Good Power Quality Research Articles

Integrating canonical correlation analysis with machine learning for power quality disturbance classification

Abstract Recently, the rapid growth of Renewable Energy Resources (RER) in power generation has resulted in the frequent occurrence of Power Quality Disturbances (PQDs) within the power system. The timely and accurate detection of these PQDs is critical for maintaining good power quality while integrating RER into hybrid power systems to make them more robust and stable. In this paper, a multi-view dimensionality reduction approach based on Canonical Correlation Analysis (CCA) is proposed to differentiate different types of PQDs. Here, a dataset of 29 types of PQDs which include nine single types and twenty multiple types of PQDs have been generated using their mathematical model in MATLAB for experimentation. CCA being a multi-view dimensionality reduction technique maximizes the correlation between two different views of the data. Here two cases of datasets have been considered for further exploration, Case 1: PQDs without noise and with 20 dB noise, Case 2: PQDs with 20 dB and 30 dB noise. Furthermore, to test the efficacy of CCA in both cases, the extracted features have been tested using four different classifiers, i.e., K-Nearest Neighbour (KNN), Support Vector Machine (SVM), Naive Bayes (NB), and Random Forest (RF). The performance of each of the classifiers has been tested on five different performance metrics such as precision, recall, F1 score, hamming loss, and accuracy, and the results show that the proposed technique of multi-view dimensionality reduction is capable of classifying the PQDs with two different views at a time.

Efficient power factor correction in single phase AC–DC boost converter for retrofitted electric bicycle battery charging: A finite element analysis approach

This research paper describes modifying a conventional bicycle into an electric bike by retrofitting it with a single-phase boost power factor correction (PFC) rectifier for low power battery chargers. The proposed work was designed and developed in a single stage, as opposed to the traditional two-stage chargers used to charge E-bicycle, to provide the desired outcomes of enhanced efficiency, good power quality, and dependability due to the charger's lower cost. Additionally, the proposed converter uses a single switch, which reduces not necessary body diode conduction and circulating current and enhances the PFC device's thermal management. Additionally, this research makes use of the diode bridge rectifier (DBR) arrangement, which offers low current stress and is suitable for electric bicycles. The converter operates at a low cost with reduced magnetics (DCM) by operating the charger in discontinuous conduction mode at such low voltage levels. It also accomplishes intrinsic power factor at the ac mains by employing a simple control method to maintain the battery in high power density constant current (CC) and constant voltage (CV) states. A thorough state space investigation is carried out in combination with modeling and testing to ensure that the electric bicycle charger operates effectively. Consequently, low power chargers are a good fit for the proposed single stage front-end converter, and a 250 W hardware prototype is used to verify the findings.

Analysis of interval type-2 fuzzy controller based interleaved sepic PFC converter for PQ enhancement in power solutions

The Power solutions have become indispensable for all the devices in recent years with an appropriate power conversion circuitries and control methods to ensure good dynamic response, improved stability, reliability and efficiency. The main intent of this article is to impart the designing of interval type-2 fuzzy logic controller (IT2FLC) based interleaved Sepic power factor correction (PFC) converter. This work also involves the careful design of the robust controller with enhanced precision and good power quality (PQ) performance at the AC mains. In addition, the development of IT2FLC based power solution improves the overall power conversion with stabilized output in the perspective of its quick rise time, less overshoot and fast settling time in comparison to other traditional controllers. Further, the uncertainties and issues associated with the conventional proportional integral (PI) and fuzzy logic controllers (FLCs) are handled effectively by the proposed IT2FLC controller. Moreover, this preferred converter is modeled with an internal parasitics and its performances are evaluated and compared with other conventional Zeigler Nicholas (ZN) tuned PI controller and FLC by dint of MATLAB/Simulink platform. Finally, the experimental test bench set up of 250 W, 48 V power circuitry is devised and the test outcomes confirm the excellent transient behavior and PQ performances of the modeled power solution.

Solar Energy Prediction Based on Intelligent Predictive Controller Algorithm

The technological advancement in all countries leads to massive energy demand. The energy trading companies struggle daily to meet their customers’ power demands. For a good quality, disturbance-free, and reliable power supply, one must balance electricity generation and consumption at the grid level. There is a profound change in distribution networks due to the intervention of renewable energy generation and grid interactions. Renewable energy sources like solar and wind depend on environmental factors and are subject to unpredictable variations. Earlier, energy distribution companies faced a significant challenge in demand forecasting since it is often unpredictable. With the prediction of the ever-varying power from renewable sources, the power generation and distribution agencies are facing a challenge in supply-side predictions. Several forecasting techniques have evolved, and machine learning techniques like the model predictive controller are suitable for arduous tasks like predicting weather-dependent power generation in advance. This paper employs a Model Predictive Controller (MPC) to predict the solar array’s power. The proposed method also includes a system identification algorithm, which helps acquire, format, validate, and identify the pattern based on the raw data obtained from a PV system. Autocorrelation and cross-correlation value between input and predicted output 0.02 and 0.15. The model predictive controller helps to recognize the future response of the corresponding PV plant over a specific prediction horizon. The error variation of the predicted values from the actual values for the proposed system is 0.8. The performance analysis of the developed model is compared with the former existing techniques, and the role and aptness of the proposed system in smart grid digitization is also discussed.

Generation of superposed orbital angular momentum beams using a free-electron laser oscillator.

With wavelength tunability, free-electron lasers (FELs) are well-suited for generating orbital angular momentum (OAM) beams in a wide photon energy range. We report here the first experimental demonstration of OAM beam generation using an oscillator FEL with the tens of picosecond pulse duration. Lasing around 458 nm, we have produced the four lowest orders of superposed Laguerre-Gaussian beams using a very long FEL resonator of 53.73 m. The produced beams have good beam quality, excellent stability, and substantial average power. We have also developed a pulsed operation mode for these beams with a highly reproducible temporal structure for a range of repetition rate of 1-30 Hz. This development can be extended to short wavelengths, for example to x-rays using a future x-ray FEL oscillator. The OAM operation of such a storage-ring FEL also paves the way for the generation of OAM gamma-ray beams via inverse Compton scattering.

Method to Enable Reduced Sensor Capacitor Voltage Estimation in Modular Multilevel Converters

Bulk power applications such as shipping increasingly consider multilevel converter topologies such as modular multilevel converters (MMC), which offers the advantages of scalability, good power quality, and reconfigurability. The internal functioning of MMC requires complete knowledge of the capacitor voltages that make up their submodules meaning a large number of sensors are needed and thus a high number of potential points of failure exist. To increase reliability and reduce investment costs, state estimation techniques such as KALMAN filters have been employed to replace the physical sensors. Analytical techniques based on the knowledge of arm current, arm voltage, and submodule states have also been developed. These techniques exploit the fact that at an insertion index of 1, the arm voltage equals the capacitor voltage on the submodule which permits the estimation algorithm to refresh periodically with measured data thereby increasing the accuracy. This method requires a long refresher time, especially when many submodules are used per arm. In this study, we propose an improved analytical estimation by not only using unity insertion indices, but also exploiting transitions between two successive insertion indices. The study was carried out on a 4 submodule per arm MMC system. The estimated capacitor voltages were then compared with sensor-based voltage measurements confirming the validity of the proposed method. It was then integrated into a complete MMC controller including the inner controls such as circulating current and capacitor voltage balancing.

ANFIS controlled fuel cell powered series active filter for voltage waveform augmentation in the distribution grid

The high penetration of nonlinear and unstable loads into the grid network severely impacts the quality of power delivered by the grid system. Furthermore, it leads to a disruptive situation of maintaining good quality power in the distribution sectors. Consequently, maintaining a good quality of power is very difficult on the power distribution grid. In this proposed work, the Proton exchange membrane Fuel Cell sustained by a three-phase Series Active Filter (PFC-SAF) is employed to enhance the quality of sensitive load voltage in the distribution grid. The generalized bell-shaped membership function based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used to generate the reference voltage signals of the PFC-SAF. The proposed system is modelled and analyzed in a Matlab/Simulink environment. The performance of the PFC-SAF is investigated based on various fault conditions and voltage harmonics. From the obtained results, it has been found that the PFC-SAF effectively regulates the voltage in the distribution grid. Also, the total harmonic distortion of the sensitive load voltage is reduced from 20.86 % to 0.55 %.

Analytical study and real simulation for improving the safety of ageing nuclear facility using UPFC

This paper aims to increase the performance and improve the safety of an ageing Nuclear Facility (NF). Good power quality extends the life of electrical equipment at NF and thus protects it from premature aging. The first stage of this paper presents a measurement and analysis of various power quality events for a real-world case of a NF under different conditions of operation. In the previous work for this group, a new proposed technique based on partial swarm optimization is presented to find the allocation of the UPFC to enhance the power quality within the specified limit. The technique is tested by IEEE33 bus. This step is to assess system performance and find the best solutions to ensure the normal and safe operation of NF. In this paper, the simulink-matlab programme was used to simulate a real NF based on a new vision of UPFC. The results indicate that the strategy is an effective way to improve the safety of power quality and ageing NF using UPFC.

Development of Solar Power Plant to Support Smart Farming 4.0 at Hubbul Khoir Islamic Boarding School Indonesia

Electricity is a very crucial thing in human life today such as for communications, education, offices, household appliances, and transportation. Unfortunately, most of the electricity in Indonesia is still generated by fossil fuels such as coal. Indonesia which is on the equator has an advantage in solar power generation. Every area in Indonesia gets sunlight for a full year. In this paper, we develop a 1.62 kWp solar power plant at the Hubbul Khoir Islamic Boarding School Indonesia. Energy generated from solar panels is used to support the hydroponic farming system owned by the Islamic boarding school. Economic analysis is used to find out whether the installed generating system is profitable or not. Power quality analysis is used to determine whether the load can be supplied with good power quality. The results obtained by the monitoring system can monitor the PV output power and the power to the load with a display on the LCD screen and on the web with overall accuracy above 96%, economic analysis results show that the system will return on investment after 6.8 years with a profit in the 25th year of Rp20,871,282, and quality the power in this system has good power quality from the PLN side and the inverter side.

A Dual Source 13 Level Inverter with Reduced Component Count for Renewable Energy Applications

An innovative multilevel inverter (MLI) relying on switched capacitor (SC) architecture is suggested for single-phase inverters with 13-levels. This suggested SCMLI is expected to be capable of generating output AC voltages at appropriate levels while utilizing fewer switches. The suggested inverter utilizes two count of capacitors, two asymmetrical dc sources, two diodes, and 11 switches. As fewer switches are needed, fewer gate drivers are also needed, increasing the converter's power density. The challenge of preserving self-voltage balance across the capacitors in an SC-MLI circuit is yet another task. Additionally, when the modulation index is low, self-voltage preservation is subpar. It is possible to maintain the self-voltage balance with the capacitors connected in this suggested SC-MLI avoiding the requirement of any ancillary devices or challenging control schemes. Regardless of the modulation index values, capacitors operate at self-balanced levels in all regions of the spectrum. The suggested SC-MLI has a strong ability to achieve good power quality and can balance capacitor voltages even at low modulation indices. The suggested SC-MLI is first modelled using different loading conditions in the MATLAB/Simulink® platform, and subsequently it is validated with the help of typhoon-HIL real-time emulator. Using the simulation tool PLEXIM-PLECS, the suggested inverter's overall switching losses and efficiency are estimated and found out to be 95.87%.

A hybrid control topology for cascaded H-bridge multilevel inverter to improve the power quality of smart grid connected system: NBO-RERNN approach

This manuscript proposes a hybrid control technique for the grid-connected photovoltaic (PV) generation system with a cascaded multilevel inverter (CMLI). The proposed hybrid approach integrates the Namib beetle optimization (NBO) and recalling-enhanced recurrent neural network (RERNN) approach, known as the NBO-RERNN technique. The cascaded multilevel inverter (MLI) is intended to increase the optimum control signal using the proposed controller. The cascaded multilevel inverter (MLI) is designed by using the minimum count of switches. The key purpose of the proposed approach is to improve power regulation or maximal solar energy conversion system (SECS) and to achieve good power quality (PQ) of the system. The proposed NBO technique generates the optimum control signal dataset offline. Based on the fulfilled dataset, the RERNN generates the best CMLI control signals inonlinemanner. The resultant control signals are used to regulate cascaded multilevel inverter insulated gate bi-polar switches (IGBT). For this purpose, the proposed NBO-RERNN control topology defines converter switching states by modeling generation system operating modes. The parameter variations of the system and external disturbances are mitigated, and the load demands are fulfilled optimally by using this control technique. The NBO-RERNN control topology is implemented in MATLAB, and its performance is compared with existing approaches. The simulation reveals that the proposed method has lower THD than the existing one.

Scaled Conjugate-Artificial Neural Network-Based novel framework for enhancing the power quality of Grid-Tied Microgrid systems

The exponential increase in the dependence on electrical power by rapid industrialization and increasing population has given rise to the need of supplying electric power efficiently and with good power quality (PQ). The evolution of renewable energy sources and their increased penetration into traditional grid systems has increased the complexity of electric power transmission and distribution. The significant increase in the use of complex converters, Flexible AC Transmission System devices and complex nonlinear loads in modern power systems have amplified the issues associated with the production and distribution of electricity having proper PQ. The proper functioning of the power system network requires healthy quality of power, maintained both at the load and source end. The Dynamic Voltage Restorer is a prospective D-FACTS (Distribution Flexible AC Transmission System) device that has been widely incorporated for addressing the PQ issues caused by irregularities in the distribution grid's voltage, current, or frequency. This research article attempts to enhance PQ indices of Photovoltaic, Fuel Cell, DVR and energy storage (battery) based Microgrid systems through a proposed Scaled Conjugate based Artificial Neural Network (SC-ANN) in the Matlab/Simulink architecture. The suggested technique’s effectiveness is verified by introducing severe PQ faults such as sag and swell and numerous power system responses have been comprehensively studied by comparing them with traditional Fuzzy Logic Controller and Proportional Integral controllers. The results obtained validates the efficiency of the proposed controller over FLC and PI methods in maintaining the system power indices constant during the onset of PQ faults by reducing harmonics and oscillations thereby enhancing the overall system reliability, efficiency and stability paving its way for real-time implementation in the areas of MG system.

Intelligent Power Controller for BLDC Motor

Now-a-days BLDC motors are used in many applications including electric vehicles. The battery-operated vehicles are gaining popularity as people become increasingly aware of the adverse effects of fossil fuel-powered vehicles on the environment. These battery- operated vehicles are equipped with the Brushless direct current (BLDC) motor due to its high efficiency. Many researchers carried out researches to regulate the operations of BLDC motors. In this research the control of BLDC motor is analyzed. While taking into account reliability and durability, the BLDC motor fails to provide an increased fault tolerance, with decreased electromagnetic interference, acoustic noise, flux ripples, and torque ripple. Torque ripple in a BLDC motor’s is mainly caused due to the variation in the interactions across the stator and rotor as well the electromagnetic fields. So, the research has come up with the solution to the torque ripple using the controllers. By using intelligent power controllers, the output performance can be improved with good power quality and efficiency.

Fulfillment of Some Important Voltage Harmonic Standards in a FPGA Controlled CHB Multilevel Inverter Utilizing Improved SHM-PAM Technique

In the area of medium voltage and high power multilevel inverter applications, good quality power output can be achieved by minimizing lower-order harmonic components, and the SHM-PAM scheme produces best results in this context. The minimization of selective lower-order harmonics rather than their complete elimination makes it more useful to comply certain grid code standard. This article proposes an improved SHM-PAM scheme for a 3-phase 7-level CHB-MLI utilizing three new half-wave (HW) symmetry waveforms to comply with six well-known grid code standards, namely CIGRE WG 36-05, EN 50160, NRS 048-2, IEC 61000-2-12, IEC 61000-3-6, and ER G5/4. The optimal switching transients and necessary dc-link voltages have been determined for controlling the CHB MLI using the recently reported dragonfly algorithm (DA). The efficacy of the reported scheme is evaluated satisfactorily by simulation study and hardware investigation on a CHB-MLI laboratory prototype. The power loss analysis of the CHB inverter for the proposed schemes is evaluated for the entire power factor range. Additionally, to demonstrate the suggested method's superiority in terms of necessary commutation angles for grid code fulfilment, a comparative study has been carried out with a number of pre-existing modulation-schemes.

Efficient 1.7 µm pumping of 2 µm thulium lasers.

Solid-state 2 µm lasers based on thulium-doped active media Tm:YAG, Tm:YAP, and Tm:YLF were investigated under 1.7 µm resonant diode pumping. In contrast with standard 0.8 µm pump wavelength, a high slope efficiency was achieved, up to 80% in the case of Tm:YAP and Tm:YLF, nearing a quantum limit without relying on Tm3+-Tm3+ cross-relaxation energy transfer. Low thermal load allowed for stable continuous-wave operation with good beam quality and output power up to 6 W (Tm:YAG, Tm:YLF), and 8W (Tm:YAP).

Optimal Load Sharing between Lithium-Ion Battery and Supercapacitor for Electric Vehicle Applications

There has been a suggestion for the best energy management method for an electric vehicle with a hybrid power system. The objective is to supply the electric vehicle with high-quality electricity. The hybrid power system comprises a supercapacitor (SC) bank and a lithium-ion battery. The recommended energy management plan attempts to maintain the bus voltage while providing the load demand with high-quality power under various circumstances. The management controller is built on a metaheuristic optimization technique that enhances the flatness theory-based controller’s trajectory generation parameters. The SC units control the DC bus while the battery balances the power on the common line. This study demonstrates the expected contribution using particle swarm optimization and performance are assessed under various optimization parameters, including population size and maximum iterations. Their effects on controller performance are examined in the study. The outcomes demonstrate that the number of iterations significantly influences the algorithm’s ability to determine the best controller parameters. The results imply that combining metaheuristic optimization techniques with flatness theory can enhance power quality. The suggested management algorithm ensures power is shared efficiently, protecting power sources and providing good power quality.

Third harmonic injection control for co‐phase traction power supply system using direct AC/AC full‐bridge modular multilevel converter

AbstractAs the full‐bridge modular multilevel converter (FB‐MMC) enables direct three‐phase AC voltage to single‐phase AC voltage conversion with good power quality and high voltage level, it is suitable for the co‐phase traction power supply system. However, voltage deviation occurs between arms when the direct AC/AC FB‐MMC operates in equal or similar frequency conditions. To solve this problem, a voltage balancing control based on third harmonic injection of co‐phase power supply system using direct AC/AC FB‐MMC is proposed. With the third harmonic injection, voltage balancing between arms is ensured and the capacity of FB‐MMC is enhanced. The third harmonic voltage is directly obtained from existing signals and the third harmonic current reference is produced by simple proportional‐integral (PI) controller. The effect of the third harmonic currents under different voltage ratios and phase difference is quantitatively analyzed, optimized range of voltage ratio and phase difference are obtained to minimize arm currents increment and reduce overrating of converter currents. In addition, a comparison between the proposed and the conventional control scheme is studied, showing the superior of proposed method in cost and performance. Finally, the effectiveness of the proposed scheme is verified by simulations and experiments.

Modelling and control of a grid-connected AC microgrid with the integration of an electric vehicle

Abstract The purpose of this paper is to propose an efficient model and a robust control that ensures good power quality for the AC microgrid (MG) connected to the utility grid with the integration of an electric vehicle (EV). The MG consists of two renewable energy sources: a photovoltaic system (PVS) and a wind turbine system (WTS) based on a permanent magnet synchronous generator (PMSG), with the integration of an EV. These sources are used to supply active and reactive power to the AC bus and the utility grid. Maximum power point tracking (MPPT) based on the perturb-and-observe (PO) method is used to increase the efficiency of the photovoltaic modules and improve overall performance. The MG system includes a 2-MW WTS, a 100-kW PVS and 12 kW provided by the EV. To validate the performance of the proposed system, a series of simulations were conducted using the MATLAB®/Simulink® environment. The results demonstrate that the proposed system ensures high performance in terms of power quality, system stability, power tracking and safe integration of the EV.

Improvement of Power Quality in Primary Distribution Systems Based on Static-Var Compensators

A flexible AC Transmission Systems (FACTS) is a new technology offers a fast and reliable control over the transmission and distribution parameters like voltage and phase angle between the sending end voltage and receiving end voltage. Distribution static synchronous compensator (DSTATCOM) is a second generation member of the (FACTS) controllers. Reactive power compensation is an important aspect in the control of distribution systems. Reactive current in addition to increasing the distribution system losses, introduces voltage drop at lead point and finally it causes poor power quality in power systems. Primary radial distribution feeders have high resistance to reactance ratio, which causes voltage drop and high power loss in radial distribution systems. providing high demanding power to entire load while maintaining voltage magnitude at acceptable range is one of the major system constraints, using of capacitor banks to improve the reactive power have not quite enough at high reactive power feeder, because it have more slow in step by step response and have not capable to generate continuously variable reactive power. In some primary distribution feeders at the state of Khartoum, it is observed that there are some appropriate drops in voltage and quality service at high reactive power loads although some individual capacitor banks have been connected at these feeders, from here we researched for a new technology to overcome this problem. A steady-state model of (DSTATCOM) is proposed and developed to compensate the reactive power by using a Voltage Source Converter (VSC) with Pulse Width Modulation (PWM) and cascade control of four direct proportional integral controllers (PI) in synchronous reference frame. The detailed modeling and control design of (DSTATCOM) with specific typical radial primary distribution feeders (industrial, commercial, residential) are presented and implemented along necessary mathematical model equations in the Matlab software. Simulation schemes of (DSTATCOM) are done with help of control block diagrams and stability analysis. Load flow is an important method for analysis, operation and planning studies of any power system in a steady-state condition. In this research backward forward sweeps load flow method (Kirchhoff’s Laws) has been proposed rather than Newton-Raphson and Fast decoupled methods because the distribution feeders have a high R/X ratio which make the systems are ill-conditioned iterations analysis. (DSTATCOM) was installed on specific typical radial feeders at the (DSTATCOM) which using for distribution lines and load compensation has been the subject of considerable interest beside it is a new technology for a good power quality solution. Keywords: Power System, Flexible AC Transmission Systems (FACTS) Devices, STATCOM, PI Controller DOI: 10.7176/ISDE/13-1-05 Publication date: May 31 st 2023

Distributed PV Management Based on Edge-cloud Computing Model of Smart Distribution Transformer Terminal Unit

With the growing installation of distributed PV at a low voltage level and the resulting concerns about good power quality, power facilities see a greater need for energy management programs, especially for flexible distributed PV management. In the dawn of a new generation of ICT technologies, an edge-cloud computing model widely applied to smart distribution transformer terminal units (SD-TTU) is proposed to achieve lifecycle management of power facilities. Firstly, existing distribution management systems’ current practices and limitations are presented. According to the development trend, the reconstructed computing model involves three layers, and data interaction among the cloud layer, edge layer, and device layer is described. To support the huge scale of sensed data integration and transmission, the architecture of the edge node is established. Then the technical details for the distributed PV management are presented, including equipment configuration, main monitoring information, and specific procedures.