Voltage Generator Research Articles

Совершенствование системы регулирования выходного напряжения комплекса «валогенератор – преобразователь частоты»

The article focuses on operation of the ship shaft generator on the joint buses of the main switchboard through a frequency converter that consists of an uncontrolled rectifier and a self-excited inverter with pulse width modulation. The most common schemes of using shaft generators on ships are given, their advantages and disad-vantages are analyzed. There has been illustrated a flowchart and given a detailed description of the operation 
 of a ship electric power plant with power take-off from the main engine. A control system regulating the constant flow interlinkage in the “frequency converter - shaft generator” complex, which ensures stable output voltage, has been developed. It has been stated that a random change in the rotational speed or in a torque fluctuation of the shaft generator rotor have little impact on the quality of generated electricity. Simulation modeling of the complex is given in the MATLAB/Simulink software package. The developed controller of a self-excited inverter supports continuous flow interlinkage by vector control. There has been demonstrated the composition and operation principle of the control system of output voltage of a shaft generator by using vector regulation method. Modeling has proved the availability of the self-excited inverter control system. The oscillograms of modeling the input and output current and voltage values have been obtained. The modeling results justified that changing the input voltage and frequency of the generator provided the high quality output voltage indicators. Harmonic distortion coefficients and static deviations have been analyzed. The expediency of using combined filters of higher harmonics to eliminate interharmonics and higher harmonics in the ship network has been proved. Practical recommendations are given to improve the quality of operation of the ship electrical complex with a shaft generator.

A closed-loop data-driven optimization framework for the unit commitment problem: A [formula omitted]-learning approach under real-time operation

Real-time operation of electric power systems under high penetration of renewable energy generation has to incorporate strategies for managing the uncertainty associated with this type of power sources. In the case of the unit commitment problem, models based on robust optimization have been widely used for the day-ahead computation of power dispatch and reserves schedule. Typical approaches use uncertainty sets with fixed levels of conservativeness, without considering the real-time performance of the solutions. This paper proposes a solution scheme for the adaptive robust unit commitment problem using online adjusted data-driven uncertainty sets. Conservativeness parameters of the uncertainty sets are dynamically calculated as a function of previous operating results and incoming data via reinforcement learning, resulting in an online learning-optimization framework. The paper also develops an experimental framework to simulate real-time operation under the proposed methodology. Out-of-sample experiments illustrate the effectiveness of the proposed scheme against well-known benchmarks with fixed robustness levels. Results show improvements in power generation costs, voltage violations, and use of reserves. Two systems of different sizes are analyzed, illustrating the scalability of the proposed approach.

A New Artificial Neural Network Model for the Output Voltage and Power Predictions of Permanent Magnet Generators with Variable Air Gaps

—An artificial neural network (ANN) model is recommended for the analysis and prediction of the output results of a recently designed and constructed generator known as a permanent magnet generator with axial flux. The generator is considered to generate a power scale of P = 3 kW, especially for off-grid household usage far from the network. This machine has an adjustable air gap mechanism, and P = 3 kW is the maximum power; thus, this power can be decreased comfortably by increasing the air gap further to 7 mm. In this case, the maximum power rate can be decreased to P = 1.5 kW according to the experimental confirmation. As a new technique, an ANN approach is introduced for the predictions of voltage and power obtained output for various electrical loads, rotor speeds, and air gaps because it is difficult to get output values for all those machine parameters. In addition, this ANN technique enables one to find the generated voltage and power for specific extremely low air gap values (i.e., 0.2 mm, 0.4 mm, 0.6 mm), which is hard in experimental work due to construction difficulties. The ANN model is used to predict the output values of the generator before any laboratory practice successfully, and the users can determine the correct air gap ranges to their required power regimes for this generator.

A Wind-Driven Rotating Micro-Hybrid Nanogenerator for Powering Environmental Monitoring Devices.

In recent years, environmental problems caused by natural disasters due to global warming have seriously affected human production and life. Fortunately, with the rapid rise of the Internet of Things (IoT) technology and the decreasing power consumption of microelectronic devices, it is possible to set up a multi-node environmental monitoring system. However, regular replacement of conventional chemical batteries for the huge number of microelectronic devices still faces great challenges, especially in remote areas. In this study, we developed a rotating hybrid nanogenerator for wind energy harvesting. Using the output characteristics of triboelectric nanogenerator (TENG) with low frequency and high voltage and electromagnetic generator (EMG) with high frequency and high current, we are able to effectively broaden the output voltage range while shortening the capacitor voltage rising time, thus obtaining energy harvesting at wide frequency wind speed. The TENG adopts the flexible contact method of arch-shaped film to solve the problem of insufficient flexible contact and the short service life of the rotating triboelectric generator. After 80,000 cycles of TENG operation, the maximum output voltage drops by 7.9%, which can maintain a good and stable output. Through experimental tests, the maximum output power of this triboelectric nanogenerator is 0.55 mW at 400 rpm (wind speed of about 8.3 m/s) and TENG part at an external load of 5 MΩ. The maximum output power of the EMG part is 15.5 mW at an external load of 360 Ω. The hybrid nanogenerator can continuously supply power to the anemometer after running for 9 s and 35 s under the simulated wind speed of 8.3 m/s and natural wind speed of 5.6 m/s, respectively. It provides a reference value for solving the power supply problem of low-power environmental monitoring equipment.

Fractional-order inverse filters revisited: Equivalence with fractional-order controllers

The equivalence of fractional-order inverse filters with fractional-order controllers is demonstrated in this work. This is achieved by appropriately rewriting the filters transfer functions in order to clarify the correspondence between the gain and time-constant of the filters and the scaling factor and differentiation/integration constant of the controllers. Possible implementations of fractional-order inverse filters using second generation voltage conveyors are presented and an application example, related to the control of a motion system, is demonstrated for evaluating the behavior of the introduced structures.

Optimal PID Controllers for AVR Systems Using Hybrid Simulated Annealing and Gorilla Troops Optimization

In the literature, all investigations dealing with regulator design in the AVR loop observe the AVR system as a single input single output (SISO) system, where the input is the generator reference voltage, while the output is the generator voltage. Besides, the regulator parameters are determined by analyzing the terminal generator voltage response for a step change from zero to the rated value of the generator voltage reference. Unlike literature approaches, in this study, tuning of the AVR controllers is conducted while modeling the AVR system as a double input single output (DISO) system, where the inputs are the setpoint of the generator voltage and the step disturbance on the excitation voltage, while the output is the generator voltage. The transfer functions of the generator voltage dependence on the generator voltage reference value and the excitation voltage change were derived in the developed DISO-AVR model. A novel objective function for estimating DISO-AVR regulator parameters is proposed. Also, a novel metaheuristic algorithm named hybrid simulated annealing and gorilla troops optimization is employed to solve the optimization problem. Many literature approaches are compared using different regulator structures and practical limitations. Furthermore, the experimental results of 120 MVA synchronous generators in HPP Piva (Montenegro) are presented to show the drawbacks of the literature approaches that observe generator setpoint voltage change from zero to the rated value. Based on the presented results, the proposed procedure is efficient and strongly applicable in practice.

A high voltage generation using a hybrid Marx generator with Fibonacci operation

A solid-state Marx generator has been used in high-voltage applications. This paper aims to develop a hybrid solid-state Marx generator with a single inductor. The proposed circuit is composed of a Fibonacci module and a boost module. Unlike traditional Marx generators, the proposed circuit is controlled by four-phase pulses to achieve Fibonacci operation. Furthermore, the output of the Fibonacci module is stepped up by the boost module. Therefore, the proposed circuit allows for higher gain than the traditional Marx generator. Regarding the proposed circuit with two-stages, theoretical analysis and experimental investigation are performed to reveal the circuit characteristics. In the case of six times voltage gain, the component count of the proposed circuit is half that of the traditional Marx generator. Furthermore, in the experimental demonstration, the prototype of the proposed circuit achieves 81 % power efficiency with six times gain.

Study on added damping due to resistive shunting on cantilever, simply supported beam, and effect on the variation of amplitude at resonance

The current work determines the piezoelectric damping of resistively shunted beams induced by resistors through joule heating. To predict this damping, a piezoelectric patch [Formula: see text] is attached to the surface of a cantilever beam. The current work emphasizes the effect of various parameters on damping added to the cantilever beam through the energy dissipation approach. This work analyzes different methods for predicting added damping. Results from different approaches rely on the base structure modeshape. Using the energy dissipation method from voltage generation, estimated added damping, included a stepped beam model to account for the curvature of the beam with PZT. Further, the same is validated with existing literature and found to be consistent. With the energy dissipation approach, including the stepped beam model compared with experimental literature data, the accuracy of the adopted beam model is validated. Few critical observations were made, such as the location of the PZT patch plays a vital role in determining the required added damping for a particular mode. This optimal location was the nodal location of the other modes. The location of the piezoelectric patch is an important parameter to achieve the required added damping for a particular mode. The optimal location of PZT to achieve maximum added damping for a particular mode may lie at the nodal location of other modes. This optimal location is addressed by rigorous experiments on a simply-supported beam initially and further correlated to a cantilever beam with the help of an energy dissipation approach. The energy dissipation model is correlated and validated for cantilever beam straight PZT on cantilever beams and a simply supported beam. In practical situations, in ambient conditions, environmental effects may result in a change of resonant frequency and thus amplitude. This variation may alter the base and shunt damping performance attributed to air damping. We have experimentally investigated the influence of air damping for base damping (inherent) and added damping (PZT).

A high-efficient photo-thermoelectric coupling generator of cuprous iodide

Thermoelectric (TE) energy converters have attracted great interest due to their maintenance-free, long-life, and high-reliability properties. However, improving the output power of TE devices remains a huge challenge. In this work, a high-efficient photo-TE coupling generator based on cuprous iodide (CuI) film is proposed to increase the output power of TE devices. Here, CuI film was prepared by the successive ionic layer adsorption and reaction method. The influence of the photovoltaic (PV) effect on the TE output voltage of CuI film was investigated by an analysis of the experimental results. The results showed that the output voltage of the photo-TE coupling generator had a maximum increment of 83.47% at 343 K compared to the sum of TE and PV voltages. The increase in the output voltage was mainly because of the PV effect rather than the TE effect, while the photo-generated electrons also induce a considerable change in the TE figure of merit. Hence, the strategy proposed in this work might be a potential approach to further improve the output performance of other TE materials.

A Novel Droop Control Strategy of Reactive Power Sharing Based on Adaptive Virtual Impedance in Microgrids

Droop control strategy is widely used to control parallel inverters in a microgrid. However, due to the mismatched line impedance, the traditional droop control strategy is difficult to evenly share the reactive power and restrain the circulating current among multiple parallel inverters. In this article, an adaptive virtual impedance-based droop control strategy without communications is proposed to solve the reactive power sharing problem caused by the difference of line impedance. The reactive power output and voltage of each distribution generator are introduced into the adaptive virtual impedance controller to achieve a tradeoff between reactive power sharing accuracy and voltage drop. Small-signal stability analysis of the inverters equipped with the proposed controller is conducted to determine the optimal control parameters. Simulation and experimental results demonstrate the effectiveness of the proposed droop control strategy.

Power system preventive control aided by a graph neural network-based transient security assessment surrogate

In the context of the clean energy revolution and the high penetration of renewables and power electronics, the uncertainty level of operating states significantly increases, which brings new challenges to the safe and stable operation of power grids. Power system preventive control is an important measure to ensure the safe and stable operation of power systems by adjusting the active generation and nodal voltage of generators. In this paper, a power system preventive control algorithm aided by a Graph Neural Network (GNN)-based Transient Security Assessment (TSA) surrogate is proposed. A GNN-based fast contingency scanning model is constructed based on power network topology, which can predict the contingency scanning results rapidly only based on the power flow by transforming the original contingency scanning problem into the node classification problem on the GNN. The obtained GNN is then used as a surrogate model for TSA to speed up the solution of particle swarm optimization-based transient security-constrained optimal power flow. Numerical Tests are carried out in the IEEE-39 system and the test results indicate that the proposed method can significantly improve the efficiency without affecting the solution accuracy.

English

Microbial fuel cells (MFCs) are considered as one of the best prospective natural resources to be discovered on the way to reduce the dependence on fossil fuel-based electricity generation. However, low power generations from MFCs, expensive electrode materials, and the inability to scale-ups MFCs to industrially relevant capacities have made the usage of MFC even worse. The utilization of MFCs in the area of electro-chemistry and thermal science can be very promising in energy storage aspects. In this current study, we studied various combinations of electrode materials and processes that can be applied to construct economical MFCs on small scale. To figure out the best suited MFC setup, MFC systems are prepared using different electrode materials and impacts of these materials on voltage generation are investigated. The cells are observed for 10 h, and voltage generation is witnessed by natural chemical reaction. Then, voltage, current, and power density curves are generated. Next, a pseudo-two-dimensional (2D) physics-based mathematical full cell model is developed to investigate the best suited MFC as a potential energy storage device. It is observed that the numerical results generated from the model are in good agreement with those obtained from the experimental analyses. Hence, the model should be able to predict the better performing anode and cathode materials to build microbial fuel cells having a maximum amount of voltage storage capacity in a specific period. Details of this work will provide more useful information on the concept of MFC and design guidelines for several applications such as energy storage and transformation. Key words: Bacteria, electro-chemistry, physics-based, power, energy storage device, electrodes.

Modeling of Automatic Generation Control and Automatic Voltage Regulator Under Generation Rate Constraint

As the interconnected power system transmits power from one area to another, the frequency will inevitable deviate from scheduled frequency. In addition, the active and reactive power demands continually change with rising and falling trend. Any mismatch between system generation and demand results in change in system frequency that is highly undesired. Excitation of generator must be regulated in order to match the power demand, otherwise the bus voltage may fall beyond the permitted limit. In this paper, a simulation model is developed for each component of AGC and AVR loops considering generator rate constraints. The response with GRC is compared with the analysis done without the Generation Rate Constraint. Although the frequency deviation is less with suitable controllers when the GRC is not considered, it is not the actual frequency deviation. When GRC is considered the actual frequency deviation can be found and then accordingly the controller is tuned. So that the desired frequency and power interchange with neighboring systems are maintained in order to minimize the transient deviations and to provide zero steady state error in appropriate short time. Further the role of automatic voltage control is to maintain the terminal voltage of synchronous generator in order to maintain the bus bar voltage Results are obtained using MATLAB SIMULINK software.

A simple structured solar selective absorber for application in thermoelectric energy harvesters

This study focuses on green energy harvesting that aims to supply electricity from a different energy source: solar thermoelectric, which is present in the environment without grid connection or utilization of batteries. The concept of using solar selective absorbers and heat sinks is introduced to create temperature differences, which are then converted into electrical energy via the use of a thermoelectric power generator. The solar selective absorber used in this study is a light-absorbing material, and its voltage generation is then compared to a blackbody.

A Novel Robust Strategy for the Concurrent Control of Frequency and Voltage in the Synchronous Generator With Real Structured Uncertainties

In this article, a novel robust strategy is proposed for concurrent control of the synchronous generator's voltage and frequency in a single machine infinite bus plant. The methodology is based on infinity norm and Mu analysis and synthesis to prepare the robust function of the power system stabilizer, automatic voltage regulator, and load frequency control systems. Ten real structured uncertainties have been considered for the K 1, K 2 and K 4 to K 6 coefficients of the Heffron–Phillips generator model, inertia constant, damping coefficient, the governor speed regulation coefficient, and the amplifier and exciter gains. Each uncertain parameter has a nominal value in the generator operating point with 25% tolerance excepts to amplifier and exciter gains where their tolerances are 12.5%. The proposed strategy efficiency lies in the strict converting of all ten real parametric uncertainties into the generalized structure of µ synthesis and the formation of efficient weighting functions. Based on the proposed strategy and H ∞ norm optimization, µ-synthesis D-K iteration procedure and loop-shaping manner, three controllers have been obtained whose robust performances (RPs) are guaranteed. The supremacy of the offered controllers is shown by comparing their functions in four scenarios and three patterns. The simulation results reveal the good RP of the designed controllers. Also, for a benchmark problem as a single machine connected to a 230 kV network, the capabilities of the designed robust controllers have been shown.

Multiple Synchronous Rotating Frame Transformation-Based 12th Current Harmonic Suppression Method for an IPMSM

In order to solve the problem that the three-phase current of the interior permanent magnet synchronous motor (IPMSM) contains the 11th and 13th current harmonics, a multiple synchronous rotating frame transformation (MSRFT)-based current harmonic suppression method is established. Firstly, the influencing factors of current harmonics in IPMSM vector control are analyzed, and the influence mechanism of the inverter’s dead-time effect and the permanent magnet flux linkage harmonics on the current harmonics is described. Secondly, a simple current harmonic extraction method is proposed by optimizing the traditional current harmonic extraction method based on MSRFTs. The proposed method achieves the accurate extraction of the current harmonic components. Thirdly, a harmonic voltage generation method is established and is combined with the proposed current harmonic extraction method to form a current harmonic suppression strategy. Finally, the feasibility and effectiveness of the proposed method are verified via MATLAB/Simulink simulations and experiments. The simulation and experimental results show that the proposed current harmonic extraction method can extract the current harmonic components accurately, and the proposed current harmonic suppression strategy can suppress the 11th and 13th current harmonics effectively.

A high dimensional functional time series approach to evolution outlier detection for grouped smart meters

Smart metering infrastructures collect data almost continuously in the form of fine-grained long time series. These massive data series often have common daily patterns that are repeated between similar days or seasons and shared among grouped meters. Within this context, we propose an unsupervised method to highlight individuals with abnormal daily dependency patterns, which we term evolution outliers. To this end, we approach the problem from the standpoint of High Dimensional Functional Time Series and we use the concept of functional depth to exploit the dynamic group structure and isolate individual meters with a different evolution. The performance of the proposal is first evaluated empirically through a simulation exercise under different evolution scenarios. Subsequently, the importance and need for an evolution outlier detection method are shown by using actual smart-metering data corresponding to photo-voltaic energy generation and circuit voltage records. Here, our proposal detects outliers that might go unnoticed by other approaches of the literature that have demonstrated to be effective capturing magnitude and shape abnormalities.

Ambient Humidity-Induced Phase Separation for Electrospun Fiber Morphology Engineering Toward Piezoelectric Self-Powered Sensing

Electrospun polymeric piezoelectric fibers have a considerable potential for shape-adaptive mechanical energy harvesting and self-powered sensing in biomedical, wearable, and industrial applications. However, their unsatisfactory piezoelectric performance remains an issue to be overcome. While strategies for increasing the crystallinity of electroactive β phases have thus far been the major focus in realizing enhanced piezoelectric performance, tailoring the fiber morphology can also be a promising alternative. Herein, a design strategy that combines the nonsolvent-induced phase separation of a polymer/solvent/water ternary system and electrospinning for fabricating piezoelectric poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE) fibers with surface porosity under ambient humidity is presented. Notably, electrospun P(VDF-TrFE) fibers with higher surface porosity outperform their smooth-surfaced counterparts with a higher β phase content in terms of output voltage and power generation. Theoretical and numerical studies also underpin the contribution of the structural porosity to the harvesting performance, which is attributable to local stress concentration and reduced dielectric constant due to the air in the pores. This porous fiber design can broaden the application prospects of shape-adaptive energy harvesting and self-powered sensing based on piezoelectric polymer fibers with enhanced voltage and power performance, as successfully demonstrated in this work by developing a communication system based on self-powered motion sensing.

Group predictive voltage and frequency regulators for small hydro power plant in the context of low power quality

The study examines the influence of predictive voltage and frequency regulators of generators of a small hydropower plant (HPP) on the quality indices of electric power and those of the control process in the case of disturbances in the system. The study aimed to determine the performance of the group predictive generator control algorithms. The research has revealed that the use of a DC link and a small HPP with group predictive voltage and frequency controllers has a noticeable effect on the improvement of power quality: the voltage distortion factor decreases by an average of 1.4 times and the voltage unbalance factor is reduced by almost ten times. In all considered conditions, the use of group predictive controllers can significantly improve the quality of electricity and the quality of the voltage and frequency control: the voltage dip depth decreases by 1.7 times and the voltage un-balance factor decreases by almost 4 times when an additional load is connected; the voltage dip depth is reduced by 20%, the frequency overshoot value is reduced by a factor of 1.8, and the transient process time for the frequency under the short-term short-circuit conditions is reduced by a factor of 1.5.

Comprehensive Numerical Analysis of a Porous Piezoelectric Ceramic for Axial Load Energy Harvesting

In this paper, an axial-type piezoelectric energy generator with various porosities of piezoelectric ceramics is designed and analysed. A 3D finite element model is developed by using ANSYS software. The porosity of piezoelectric ceramic is varied from 0 to 80% through thickness or along the length of the duralumin beam. The axial type energy harvester consists of bimorph (d31) and cylinder (d33) piezoelectric patches with base excitation. The effects of various porosities, proof mass locations, and different applied acceleration are used to determine the output voltage and power generation. The maximum output voltage and power are obtained equal to 2.25 V and 5.1 µW, respectively.