to verify the omnidirectional WPT of the proposed Rx coil structure, with loop-type Tx coil as an example among various Tx types. Omnidirectional power transfer capability of the proposed coil was verified with a light emitting diode (LED) load. The superiority of the proposed coil was verified by comparison with other Rx coil structures also. [ABSTRACT FROM AUTHOR]

In this article, a simple and cost-effective symmetric sensing coil set to be used for the metal object detection (MOD) in a stationary wireless electric vehicle charger is newly proposed. Compared to the conventional nonoverlapping sensing coil using the magnetic field change detection method, the proposed symmetric sensing coil set design offers the considerable advantage of eliminating all blind zones, i.e., regions where metal is undetectable in the conventional method. Moreover, by reducing the number of layers to one, the fabrication of the proposed sensing coil is easier and more cost effective. The design of the proposed sensing coil is optimized for highly sensitive MOD based on a sensitivity equation and on the finite element method simulations. An experiment conducted with a metal object 40 × 40 mm2 in size and a 20 A transmitting (Tx) coil current verifies the reliability and the blind-zone elimination feature of the proposed sensing coil. [ABSTRACT FROM AUTHOR]

Featured Application: This work is applicable to a secondary control of distributed energy resources in a microgrid without using communication devices. This paper presents a control method for inverter-interfaced distributed generation (DG) and energy storage systems (ESSs) in an islanded microgrid. The proposed method is focused on secondary control, particularly frequency restoration and maintaining the ESSs' state of charge (SOC). To recover frequency deviation due to load change, an ESS is used as a droop-controlled grid-forming source. However, the grid-forming ESS cannot manage its own SOC, since it cannot control its own output power; hence, grid-feeding DGs are used to maintain the SOC within a desired range. Management of the SOC, as well as frequency restoration, is conducted by using local controllers without any communication devices, since dependency on communication may deteriorate system reliability in the case of failure. The proposed method for maintaining SOC can be realized by adjusting the system frequency, which is the only value that can be measured locally with almost the same value at every node in a steady state. Frequency restoration can be achieved by a simple ON/OFF scheme of the integral controller with a hysteresis loop to solve problems caused by differences between frequency measurements or set points among DGs. [ABSTRACT FROM AUTHOR]

Background:Women diagnosed with gestational diabetes mellitus suffer from anxiety and depression, which make controlling blood glucose levels difficult. Introduction:This quasi-experimental study uses a nonequivalent control group pretest–posttest design to investigate the effects of a web-based self-care program on self-care behaviors, anxiety, depression, and blood glucose in patients with gestational diabetes mellitus. Methods:The subjects of the study were outpatients being treated in the Department of Endocrinology at Hospital G, located in Seoul near University C, from July 15, 2015, to December 31, 2016. The experimental and control groups contained 22 participants each. The experimental group received a 12-week web-based program and one session of nutrition education; the control group received nutrition education. Using the SPSS program, pre–post changes in blood glucose, anxiety, depression, and self-care behaviors were examined between the two groups by a repeated-measures ANOVA. Results:After the 12 weeks intervention, self-care behaviors increased in both groups, and blood glucose monitoring increased in the experimental group (p = 0.001). Anxiety in the experimental group decreased by 5.1 points but increased by 1.0 point in the control group (p = 0.048). Depression increased in both groups. Glycated hemoglobin (HbA1C) levels decreased in the experimental group but increased in the control group (p = 0.001). Discussion:In addition to reducing HbA1C and anxiety, the web-based self-care program was effective in increasing the frequency of daily blood glucose monitoring in patients with gestational diabetes mellitus. Conclusions:This study will be helpful in informing an anxiety intervention program, blood glucose control, and healthy self-care behaviors in women with gestational diabetes mellitus. [ABSTRACT FROM AUTHOR]

This paper presents a novel supervisory control method for an islanded hybrid ac/dc microgrid (HMG) with a high renewable energy source (RES) penetration. Droop control can respond to inevitable uncertainties in the load and RES. However, this leads to frequency and voltage deviations, and the generator output power may deviate from the optimal point. To restore the frequency and voltage of both ac and dc grids while reducing generation cost at short time intervals, a model predictive control based optimization problem is formulated to update the set-points of the available resources including the interlinking converter and distributed generators. With the sensitivities, which help to linearly express the frequency and voltage for resource output power, the problem can be approximated to a quadratic programming model. In addition, to consider the effect of the reactive power on the frequency and improve the accuracy, the second-order frequency sensitivity is calculated and applied selectively. The proposed method was tested on a modified IEEE 33-bus system connected to a sample dc grid. The simulation results validate its performance for reliable and economic operation in an islanded HMG. [ABSTRACT FROM AUTHOR]

This paper presents a new generation adjustment method for achieving economical operation of power systems. Uncertainty in the loads and renewable energy sources is inevitable in power systems. The participation factor, which can be calculated using the incremental cost, is generally used to manage such unexpected variations. The incremental cost considers only the generators; however, owing to line loss, the location of the variation may also affect the operation performance. Herein, we introduce a bus-dependent participation factor (BDPF) to precisely reflect the line loss. The BDPF is calculated based on the generation-load incremental cost (GLIC), which is the cost variation for a specific generator and load. The GLIC can fairly reflect line loss changes; in addition, the second-order loss sensitivity is used to improve the accuracy of the BDPF. Using the BDPF, power generation can be instantly adjusted under unexpected variations, after which re-adjustment can be performed, if operation constraint violations exist. The proposed method is tested on the IEEE 14-bus and 118-bus systems, and the simulation results validate its effectiveness. [ABSTRACT FROM AUTHOR]

This paper describes a control method for distributed generation (DG) units to implement active power sharing and frequency recovery simultaneously in an islanded microgrid. Conventional active power–frequency (P –f) droop control is used for the DG controller, and the frequency deviation is recovered by the DG itself via self-frequency recovery control, without requiring secondary frequency control. Because the electrical distance (impedance) from each DG unit to a point where the load demand changes differs among DG units, the instantaneous frequency deviations may differ between DG units. These differences are fed into the integrators of the self-frequency recovery control and may result in errors in active power sharing. To solve this problem and share active power more accurately, a compensation control method is developed for active power sharing, which considers the droop coefficients of each of the DG units. Simulation results show that the proposed control method is effective. [ABSTRACT FROM AUTHOR]

In this paper, we propose a frequency and voltage control strategy for a standalone microgrid with high penetration of intermittent renewable generation systems, which might cause large frequency and voltage deviation in the system due to unpredictable output power fluctuations. To this end, a battery energy storage system (BESS) is suggested for generating the nominal system frequency instead of a synchronous generator, from a frequency control perspective. This makes the system frequency independent of the mechanical inertia of the synchronous generator. However, a BESS has a capacity limitation; a synchronous generator is used to maintain the state of charge (SOC) of the BESS at a certain value. For voltage control, we proposed that a reactive power/active power (Q/P) droop control be added to the conventional reactive power controller. By adding a Q/P droop control, renewable generation acquires a voltage-damping effect, which dramatically alleviates the voltage fluctuation induced by its own output power fluctuation. Simulation results prove the effectiveness of the proposed control strategy from both frequency and voltage control perspectives. [ABSTRACT FROM AUTHOR]

Abstract: In Douglas et al. (2012) [9], the authors investigated a family of quotient Hilbert modules in the Cowen–Douglas class over the unit disk constructed from classical Hilbert modules such as the Hardy and Bergman modules. In this paper we extend the results to the multivariable case of higher multiplicity. Moreover, similarity as well as isomorphism results are obtained. [Copyright &y& Elsevier]