Optimization Of Power Factor Research Articles

Thermoelectric power factor optimization in hydrothermally synthesized SnO2 nanoparticles by Cu doping

Thermoelectric power factor optimization in hydrothermally synthesized SnO2 nanoparticles by Cu doping

Power Factor Optimization with Cos Phi Mode Trainee

The power factor cos phi measures the efficiency of using electrical power in a system. A low power factor indicates the presence of high reactive power consumption, which can lead to increased energy losses and operational costs. To overcome this problem, an effective power factor regulation system is required. This research designed and developed the Cos Phi Trainer, which operates in two modes, manual and automatic, to improve the power factor at an electrical load. The system is designed to give users a practical understanding of measuring and improving power factors by setting up compensation capacitors. In manual mode, the user directly sets the value of the capacitor used to fix the power factor. While in automatic mode, the system uses current and voltage sensors to measure the power factor value in real-time and automatically adjusts the capacitor to achieve the optimal power factor. The trainer has an easy-to-use interface and a measurement panel that displays important parameters such as current, voltage, active power, reactive power, and power factor. The test results show that the system can significantly increase the power factor in manual and automatic modes. Thus, this Cos Phi Trainer is an effective tool for training in the laboratory of Indorama Engineering Polytechnic and teaching about electrical power management and energy loss reduction in the electrical system. Keywords: Power factor, manual, active power, reactive power, trainer

Optimization of Power Factor for a Screen-Printed Silver Selenide-Based Flexible Thermoelectric Film by Hot Pressing

Optimization of Power Factor for a Screen-Printed Silver Selenide-Based Flexible Thermoelectric Film by Hot Pressing

Simultaneous optimization of power factor and thermal conductivity via charge transfer effect and enhanced scattering of phonons in Si80Ge20P1/CoSi2 composites

SiGe based alloy is a promising medium-high temperature thermoelectric material that has been applied in the field of aerospace exploration. So far, utilizing the second phase to promote the scattering of phonons is a common way to improve the thermoelectric performance of SiGe based alloy, but this often deteriorates the electrical properties. In this study, the Si80Ge20P1/CoSi2 composites have been prepared by mechanical alloying and spark plasma sintering, and the content of cobalt silicide (CoSi2) nanoparticles have been manipulated. Since the CoSi2 nanoparticles possess higher carrier concentration and smaller work function than the Si80Ge20P1 matrix, the carrier concentrations of composites have been pushed up due the charge transfer effect. Meanwhile, the formation of nano-sized phase interfaces and stacking faults in the composites has enhanced the scattering of low-frequency phonons. As a result, the optimal power factor of 3.41 mW⋅m−1⋅K−2 and thermal conductivity of 2.29 W⋅m−1⋅K−1 have been achieved, and the corresponding zT reaches up to 1.3 in the Si80Ge20P1+0.5% CoSi2 (in mole) composite at 873 K. This work provides a new idea for developing the performance of SiGe based alloy.

Data Power Optimization Algorithm for Downlink Multi-ARS Small Cell Communication Systems

In this paper, we investigate a novel downlink Small Cell (SC) system based on the Cell Free (CF) model,with the deployment of Unmanned Aerial Vehicles (UAVs) as Aerial Relay Stations (ARSs) simultaneously serving users in a specific area. The new SC model concept is expressed in the user-centric idea that the user will choose only one ARS with the best conditions for communication, and the concept of “cell" or “cell boundary" will no longer exist. The Time Division Duplex (TDD) mechanism is used for system-wide communication protocol, and the Minimum Mean Squared Error (MMSE) technique is applied for downlink channel estimation. We establish the downlink user throughput expression and then propose a Bisection optimization algorithm to control power for downlink data transmission to improve system quality and save energy. We evaluate the downlink multi-ARS SC communication system with and without power optimization in different aspects, such as altering the number of users, the number of ARSs, the number of antennas, and the transmission channel estimation interval. The results also reveal that the system quality is significantly improved when applying the downlink power factor optimization problem

Multi-objective distributed generation integration in radial distribution system using modified neural network algorithm

This paper introduces a new approach based on a chaotic strategy and a neural network algorithm (NNA), called chaotic-based NNA (CNNA), to solve the optimal distributed generation allocation (ODGA), in the radial distribution system (RDS). This consists of determining the optimal locations and sizes of one or several distributed generations (DGs) to be inserted into the RDS to minimize one or multiple objectives while meeting a set of security limits. The robustness of the proposed method is demonstrated by applying it to two different typical RDSs, namely IEEE 33-bus and 69-bus. In this regard, simulations are performed for three DGs in the cases of unity power factor (UPF) and optimal power factor (OPF), considering single and multi-objective optimization, by minimizing the total active losses and improving the voltage profile, voltage deviation (VD) and voltage stability index (VSI). Compared to its original version and recently reported methods, the CNNA solutions are more competitive without increasing the complexity of the optimization algorithm, especially when the RDS size and problem dimension are extended.

Balanced Dual-Side LCC Compensation in IPT Systems Implementing Unity Power Factor for Wide Load Range and Misalignment Tolerance

Misalignment tolerance and wide load range capability are necessary for a practical inductive power transfer (IPT) system. In pursuit of high-performance, input unity power factor and high efficiency are expected. In this paper, a balanced design method of dual-side LCC compensation is proposed to achieve input unity power factor over wide misalignment and load ranges. With the proposed method, dual-side LCC compensation is in a balanced state where zero phase angle frequencies coincide with designed voltage gain frequencies under coupling and load variations. Unity power factor can be implemented while maintaining voltage gain with frequency control. Possible output power versus frequency characteristics of this balanced dual-side LCC compensation are categorized and fully analyzed. One of them, with strong power regulation capability and high misalignment adaptability, is selected as the design target. Coil currents are optimized using a surplus degree of design freedom while selecting parameters. Unity power factor and coil current optimization ensure low losses in devices and coils, which benefits system efficiency. Thus, a wide load range, high misalignment tolerance, nearly zero reactive power, and high efficiency can be simultaneously implemented. The proposed method is verified on a 2.1kW prototype. The coil size of both primary and secondary sides is 600mm <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">×</i> 600mm, and the air gap is 150mm. Load power varies from 10% to 100% within the coupling range from 0.15 to 0.35. Nearly unity power factor is realized under various working conditions. The maximum dc-dc efficiency reaches 96.4%.

Alternatingly Stacked Low‐ and High‐Resistance PtSe2/PtSe2 Homostructures Boost Thermoelectric Power Factors

Abstract2D transition‐metal dichalcogenide (TMDC) materials are promising candidates with excellent thermoelectric (TE) properties owing to their low dimensionality in electronic and phonon transport. However, the considerable coupling of the Seebeck coefficient and electrical conductivity in such TE materials eventually results in the limit of the TE power factor increase, which severely hinders potential TE device applications. Herein, an alternative approach is demonstrated for breaking the strong coupling between the Seebeck coefficient and electrical conductivity in single TE materials by adopting a novel stacked PtSe2/PtSe2 homostructure. By alternately piling low‐resistance (LR) PtSe2 (3 nm) onto high‐resistance (HR) PtSe2 (2 nm) as one unit, the Seebeck coefficient and electrical conductivity of such stacked homostructures can be greatly enhanced with slightly improved electrical conductivity, ultimately resulting in a TE power factor in three‐unit‐stacked homostructures that is ≈1,648% higher than that of a single PtSe2 (15 nm) layer with the same thickness. This enhancement is attributed to an independent increase in the Seebeck coefficient, which depends on the interface among the LR and HR PtSe2 layers. The findings pave the way for a method that, unlike power factor optimization in conventional thermoelectric materials, can only utilize the Seebeck coefficient and electrical conductivity of each layer in a stacked homostructure.

Covert Wireless Communication With Noise Uncertainty in Space-Air-Ground Integrated Vehicular Networks

In this paper, we propose a covert wireless uplink transmission strategy in space-air-ground integrated vehicular networks, where the source vehicle transmits its own message over the channel that being used by the host communication system, to avoid being detected by the warden. It is obvious that the data transmission efficiency of the covert communication system is limited due to the co-channel interference. To improve the data transmission efficiency, we consider that the covert communication system adopts improper Gaussian signaling (IGS). We formulate a joint transmit power and IGS factor optimization problem to minimize the outage probability of the covert communication system. The minimum error detection probability of the warden is first analyzed with noise uncertainty, which is used to measure the system covertness. Under the constraints of the quality of service (QoS) of host communication system and the covertness requirement, the optimal transmit power is first derived with proper Gaussian signaling (PGS) scheme. Then, with the approximate outage probability derived under IGS scheme, the optimization problem is solved by jointly designing the transmit power and IGS factor. Finally, we provide extensive numerical results to validate the proposed covert transmission strategy, and demonstrate that the IGS scheme is beneficial in improving the data transmission efficiency in terms of outage probability compared to PGS scheme.

Covert Wireless Communication With Spectrum Mask in Internet of Things Networks

Covert wireless communications aim to hide the existence of transmission behavior from watchful adversaries to enhance security. In this paper, we propose a spectrum mask based covert communication strategy in Internet of Things (IoT) networks, where the overt channels are leveraged to enhance the covertness. Specifically, the legitimate IoT transmitter superimposes its own message on the overt channel to avoid being detected by the warden. We assume that proper Gaussian signaling (PGS) is adopted at the overt channel, and improper Gaussian signaling (IGS) is adopted at the legitimate transmitter to improve the covert transmission performance. To maximize the covert rate of the legitimate IoT system, a joint transmit power and IGS factor optimization problem is formulated under the constraints of covertness requirement. The metric of minimum error detection probability, that represents the worst-case for the legitimate transmitter, is utilized to measure the covertness. By exploiting the piece-wise monotonic properties of the objective function and the constraints, we derive the optimal transmit power and IGS factor pairs in both the IGS and PGS schemes. Finally, extensive numerical results are presented to demonstrate that the IGS scheme can improve the covert rate compared to the PGS scheme under a given covertness constraint.

Degradation of toluene by tube-tube coaxial dielectric barrier discharge: power characteristics and power factor optimization

ABSTRACT In this paper, the power characteristics and power factor optimization were investigated in a coaxial tube–tube dielectric barrier discharge (DBD) reactor. The effects of several parameters, including discharge voltage, discharge length, discharge frequency and gas flow rate on discharge power and power factor have been evaluated. The experiment results showed that higher discharge power can be obtained by increasing the discharge voltage, discharge frequency and electrode length. But for the power factor, with the increase of discharge frequency, the power factor increased firstly and then decreased. Moreover, with the discharge length increased, the discharge frequency when the power factor reached the maximum value reduced. The response surface method (RSM) and artificial neural network (ANN) were used to optimize the power factor, and their results were relatively consistent. The result of the ANN showed that when discharge voltage was 9.58 kV, discharge frequency was 8.69 kHz, discharge length was 15.8 cm, and gas flow rate was 1.5 L/min, the power factor reached the maximum value of 0.362. The degradation experiment of toluene was carried out in the reactor and its degradation effect was analyzed. The toluene degradation rate is positively correlated with the power factor, and the discharge voltage, gas flow rate and initial concentration are also the key parameters to determine the degradation of toluene. When the discharge voltage, gas flow rate, and initial concentration are 10 kV, 70 mL/min, and 50 ppm, respectively, the power factor and toluene degradation rate reach 0.34 and 74.3%.

Optimization of Thermoelectric Power Factor of Bilayer Graphene by Vertical Electric Field

We theoretically investigated thermoelectric (TE) effects in bilayer graphene (BLG) in the presence of a vertical electric field E⊥ based on linear response theory combined with a Green’s function ...

Investigation of Optimal PV Allocation to Minimize System Losses and Improve Voltage Stability for Distribution and Transmission Networks Using MATLAB and DigSilent

Electricity generation from renewable energy sources such as solar energy is an emerging sustainable solution. In the last decade, this sustainable source was not only being used as a source of power generation but also as distributed generation (DG). Many literatures have been published in this field with the objective to minimize losses by optimizing the DG size and location. System losses and voltage profile go hand-in-hand; as a result, when system losses are minimized, eventually the voltage profile improves. With improvement in inverter technologies, PV-DG units do not have to operate at a unity power factor. The majority of proposed algorithms and methods do not consider power factor optimization as a necessary optimization. This article aims to optimize the size, location, and power factor of PV-DG units. The simulations are performed on the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. The methodologies developed in this article are divided into two sections. The first section aims to optimize the PV-DG size and location. A multi-objective function is developed by using system losses and a voltage deviation index. Genetic algorithm (GA) is used to optimize the multi-objective function. Next, analytical processes are developed for verification. The second section aims to further enhance PV-DG by optimizing the power factor of PV-DG. The simulation is performed for static load in both systems, which are the IEEE 33 bus radial distribution network and IEEE 14 bus transmission network. A mathematical analytical method was developed, and it was found to be sufficient to optimize the power factor of the PV-DG unit. The results obtained show that voltage stability indices help minimize the computation time by determining the optimal locations for DG placement in both networks. In addition, the GA method attained faster convergence than the analytical method and hence is the best optimal sizing for both test systems with minimum computation time. Additionally, the optimization of the power factor for both test systems has demonstrated further improvement in the voltage profile and loss minimization. In conclusion, the proposed methodology has shown promising results for both transmission and distribution networks.

Simultaneous Optimization of Power Factor and Thermal Conductivity towards High-Performance InSb-Based Thermoelectric MaterialsSupported by the National Natural Science Foundation of China (Grant Nos. 52002137, 51772109, 51872102, and 51802070), the Fundamental Research Funds for the Central Universities (Grant Nos. 2021XXJS008 and 2018KFYXKJC002), and Graduates’ Innovation Fund of Huazhong University of Science and Technology (Grant No. 2020yjsCXCY022).

Thermoelectric performance of InSb is restricted by its low Seebeck coefficient and high thermal conductivity. Here, CuCl is employed to optimize simultaneously the electrical and thermal transport properties of InSb. The substitution of Cl for Sb results in enhanced electron effective mass, leading to high Seebeck coefficient of –159.9 μV/K and high power factor of 31.5 μW⋅cm−1⋅K−2 at 733 K for InSb + 5 wt% CuCl sample. In addition, CuCl doping creates hierarchical architectures composed of Cu9In4, Sb, Cu2Sb in InSb, leading to a strengthened phonon scattering in a wide wavelength (i.e., nano to meso scale), thus a low lattice thermal conductivity of 2.97 W⋅m−1⋅K−1 at 733 K in InSb + 5 wt% CuCl. As a result, a maximum ZT of 0.77 at 733 K has been achieved for the InSb + 5 wt% CuCl sample, increasing by ∼ 250% compared to pristine InSb.

Power Factor Correction Using Programmable Logic Control Based Rotary Method

The power factor value of an induction motor is low. This power factor value is due to the large reactive power. Therefore, it is necessary to add capacitors to improve the power factor. The addition of this capacitor uses a capacitor bank with the rotary method. This rotary method is expected to be able to improve the low power factor. The method used is to determine the set point of the desired power factor. Then this method will add the value of the capacitor bank if it does not meet the set point. If it exceeds the set point value, this method will reduce the value of the capacitor bank. For programming this method using Programmable Logic Control. Programmable Logic Control can perform real time monitoring. The results of the test method showed that the capacitor bank worked to improve the power factor optimization. From the power factor of the drilling machine 0.54 to 0.86 in the test. Further developments can make capacitor sizes smaller and more varied in order to optimize the power factor.

Design optimization of permanent magnet synchronous motor using Taguchi method and experimental validation

Abstract The critical dimensions of magnet and its positional parameters in a permanent magnet synchronous motor (PMSM) are optimized using Taguchi method. L16 Orthogonal Array (OA) was used in Taguchi method to optimize the magnet width w and thickness t, and magnet position parameters i.e., D1, O1, and Rib. Using the D-optimal design criterion, 52 data points for five factors were selected for optimization of power factor and efficiency using response surface methodology to perform the sensitivity analysis. Regression model for efficiency and power factor are modeled using analysis of variance results. A 1.07 kW capacity PMSM was designed based on the optimized parameters and making use of efficient computational resource, i.e., RMxprt tool of the ANSYS Maxwell software and drive system in ANSYS Simplorer for real time results and performance study. The performance of PMSM in terms of line current, load torque, and efficiency has been verified with the experimental results and the efficiency data available in literature. The results were found to be in a good agreement. Confirmation test results showed that the Taguchi method is very successful in the optimization of permanent magnet synchronous motor dimensions.

Graphitic carbon nitride-bismuth antimony telluride nanocomposites: A potential material for thermoelectric applications

Modified forms of Bi2Te3 system attracts immense importance in thermoelectric generation by providing a green and clean technology for converting low-grade waste heat into electrical energy. Herein, we have explored the potential of a new material graphitic carbon nitride (g-C3N4) for tuning the thermoelectric properties of Bi0·4Sb1·6Te3. The electronic and lattice transport properties of Bi0·4Sb1·6Te3 are effectively decoupled through nanostructuring, modification of carrier concentration through defect engineering and embedding g-C3N4 nanostructures in the bulk material which leads to the synergetic optimization of power factor and suppressed thermal conductivity due to all-scale hierarchical architecture. All the Bi0·4Sb1·6Te3/g-C3N4 nanocomposites exhibit reduction in thermal conductivity and we obtained an ultra-low thermal conductivity of 0.33 W/mK for Bi0·4Sb1·6Te3 nanocomposite with 1% g-C3N4. The simultaneous optimization of electrical and lattice transport properties leads to a marked improvement in figure of merit from 0.295 for pristine Bi0·4Sb1·6Te3 to a peak value of 1.09 for Bi0·4Sb1·6Te3 with 0.50% g-C3N4.

Simultaneous optimization of power factor and thermal conductivity via Te and Se double substitution in Cu12Sb4S13 tetrahedrite

The present study reports the structural, electronic, elastic, and thermoelectric properties of Cu12Sb3.9Te0.1S13-xSex (x = 0, 0.1, 0.5, 0.75 and 1) tetrahedrite. The thermal conductivity was reduced due to charge carrier compensation (by Te), weakening of the Sb-S bond and local chemical disorder (induced by Se), resulting in a low mean sound velocity. Simultaneously, the power-factor was maintained high from an enhancement of the density of states near the Fermi level due to Se. Consequently, a maximum figure of merit ~0.84 at 673 K was achieved for the Cu12Sb3.9Te0.1S12.5Se0.5 sample due to concomitant optimisation of the power-factor and thermal conductivity.

Analysis and design optimization of a low-cost axial flux Vernier machine with SMC cores and ferrite magnets

In this paper, a low-cost high-performance axial flux Vernier machine (AFVM) with soft magnetic composite (SMC) cores and ferrite magnet is proposed, analyzed and optimized. By cooperating with spoke magnet rotor configuration and 3D magnetic flux stator structure, the proposed AFVM can output higher torque compared with the traditional permanent magnet machine though low-cost low-energy-density ferrite magnet and low-permeability SMC material are adopted. The main electromagnetic topology and operation principle of the proposed AFVM are introduced; then, its main dimensions are investigated and optimized by using sequential optimization method. Moreover, a new multilevel Taguchi design optimization which is an improvement of multilevel optimization is proposed for the torque and power factor optimization. Lastly, its main performance of AFVM optimized by the sequential optimization method and multilevel Taguchi design optimization method has been compared with a normal axial flux machine in terms of torque ability, power factor and efficiency based on 3D finite element method.

Material Descriptors for the Discovery of Efficient Thermoelectrics

The predictive performance screening of novel compounds can significantly promote the discovery of efficient, cheap, and non-toxic thermoelectric materials. Large efforts to implement machine-learning techniques coupled to materials databases are currently being undertaken, but the adopted computational methods can dramatically affect the outcome. With regards to electronic transport and power factor calculations, the most widely adopted and computationally efficient method, is the constant relaxation time approximation (CRT). This work goes beyond the CRT and adopts the proper, full energy and momentum dependencies of electron-phonon and ionized impurity scattering, to compute the electronic transport and perform power factor optimization for a group of half-Heusler alloys. Then the material parameters that determine the optimal power factor based on this more advanced treatment are identified. This enables the development of a set of significantly improved descriptors that can be used in materials screening studies, and which offer deeper insights into the underlying nature of high performance thermoelectric materials. We have identified $n_v$$\epsilon_r$ / $D_o^2m_{cond}$ as the most useful and generic descriptor, a combination of the number of valleys, the dielectric constant, the conductivity effective mass, and the deformation potential for the dominant electron-phonon process. The proposed descriptors can accelerate the discovery of new efficient and environment friendly thermoelectric materials in a much more accurate and reliable manner, and some predictions for very high performance materials are presented.