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Fine grid management is one of the important development directions of transportation planning that has not been fully considered in previous literature. This paper explores the application of the fine grid management method in transportation planning. Based on a case study of Chuanhui, China, this paper proposes a data-driven fine grid partitioning method for determining traffic analysis zones (TAZs). The TAZs are partitioned based on quadrilateral and hexagonal grids. This paper also summarizes a set of criteria for evaluating the impact of different fine grid partitioning methods based on the geographically and temporally weighted regression (GTWR) model. The results show that our fine grid partitioning method for determining TAZs based on quadrilateral grids can achieve a relatively low level of predicted value bias and variable correlation degree bias when the number of TAZs is larger, and it has obvious advantages. Finally, policy implications are proposed to promote the refinement of transportation planning. [ABSTRACT FROM AUTHOR]

Recent advancements in network-connected devices have led to a rapid increase in the deployment of smart devices and enhanced grid connectivity, resulting in a surge in data generation and expanded deployment to the edge of systems. Classic cloud computing infrastructures are increasingly challenged by the demands for large bandwidth, low latency, fast response speed, and strong security. Therefore, edge computing has emerged as a critical technology to address these challenges, gaining widespread adoption across various sectors. This paper introduces the advent and capabilities of edge computing, reviews its state-of-the-art architectural advancements, and explores its communication techniques. A comprehensive analysis of edge computing technologies is also presented. Furthermore, this paper highlights the transformative role of edge computing in various areas, particularly emphasizing its role in power systems. It summarizes edge computing applications in power systems that are oriented from the architectures, such as power system monitoring, smart meter management, data collection and analysis, resource management, etc. Additionally, the paper discusses the future opportunities of edge computing in enhancing power system applications. [ABSTRACT FROM AUTHOR]

Soft-switching technologies can effectively solve the problem of switching losses caused by increasing switching frequency of grid-connected inverters. As a branch of soft-switching technologies, load-side resonant soft-switching is a hotspot for applications of high-frequency inverters, because it has the advantage of achieving soft-switching without using additional components. However, the traditional PI control strategy based on the linear model is prone to destabilization and non-robust dynamic performance when large signal perturbation occurs. In this paper, a novel Passivity-Based Control (PBC) method is proposed to improve the dynamic performance of load-side resonant soft-switching grid-connected inverter. Besides, the model based on the Port Controlled Hamiltonian (PCH) model of the soft switching inverter is carried out, and the passivity-based controller is designed based on the established model using the way of interconnection and damping assignmentpassivity based control (IDA-PBC). Both stable performance and dynamic performance of the load-side resonant soft-switching inverter can be improved over the whole operating range. Finally, a 750 W load-side resonant soft-switching inverter simulation model is built and the output performance is compared with the traditional PI control strategy under stable and dynamic conditions. The simulation results show that the proposed control strategy reduces the harmonic distortion rate and improves the quality of the output waveforms. [ABSTRACT FROM AUTHOR]

Electric power generation is quickly transitioning toward nontraditional inverter-based resources (IBRs). Prevalent devices today are solar PV, wind generators, and battery energy storage systems (BESS) based on electrochemical packs. These IBRs are interconnected throughout the power system via power electronics inverter bridges, which have sophisticated controls. This paper studies the impacts and benefits resulting from the integration of grid forming (GFM) inverters and energy storage on the stability of power systems via replicating real events of loss of generation units that resulted in large load shedding events. First, the authors tuned the power system dynamic model in Power System Simulator for Engineering (PSSE) to replicate the event records and, upon integrating the IBRs, analyzed the system dynamic responses of the BESS. This was conducted for both GFM and grid following (GFL) modes. Additionally, models for Grid Forming Static Synchronous Compensator (GFM STATCOM), were also created and simulated to allow for quantifying the benefits of this technology and a techno-economic analysis compared with GFM BESSs. The results presented in this paper demonstrate the need for industry standardization in the application of GFM inverters to unleash their benefits to the bulk electric grid. The results also demonstrate that the GFM STATCOM is a very capable system that can augment the bulk system inertia, effectively reducing the occurrence of load shedding events. [ABSTRACT FROM AUTHOR]

Demand flexibility plays a crucial role in mitigating the intermittency of renewable power sources. This paper focuses on an active distribution grid that incorporates flexible heat and electric demands, specifically heat pumps (HPs) and electric vehicles (EVs). Additionally, it addresses photovoltaic (PV) power generation facilities and electrical batteries to enhance demand flexibility. To exploit demand flexibility from both heat and electric demand, along with the integration of PVs and batteries, Control and Communication Mechanisms (CCMs) are formulated. These CCMs integrate demand flexibility into the distribution grids to obtain economic benefits for private households and, at the same time, facilitate voltage control. Concerning EVs, the paper discusses voltage-based droop control, scheduled charging, priority charging, and up-/down-power regulation to optimize the charging and discharging operations. For heat demands, the on-off operation of the HPs integrated with phase change material (PCM) storage is optimized to unlock heat-to-power flexibility. The HP controllers aim to ensure as much self-consumption as possible and provide voltage support for the distribution grid while ensuring the thermal comfort of residents. Finally, the developed CCMs are implemented on a small and representative community of an active distribution grid with eight houses using Power Factory software and DIgSILENT simulation language (DSL). This scalable size of the active distribution network facilitates the careful study of symbiotic interaction among the flexible load, generation, and different houses thoroughly. The simulation results confirm that the integration of flexible demands into the grid using the designed CCMs results in the grid benefiting from stabilized voltage control, especially during peak demand hours. [ABSTRACT FROM AUTHOR]

This research paper presents a new approach to address power quality concerns in microgrids (MGs) by employing a superconducting fault current limiter (SFCL) and a fuzzy-based inverter. The integration of multiple power electronics converters in a microgrid typically increases total harmonic distortion (THD), which in turn results in power quality issues. Moreover, the intrinsic variability of solar and wind power sources gives rise to fluctuations in power generation, which consequently leads to power oscillations and voltage sag within microgrids that rely on renewable energy. This research paper introduces a technical approach to achieve power balance in renewable-based microgrids (MGs) by utilizing a fuzzy logic-controlled (FLC) pulse width modulation (PWM) inverter. The Microgrid (MG) consists of a hybrid photovoltaic (PV) system and a wind energy conversion system (WECS) that utilizes a permanent magnet synchronous generator (PMSG). The system employs an optimal torque-controlled maximum power point technique (MPPT) algorithm to optimize power output. The battery energy storage system (BESS) is employed to facilitate power provision during critical scenarios or to ensure a stable power output for fluctuating loads. The SFCL is utilized as a device for voltage compensation in cases of voltage sag incidents. The effectiveness of the suggested control strategy is assessed by performing a comparative analysis of total harmonic distortion (THD) in the load voltage, with and without the utilization of a SFCL. The results suggest that the incorporation of an FLC inverter-SFCL-BESS system effectively mitigates THD and voltage sag, according to the requirements set by the IEEE 519 standards. The research study is carried out by using the MATLAB/SIMULINK software environment. [ABSTRACT FROM AUTHOR]

The inherent constraints of grid‐forming converters affect their ability to maintain voltage source characteristics within a specific operational range. In response to these limitations, ongoing pilot projects involving grid‐forming technology have adjusted their current thresholds up to three times the rated current, significantly exceeding the traditionally threshold of 1.2 times the rated current. This paper aims to investigate the effects of current thresholds on the dynamic responses of grid‐forming converters under large disturbances, with the intention of identifying an optimal current threshold that meets the grid's demands for maintaining voltage source characteristics and overall stability. A novel power angle relationship is introduced, integrating current limits and anti‐windup voltage controls into the equivalent circuit models of these converters. Analytical expressions for stable and unstable equilibrium points are derived, improving insights into the converters' dynamic behaviour and their resilience to phase jumps across various current thresholds and short‐circuit ratios. Findings indicate that higher current thresholds substantially improve phase jump limits and withstand capabilities. The paper concludes with proposed configurations and optimization strategies for current thresholds, all supported by experimental validation. [ABSTRACT FROM AUTHOR]

With the progress of communication technology, the cost of optical fiber and 5G continues to decrease, and data transmission becomes more convenient and fast, making it possible to realize differential protection of distribution network by various intelligent algorithms using signal waveforms. Aiming at the problem that the traditional relay protection device can not meet the actual demand when the single-phase ground fault occurs in the distribution network with distributed generation, this paper proposes a new differential protection scheme. The characteristic mode decomposition improved by the whale optimization algorithm is used to decompose the zero-sequence current waveform collected at both ends of the line. Based on the basic principle of current differential protection, the derivative dynamic time warping of the component with the largest fault feature can effectively solve the problem that the grounding current of the distribution network cannot meet the working requirements of the differential protection device, and ensure the safe and stable operation of the system. Finally, based on MATLAB software, the performance of this method is comprehensively evaluated by simulating different fault conditions, so as to ensure the feasibility and accuracy of this method in the case of diversified faults when the distributed generation is used as part of the power supply. [ABSTRACT FROM AUTHOR]

The work is based on a collaboration between Hiroshima University and Kure KOSEN College. This paper presents the design concept, hardware, and applications of a single-phase synchronous inverter (SSI), a specially designed grid-forming inverter (GFM) for single-phase micro-grid (SMGs). The SSI is designed for the conventional 100/200 V distribution network and is based on the concept of "Non-Interference Core (NIC) dynamic model". Novel contributions of this paper are: (1) A root mean square (RMS) model of NIC-SSI was developed, combined with the conventional power system model, and verified through the comparison with the hardware-in-the-loop (HIL) simulation and SSI hardware experiments; (2) using the developed RMS simulation tool, the stabilization effect of the SSIs was investigated in condition under which the SSIs are massively installed in a distribution system; (3) off-grid SMG operations using SSIs under various ill-conditioned loads were demonstrated. The results show that the SSI has the considerable ability of grid stability enhancements for frequency, transient, and small-signal stabilities. The proposed SMG using SSIs is promising. [ABSTRACT FROM AUTHOR]

This paper proposes an active damping control method based on converter‐side current feedback to mitigate the resonance issue in multi‐inverter grid‐connected systems caused by coupling with the grid impedance. The method aims to address the reduction in grid power quality by utilizing an active damping device without modifying the hardware and software of the grid‐connected inverters. By introducing an additional small‐capacity power electronic device in parallel, the proposed method establishes two parallel admittances at the common connection point, creating specific conduction paths for system harmonics and reshaping the overall system admittance. In parallel operation of two photovoltaic grid‐connected inverters with different capacities, the access of the inherent admittance and virtual admittance of the source damper reduces the harmonic distortion rate of the grid‐connected current from 19.81% to 2.04% and from 15.86% to 0.52%, respectively. Simulation results validate the effectiveness and correctness of the proposed strategy. [ABSTRACT FROM AUTHOR]

The current source inverter (CSI) has become the main grid-connected interface of distributed generation systems due to its advantages, such as boost capability, current controllability, and short-circuit protection capability. However, in weak grids, the grid-connected CSI that uses a phase-locked loop to achieve grid voltage synchronization has problems, such as instability in the fundamental positive-sequence voltage phase detection at the point of common coupling and instability in the current loop control, which seriously hamper the promotion and application of the CSI and its interconnected systems. For this reason, this paper proposes a sliding mode observer-based phase-locking strategy for the CSI. The strategy proposes a sliding mode observer for grid voltage phase detection, so that the grid current can directly follow the grid voltage, solving the problem of inconsistency or distortion between the voltage phase of the point of common coupling and the grid voltage phase in weak grids. On this basis, the grid impedance is regarded as part of the CL filter, and a robust parameter design method is proposed for the grid current closed-loop control in weak grids, which achieves robust operation of a CSI in weak grids. Finally, an experimental platform for a single-phase grid-connected CSI is built to verify the effectiveness and feasibility of the proposed scheme. [ABSTRACT FROM AUTHOR]

Recently, Egypt has recognized the pivotal role of High Performance Computing in advancing science and innovation. Additionally, Egypt realizes the importance of collaboration between different institutions and universities to consolidate their own computational and data resources into a unified platform to serve different disciplines (e.g., scientific, industrial, governmental). Otherwise, additional resources would be needed to be purchased with the associated cost, effort, and time difficulties (e.g., setup, administration, maintenance, etc.). Thus, this paper delves into the architecture and capabilities of the EN-HPCG grid using two different workload management systems: (i) Slurm (Open-Source) and (ii) PBS Pro (Licensed). This paper compares the performance of the grid between Slurm and PBS Pro in specific high-throughput computing (HTC) applications using the NAS Grid parallel benchmark (NGB) to determine which workload manager is more suitable for EN-HPCG. The evaluation includes grid-level performance metrics such as throughput, and the number of tasks completed as a function of time. Also, the presented methodology aims to assist potential partners in their decision-making process to join the EN-HPCG grid, with a focus on the site speed-up metric. Our results showed that, unless an open-source solution without cost and license problems is an obligation (in which case, Slurm is the viable solution), then it is not advisable to integrate a cluster with high-speed hardware with a cluster possessing outdated hardware when using the Slurm scheduler. In contrast, the PBS Pro scheduler takes into account online decision-making in a dynamic environment using a unified grid. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Technology (Natural Science) is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper presents the topology and machine learning-based intelligent control of high-power PV inverter for maximum power extraction and optimal energy utilization. Modular converters with reduced components economic and reliable for high power applications. The proposed integrated intelligent machine learning based control delivers power conversion control with maximum power extraction and supervisory control for optimal load demand control. The topology of the inverter, operating modes, power control and supervisory control aspects are presented. Simulation is carried out in MATLAB/SIMULINK to verify the feasibility of the proposed inverter and control algorithm. The experimental study is presented to validate the simulation results. The operational performance of the proposed topology is evaluated in terms of operational parameters such as regulation of output power, and load relay control and is compared to existing topologies. The economic performance is also evaluated in terms of power switch sizing and reliability in power delivery concerning switch or power sources failure. [ABSTRACT FROM AUTHOR]

The advent of distributed generation has brought with it a plethora of challenges for the nascent power systems that are being deployed on a large scale. Firstly, the majority of power electronic converters connected to the grid are in current source mode, which results in a lack of inertia and an inability to provide effective inertia or achieve damping support during fluctuations in grid frequency. Secondly, the issue of power quality, caused by the presence of harmonics, is becoming increasingly severe. This is particularly problematic in microgrids or systems with high line impedance, where harmonics can be amplified, thereby further compromising the stability of the power system. To address the deficiency in system inertia, numerous scholars are currently utilizing grid-forming (GFM) technology to achieve virtual inertia. In order to address the issue of system harmonics, it is possible to install active power filter (APF) devices at the point of common coupling (PCC), which serve to mitigate the effects of harmonics. This paper puts forth a proposal for the implementation of an APF with virtual inertia, based on PR + RC composite control. This composite control mechanism serves to enhance the harmonic suppression capabilities of the APF. The introduction of a frequency droop enables the capacitor voltage amplitude to be adjusted during fluctuations in system frequency, thereby achieving virtual inertia and providing active support for system frequency. The experimental results demonstrate that this strategy not only reduces the total harmonic distortion (THD) by 13% in comparison to PI control, indicating excellent harmonic suppression performance, but also allows the system to be inert, achieving positive results in suppressing frequency fluctuations during transients. [ABSTRACT FROM AUTHOR]

This paper designs a novel coordinated control scheme to improve the control performance of voltage source converters (VSC) based multi-terminal high voltage direct current (MTDC) transmission network by merging the benefits of adaptive drooping and voltage margin controllers. In this proposed scheme, the droop coefficient is used to manage the DC voltage and maintain power sharing by shifting the control modes of the rectifiers and inverters in the presence of considerable power disturbances. The droop coefficient is planned based on the stability limit of DC voltage. The performance of the designed control scheme is compared to that of existing coordinated control and voltage margin droop control approaches. A ±400 kV five-terminal VSC-MTDC network is developed in PSCAD to verify the planned control method. The simulation results indicate that the proposed control scheme can achieve good performance for controlling the DC voltage and maintaining active power in the MTDC system. [ABSTRACT FROM AUTHOR]

Distributed photovoltaic (PV) in the distribution network accounted for an increasing proportion of the distribution network, and the power quality of the distribution network of the power quality problem is more and more significant. In this paper, the voltage regulation methods for low-voltage distribution networks containing high-penetration PV are investigated. First, the working principles of the four voltage control methods are introduced: energy storage system configuration, regulating the reactive power output of PV inverters, restricting the active power output of PV, adjusting the switching positions of on-load regulator trap changer and distribution network reconfiguration, and then, in combination with the recent related research, the optimization of each method is compared horizontally with its respective concerns and characteristics. The optimization of each method is compared horizontally with the recent studies to find out the focus and characteristics of each method, and the shortcomings of each method are explored. Coordinated voltage control through multiple flexibility resources has become the mainstream voltage regulation scheme, and distribution network voltage regulation is considered from the perspective of flexibility resources. The three types of flexibility resources, namely, source, network, and storage, have been widely used in distribution network voltage regulation. Although load-side resources have become one of the main regulation resources of the new type of power system, the current study introduces less about the participation of load-side flexibility resources in voltage regulation of LV distribution networks and advancing the application of load-side resources in voltage regulation of LV distribution networks is the focus of future research. Then, the important role of load-side flexibility resources in voltage regulation is described in three parts, namely, the important role of load-side resources, the development trend, and the suggestions for promoting the coordination of source-network-load-storage flexibility resources, aiming to promote the application of load-side resources in voltage regulation in LV distribution networks, and the suggestions and programs are proposed for the technological challenges faced by voltage regulation. In the context of today's new power system emphasizing the interaction of source, network, load, and storage, new technologies and methods for solving voltage problems in LV distribution networks are prospected, with a view to providing certain reference value for the actual operation and optimization of distribution network systems. [ABSTRACT FROM AUTHOR]

This paper deals with the position detection of automated guided vehicles (AGVs) in dynamic resonant-inductive wireless power transfer (WPT) systems. A position detection is necessary to activate the correct transmitting coil. One of the simplest and most effective approaches for a position detection method is to use optical or magnetic position sensors for each coil. However, due to needing a high number of sensors, this technique is relatively expensive. Therefore, an AGV position detection technique based on a reduced number of optical or magnetic sensors (by a factor of two) is proposed. The proposed detection technique was verified experimentally by using a scaled-down prototype of the dynamic WPT system. The proposed approach can be easily implemented by uploading a specific program code to a microcontroller. The microcontroller with the code developed by us was used for processing data from AGV position detection sensors, activating a suitable transmitting coil and controlling an inverter of the dynamic WPT system. As shown by the experiments, due to the proposed approach for the position detection of AGVs and activation of transmitting coils, the number of the position detection sensors is reduced by a factor of two, leading to reductions in the overall cost and level of complexity of the dynamic WPT system without degrading its performance. [ABSTRACT FROM AUTHOR]

This paper presents an innovative control scheme designed to significantly enhance the power factor of AC/DC boost rectifiers by integrating an adaptive neuro-fuzzy inference system (ANFIS) with predictive current control. The innovative control strategy addresses key challenges in power quality and energy efficiency, demonstrating exceptional performance under diverse operating conditions. Through rigorous simulation, the proposed system achieves precise input current shaping, resulting in a remarkably low total harmonic distortion (THD) of 3.5%, which is well below the IEEE-519 standard threshold of 5%. Moreover, the power factor reaches an outstanding 0.990, indicating highly efficient energy utilization and near-unity power factor operation. To validate the theoretical findings, a 500 W laboratory prototype was implemented using the dSPACE ds1104 digital controller. Steady-state analysis reveals sinusoidal input currents with minimal THD and a power factor approaching unity, thereby enhancing grid stability and energy efficiency. Transient response tests further demonstrate the system's robustness against load and voltage fluctuations, maintaining output voltage stability within an 18 V overshoot and a 20 V undershoot during load changes, and achieving rapid response times as low as 0.2 s. Comparative evaluations against conventional methods underscore the superiority of the proposed control strategy in terms of both performance and implementation simplicity. By harnessing the strengths of ANFIS-based voltage regulation and predictive current control, this scheme offers a robust solution to power quality issues in AC/DC boost rectifiers, promising substantial energy savings and improved grid stability. The results affirm the potential of the proposed system to set new benchmarks in power factor correction technology. [ABSTRACT FROM AUTHOR]

Due to increasing load demand and the energy crisis, microgrids (MGs) have attracted more attention. The idea and technology of microgrids (MGs) have undergone significant advancements largely aimed at enabling the automation of distribution systems and enhance the integration of renewable energy sources (RESs). In this paper, the MG is a combined form of various distributed generations (DGs), battery energy storage system (BESS), and plug-in hybrid electric vehicles (PHEVs). A novel approach is introduced to minimize the operational expenses of the grid-connected low-voltage microgrid by leveraging a probabilistic expert optimization technique. This methodology takes into account various factors such as power supply costs, power dissipation, PHEV charging requirements, and the optimal capacity of BESS. Three charging techniques are proposed in this paper to control the PHEVs' charging demand at homes and public charging stations. This study employs a comprehensive model to simulate a whole day, accounting for the stochastic charging requirements of PHEVs, load profiles, RESs outputs, and variations in energy price. To address the inherent nonlinearity of the optimization problem, the energy management within the MG is tackled using the slime mould algorithm, a population-based stochastic optimizer. The primary goal is to minimize operational costs in the microgrid by optimizing the efficient utilization of available resources. [ABSTRACT FROM AUTHOR]

The Modular Multilevel Converter (MMC) is a promising converter for medium-/high voltage applications due to its various features. The waveform quality could be enhanced further by expanding the number of generated voltage levels, which increases the number of submodules (SMs); however, this improvement enlarges the size and cost of the converter, posing a persistent challenge. Hence, there exists a trade-off between power quality and the size and complexity of the converter. To verify the performance of such a complex converter and to validate the effectiveness of the control system, especially in the absence of a physical system, Real-Time (RT) simulation becomes crucial. However, the large number of components of a MMC creates important numerical challenges and computational difficulties in RT simulation. This paper proposes a grid-connected MMC employing a Z Packed U-Cell converter as a SM to generate a higher number of voltage levels while minimizing the required number of SMs. The ZPUC-MMC is implemented on an FPGA-based RT simulation platform using Electric Hardware Solver to reduce computational burden and simulation time, while improving the accuracy of the obtained results. Conventional controllers of MMCs are applied to assess the effectiveness and robustness of the proposed system during steady-state and dynamic operations. [ABSTRACT FROM AUTHOR]

Considering the smart grids establishment, where the presence of nonlinear loads and new power generation sources become increasingly expressive, there is a potential for unknown disturbances occurrence. Besides, given the huge amount of data coming from smart meters, it is important to preserve the relevant information and promote efficient storage of the data. Novelty Detection (ND) techniques can be used to address these challenges. The Stockwell Transform (ST) is a time–frequency distribution that has shown a great ability to detect novelties related to stationarity changes in signals. It can be applied to voltage and current signals from the grid. Therefore, the main contribution of this paper is to provide an FPGA real-time implementation of an ST-based novelty detector. Novelty detection goes beyond classic electrical disturbances well known in the area of power quality, as it relates any novelty event to a stationarity change in the analyzed signal. To perform the implementation in FPGA platform, the use of a soft-core processor is proposed to optimize the hardware resources of the FPGA. In addition, a strategy of voice selection is proposed to reduce the complexity and execution time of the algorithm in real-time implementation, while maintaining the detection capability. The proposed ND technique was implemented in a low-cost FPGA-based functional prototype, where synthesized and field-recorded real signals were applied, attesting the ND performance. The reported tests show that the strategies adopted for real-time implementation provided an optimization of hardware resources and enabled the execution of the ST algorithm and determination of the novelties. [ABSTRACT FROM AUTHOR]

Peer-to-peer energy trading is an innovative idea that overcomes several technological and industrial hurdles. It allows industries and consumers, including knowledgeable prosumers, to trade excess energy with distributed generation sources, such as solar, wind, and electric vehicles, thus promoting a significant reduction in overall energy consumption. Real-Time Pricing (RTP) is increasingly essential in integrating smart home device Demand Response (DR) strategies. RTP improves energy management and enables customers to respond intelligently to price fluctuations. In this vein, this paper proves how DR and peer-to-peer (P2P) energy trading could affect energy prices by allowing producers (consumers) and smart home users to interact directly rather than through the traditional grid. The two-pronged planning approach substantially contributes to the reduction of electricity costs. DR enables P2P energy trading, while deep learning algorithms adapt smart home devices to RTP dynamics. Simulation results show that using P2P energy trading and DR in smart homes can significantly eliminate costs. This hybrid approach increases the energy efficiency of Smart Grid (SG) 2.0 technology and makes it more adaptable and cost-effective. [ABSTRACT FROM AUTHOR]

With the advancement of regulations regarding the reduction in carbon emissions, renewable energy communities have come into the picture. However, many implications come with the installation of these communities from a cybersecurity point of view. The software platforms responsible for managing and controlling them handle a lot of crucial information, and therefore, tampering with these data can lead to several impacts on the operation of these communities and, in turn, the power grid as well. This paper examines the plausible impacts that can be caused by altering certain parameters of the system that make it a potential cyber attack target. The analysis is done by observing how the grid responds to these manipulations for both low-voltage as well as medium-voltage systems. These systems are designed along with integrated energy communities and are implemented in MATLAB/Simulink R2022b software. The observations are made by plotting the grid voltage and power profiles in normal as well as attacked conditions. [ABSTRACT FROM AUTHOR]

This paper describes research on the harmonic-distortion capacity of a single-stage photovoltaic (PV) 3.68 kWp generator in a microgrid configuration. An overview of various harmonic compensator methods used in PV generators is presented to evaluate their advantages and disadvantages. Proportional-resonant (PR) structures with harmonic compensators (HCs) are designed, modeled, and validated through real-time tests. The modeling of harmonic compensation structures for a photovoltaic inverter using MATLAB/SIMULINK R2022a is explained in detail. The harmonic compensation capacity of a PV generator inverter is studied under voltage harmonics, grid frequency variation, and voltage unbalance. The contributions of this work are, firstly a bibliographic analysis of various strategies currently used for harmonic compensation in grid-connected inverters and secondly, a detailed explanation of the modeling of harmonic compensation structures using MATLAB/SIMULINK. Finally, a demonstration of the improvement in energy quality that results from using harmonic compensation techniques in photovoltaic generators in microgrid configurations affected by grid disturbances is performed. The obtained results show that harmonic compensation strategies based on resonant filters are a good alternative for the reduction of harmonic voltage distortion in the presence of grid disturbances such as frequency variation and voltage unbalance. [ABSTRACT FROM AUTHOR]

With the increasing demand for electricity, microgrid systems are facing issues such as insufficient backup capacity, frequent load switching, and frequent malfunctions, making research on microgrid resilience crucial, especially to improve system power supply reliability. This paper proposes a method for analyzing the resilience metric of new energy grid-connected microgrid system, and proposes optimization strategies to improve resilience. Firstly, a measurement method for the resilience of the microgrid system is established based on the operating characteristics of the system components. Secondly, the sensitivity relationship between system resilience and parameters is established, and an optimization model for resilience improvement strategies of microgrid systems based on parameter sensitivity is constructed. Finally, simulation verification is conducted based on the IEEE 37-node microgrid system. The results show that the proposed measurement method can scientifically and reasonably measure the resilience of the microgrid system, and the resilience improvement strategy significantly improves the operational resilience, verifying the effectiveness and robustness of the proposed analysis method. [ABSTRACT FROM AUTHOR]

Modern power systems have several measurement devices for reliable, safe, and improved operation and control. Due to the high infiltration of inverter‐based resources, protecting modern power systems has become challenging. This paper proposes a new protection scheme based on the computation of 'discrepant impedance' using real‐time protocol services for data exchange. The sampled values of voltages and currents are transmitted to a central processing unit to implement the protection scheme. With the development of digital instrument transformers (IEC 61869‐9), the current and voltage samples are directly interfaced wired or wirelessly to the IEC 61850‐9‐2 process bus. The proposed protection scheme is validated with grid forming and grid following inverters on Consortium for Electric Reliability Technology Solutions (CERTS) microgrid network using a real‐time digital simulator. The protection scheme is independent of the type of energy sources and their control philosophy, operation modes and topology of the microgrid network. [ABSTRACT FROM AUTHOR]

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to preventing malfunctions and faults in electric assets and connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic—the supraharmonic 2 kHz to 150 kHz range. This range is not populated by easily recognizable harmonic components of the 50 Hz to 60 Hz mains fundamental, but by a combination of intentional emissions, switching non-linearities and byproducts, and various types of resonances. This paper aims to provide a detailed analysis of the impact of supraharmonics (SHs) on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and the heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference with equipment and power line communication (PLC) technology in particular. Under some shareable assumptions, limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with a specific focus on their accuracy. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Xinjiang University (Natural Science Edition) is the property of Xinjiang University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Static compensators (STATCOMs) are often used in distribution systems to enhance power quality. There is a need to enhance the performance of STATCOM to optimize its utilization and facilitate the provision of additional ancillary services. This paper employs the multilayer discrete noise-eliminating second order generalized integrator (MDNESOGI) to regulate the quasi-impedance source inverter (qZSI)-STATCOM for power exchange with the grid. Compared to conventional second-order generalized integrator (SOGI), MDNESOGI exhibits a higher capability for rejecting DC offset. In instances of abnormal grid operation or system malfunction, the inclusion of DC rejection capability enhances the robustness and reliability of the system. The suggested control algorithm only requires two integrators, three mathematical operators, and a damping factor, making it far easier to implement than transformation-based methods. The distorted load current is broken down into its active and reactive components using this control mechanism. The reference currents are then calculated by multiplying these parts by their corresponding voltage standards. The DC offset is reduced and transient oscillations in the weight component are eliminated by adjusting the damping factor. The suggested algorithm effectively handles power quality tasks like (a) reducing harmonic distortion, (b) compensating for reactive power, (c) adjusting for power factor, and (d) balancing the load under different conditions in the distribution system. The experimental study results are used to examine the stability of the proposed control scheme in both static and dynamic scenarios. In addition, a comparison to traditional methods is provided to demonstrate the new method's superiority. Experimentation results show that the suggested controller is superior to its contemporaries in all scenarios where power quality is a factor, meeting the IEEE standard requirements. [ABSTRACT FROM AUTHOR]

Optimal power flow (OPF) analysis enables the in-depth study and examination of islanded microgrid design and operation. The development of the analysis framework, including modeling, formulating, and selecting effective OPF solvers, however, is a nontrivial task. As a result, this paper presents a tutorial on an OPF modeling framework, offering a mathematical model that can be readily implemented using established open-source software tools such as OpenDSS, Pyomo, and IPOPT. The framework is versatile, capable of representing single-phase and unbalanced three-phase islanded microgrids. Various inverter models, such as those of grid forming and following equipped with their operating characteristics, can be incorporated. The efficacy of the proposed framework is demonstrated in studying the OPF of single-phase and three-phase microgrids. [ABSTRACT FROM AUTHOR]

In this paper, with the development of an intelligent power system idea, sustainable energy sources were increasingly deployed, including transmission and distribution systems networks. As a result, optimal use of cascaded H-bridge inverter topologies (MLIs) and power distribution operations is critical for long-term power generation. Traditionally, selective harmonics reduction models must be performed to achieve the optimal switching frequency of multilevel inverters. This research aims to determine the switching frequency for wind-incorporated multilevel inverters to reduce overall harmonic components used in grid applications. This research adds towards the best possible solution by employing multiple newly established adaptive optimization techniques: MNSGA-II and salp swarm. The well-known genetic algorithm and particle swarm optimization are used for the wind-tied multilevel inverters optimization issue. Sevenlevel, eleven-level, and fifteen-level MLIs were employed to reduce overall harmonic distortion. The reliability and convergence rate of simulated data with various modulation indices for seven-, eleven-, and fifteen-level MLIs are obtained and compared. Models are developed based on MATLAB Simulink and are used to validate quantitative measurements. [ABSTRACT FROM AUTHOR]

The creation of features makes the difference in improving the photovoltaic forecast (PVF) for on‐grid, hybrid and off‐grid PV systems. The importance of the PVF is tremendous, and it can be essential in optimizing the home appliances to maximize the Renewable Energy Sources (RES) usage or to create performant bids for the electricity market. Several use cases are considered from the connectivity point of view. Therefore, in this paper, we propose a Weather Prediction Error (WPE)‐based method that uses a Stacking Regressor (SR) for various PV systems that coexist in the emerging Energy Communities (EC) landscape. The novelty of the research we conduct consists in proposing several features and determining the coefficients to adjust the PVF based on WPE. The forecast results of four types of PV systems from size and connectivity point of view are investigated. Compared with individual Machine Learning (ML) models, R2 increases with more than 3% with the SR and with more than 6% after applying the adjustment coefficients. Nevertheless, the major improvement is recorded for the off‐grid inverter and for the large industrial PV power plant, demonstrating that the proposed model is suitable for these types of systems. The other metrics improved as well, especially Mean Average Error (MAE) that decreases between 10% and 23%. A significant decrease is in the case of the industrial on‐grid PV, from 130 kW to 123 kW using the SR and to 107 kW after adjustments. This represents around 18% from the initial MAE. The ratio of daily deviations is also improved using the SR. For all the PV systems, the ratio stabilizes in a shorter interval, from daily values between 0.78 and 1.33 obtained with the ML models to values between 0.83 and 1.24 obtained with the SR. After the final adjustments, the interval becomes shorter, having daily values between 0.90 and 1.10. [ABSTRACT FROM AUTHOR]

In response to the need for smaller and lighter power supply equipment, there has been a push towards higher power density in current power electronic converters. This development aligns well with the requirements of photovoltaic grid‐connected inverters. Among various passive filters utilized in these inverters, the LCL filter stands out as a popular choice. Nevertheless, it should be noted that traditional LCL filters have limited core utilization and exhibit significant redundancy. In view of the above problems, this paper proposes a magnetic integrated passive filter based on ripple transfer technology and carries out volume optimization design. Compared to the conventional LCL filter, the magnetic integrated passive filter offers a reduction in size and weight while preserving its capability to ripples attenuate. Finally, a laboratory prototype with a rated power of 2 kW is built to verify the effectiveness of the proposed magnetic integrated passive filter. [ABSTRACT FROM AUTHOR]

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In recent years, with depletion of fossil fuel and exponential increase of power demand meeting the customer needs become a significant challenge for service providers. In this paper, Internet of Things (IoT) based bidirectional converter (BC) is designed which enhances the power electronics converters into the next platforms. This bidirectional converter is built with wireless connectivity. Also, the cluster is built in the series of diverse downwind distances (i.e., between the turbines) can be tested with minimum rearrangement effort. In IoT equipped bidirectional converter farm is evaluated in offline mode by collecting the data remotely. The proposed BC is able to operate in renewable energy (like photovoltaic, wind, etc.) based standalone systems. This BC converter is proposed to transfer power from grid/ renewable energy systems to a battery storage system (BSS) as well as BSS to grid power transfer. The proposed work of cascade topology allows maintaining input voltage as well as output voltage level. During discharging, the energy from a battery pack is returned to the grid where the dc link bus is interconnected with electric traction inverter. Input and output voltage values of the converter are used to fix the reference voltage subject to the power demand requirement. Artificial neural networks are used to regulate the voltage of dc link capacitor. The performance of the proposed BC regarding voltage gain, efficiency, and flexible application have been analysed using MATLAB simulation and also with experimental studies. [ABSTRACT FROM AUTHOR]

Summary: Grid‐connected inverter with a novel fractional‐order LLCL filter has the advantage of high grid current tracking accuracy and low total harmonic distortion without passive or active dampers, and the grid voltage full feedforward scheme is an effective method to improve the quality of grid current. However, due to the digital control delay, the suppression of the grid current harmonics is weakened, and the inverter output impedance has an additional negative phase shift, which deteriorates the stability of grid‐connected systems under weak grid. In this paper, a weighted grid voltage fractional‐order feedforward control scheme is proposed based on a quasi‐proportional resonant (QPR) controller, which introduces two weighting factors in the full feedforward path of the grid voltage and compensates the phase lag of the output impedance by designing appropriate weighting factors. Then, an improved scheme combining the QPR controller with a phase compensator is presented. As a result, the suppression ability of grid current harmonics and the adaptability to grid impedance variations are enhanced. Simulation and experimental results verify the effectiveness of the proposed grid voltage fractional‐order weighted feedforward scheme. [ABSTRACT FROM AUTHOR]

The power industry is currently undergoing a rapid transformation toward the maximum utilization of renewable energy resources. In grid-connected renewable energy systems, enhancing the voltage stability during the fluctuations in renewable energy outputs can be achieved using a transformer with built-in on-load tap changing. It is one of the main traditional voltage regulation techniques utilized to improve the voltage profile in the power grid. Due to the unpredictable nature of renewable energy penetration, the frequent operation of an on-load tap changer (OLTC) may increase significantly. Despite the proposed methods used to optimize the location and size of renewable generation, there is a lack of empirical or detailed studies that have been looking at the issue of tap changers, mainly the impact of renewable energy storage allocation. The main aim of this paper is to find a compromise approach to mitigate unnecessary tap-changing operation time by wisely siting and sizing the renewable energy storage system (RESS). Initially, a generalized method is proposed to formulate an analytical optimization framework coupled with a renewable storage index. This approach is employed to evaluate the behavior of OLTC in a grid-connected renewable energy system. The formulation is then used to model a decision-making approach to confirm the location and size of RESS, using the analytic network process (ANP) with entropy and technique for order of preference by similarity to an ideal solution (TOPSIS). The performance of the proposed approach is evaluated and compared using the IEEE benchmark networks. Aspects in relation to the predictions of future operations about the management of renewable energy storage in coordination with voltage regulators in the smart grid context, that will be the subject matter of additional studies are also discussed. [ABSTRACT FROM AUTHOR]

According to recent power quality studies, voltage sags and voltage unbalance in medium-voltage and low-voltage distribution grids are the most common type of power quality problems. Power quality is an essential concern in the modern power system that can affect consumers and utility. In modern age, with an increase in sensitive and expensive electronic equipment, power quality is essential for the power system's reliable and safe operation. This paper proposes a hybrid technique-based unified power quality conditioner (UPQC) of microgrid in an EV charging station (EVCS), and it is the combination of recalling-enhanced recurrent neural network (RERNN) and sand cat swarm optimization (SCSO), together called as RERNN-SCSO. The SCSO creates the converter control signal, and the RERNN method forecasts the control signal from SCSO method. The proposed technique consists of series-active power filter (Se-APF), shunt-active power filter (Sh-APF), and DC-side capacitor as the parts of proposed technique. The major purpose of RERNN-SCSO technique is used to increase the power quality. Many loads, like highly inductive NLL, nonlinear loads (NLL) as well as unbalanced NLL (UNLL), are all linked at the point of common coupling (PCC). When the major structure of UPQC is built into the EVCS, an additional alternating current (AC)/DC converter will help with initialization. At this, the charging position provides charging service to the EVs as well as discharges the EVs into the power grid. The novelty of the proposed work consists in connecting EVs in parallel to the UPQC DC-side using double-layer microgrid (MC) and DC–DC converter. The proposed method ensures EV charging while efficiently handling quality of power issues like harmonic current, voltage disturbance, voltage sag and swell and voltage unbalance. RERNN-SCSO method performance is performed on the MATLAB/Simulink software to analyze the working performances and related with present techniques. RERNN-SCSO method-based THD under voltage sag condition as 2.03% and swell as 2.01%, which is lower than the existing methods. [ABSTRACT FROM AUTHOR]

This paper is focused on the modeling and simulation of a hysteresis current-mode regulated high-gain DC–DC converter intended for solar applications. First, the study effort outlined the working principle of a novel high-gain DC–DC converter scheme called a double-switch SEPIC-buck converter (DSSB). This work also presents the dual hysteresis current control technique, which aims to enhance the system's performance and lower the harmonic content of its voltages and currents. Two dual hysteresis current controllers independently control the source and load currents of the proposed converter. The frequency and hysteresis bandwidth are also simultaneously set using the two controllers. Compared to other standard DC–DC converters (buck, SEPIC, boost, and buck-boost), DSSB has better efficiency, a larger voltage gain, and superior dynamic characteristics. The suggested topology has a peak efficiency of 95% and a voltage gain of 1 + D D / 1 - D . The suggested DSSB converter has a THD of 6.6% and an efficiency of 97–98% when compared to various DC–DC converters, while the conventional SEPIC converter, along with boost, buck, and buck-boost converters, have a THD of 10% and an efficiency of 95–97%. Additionally, the DSSB converter has a far smaller crest factor than all other DC–DC converters, including boost, buck, buck-boost, and SEPIC. The suggested converter's performance is theoretically assessed using simulations based on Matlab/Simulink software under various circumstances. The results of simulation work in Matlab/Simulink corroborate the findings of the analysis and investigation. [ABSTRACT FROM AUTHOR]

This research explores the application of neural networks in managing grid-photovoltaic (PV) systems. this paper aims to improve the performance and reliability of PV systems using artificial intelligence capabilities, specifically neural networks. The main emphasis of this system is to control active and reactive power and to track the maximum power point (MPPT). This study introduces an intelligent control technique for fuel cell distributed generation (DG) grid connection inverters. The algorithm allows for the management of both active and reactive power for the unit. The algorithm provides local reactive power compensation, making it economically viable. The controller modeling and performance validation are conducted using MATLAB/Simulink and Sim power system blocks, demonstrating its capacity for enhancing power factor. This makes fuel cell technology a clean, highly controllable, and economically viable option for DG systems. The system maximizes the energy extraction of PV panels and maintains them at their ideal PowerPoint across various environmental conditions. It also raises the voltage from 260 volts to 350 volts. Simulations and practical evaluations validate the proposed control system. The obtained results indicate that the total harmonic distortion (THD) of the grid current under operating conditions was less than 1.86%. This demonstrates significant improvements in the efficiency and reliability of PV systems. The neural network controller shows remarkable flexibility and the ability to quickly adapt to fluctuations in load and radiation, which contributes to developing a more sustainable and stable energy network. [ABSTRACT FROM AUTHOR]

This paper investigates the challenges in the grid caused by high penetration of photovoltaic (PV) systems and measures to achieve efficient islanding detection during grid abnormalities. To achieve this an islanding classification approach is developed by using a multi-layer perceptron neural network (MLPNN) to train with the possible islanding scenarios that can occur in a grid. The proposed approach aids the grid-connected system to isolate the healthy portion from the faulty portion of the system and ensure uninterrupted operations of the system even in the case of fault and grid maintenance. The performance of the proposed method was tested on the data obtained for different grid abnormalities simulated on a grid-connected photovoltaic system using a Typhoon-HIL environment. The obtained results depicted 95.6% training efficiency and 98.3% testing efficiency, and the trained approach can effectively detect an islanding scenario in 0.02 s with 1.7% misclassification error. [ABSTRACT FROM AUTHOR]

The quasi-Z-source inverter (qZSI) become one of the most promising power electronic converters for photovoltaic (PV) applications, due to its capability to perform a buck-boost conversion of the input voltage in a single stage. The control strategy based maximum power point tracking (MPPT) and proportional integral (PI) controller are well known in grid-connected with traditional configuration but not in qZSI. This paper presents a control strategy for qZSI grid-connected based on the MPPT algorithm and the linear control by PI controllers. This is complemented by the capability to efficiently transfer the harvested power to the grid, ensuring a unity power factor. The proposed control strategy effectively separates the control mechanisms for the direct current (DC) and alternating current (AC) sides by utilizing the two control variables, the shoot-through duty ratio and the modulation index. An adapted space vector modulation technique is then utilized to generate the switching pulse width modulation (PWM) signals, using these two control variables as inputs. The proposed approach was tested and validated under MATLAB/Simulink and PLECS software. [ABSTRACT FROM AUTHOR]

A dual output dual-frequency (DODF) resonant converter-based AC-AC induction heating (IH) by using asymmetrical duty cycle (ADC) control is presented in this paper. The proposed scheme gives two outputs with independent power control, which improves input power factor and achieves zero voltage switching (ZVS) with a wide range of operations. It includes two pairs of two half-bridge series resonant converters, each pair having one common capacitor along with various resonant frequencies. These converters are modulated with the ADC control scheme to obtain smooth operation. The proposed topology doesn't use the DC stage; it is directly connected to the power supply to produce high-frequency AC output. With the use of direct connection, the converter components are reduced when compared to conventional converters. There will be a reduction in voltage drop, power losses, cost of the converter and which will result in improved efficiency. Simulation results are obtained from PSIM 11.1.7 software. This scheme controls two different loads with an efficiency of 98.25%. [ABSTRACT FROM AUTHOR]

This paper proposes a robust protection technology to enhance the grid-connected capability of the doubly fed induction generator (DFIG) based on wind turbines (WTs) under low voltage ride through (LVRT) conditions. The proposed method to control the rotor side converter (RSC) and grid side converter (GSC) uses proportional–integral (PI) controllers. The protection devices are the static compensator (STATCOM), crowbar, series dynamic resistor (SDR), and DC-chopper, with the proposed method to control STATCOM using proportional–integral (PI) controllers and the proposed method to control the rest of the protection devices based on the allowable threshold values of rotor current and DC-link voltage. The protection coordination strategy between them is proposed to avoid the disconnection between the rotor circuit and grid, maintain the DC-link at constant voltage, enhance the dynamic response of WT, and improve the voltage response at the point of common coupling (PCC) of WT. The DFIG-WT of 2 MW-575 V connecting to the 34-bus IEEE network is carried out to verify the effectiveness of the proposed method under the conditions of symmetrical and asymmetrical faults, and the LVRT requirements of the Spanish grid code are considered. The obtained simulation results using the PSCAD/EMTDC software show that the rotor current, DC-link voltage, voltage PCC, and power oscillation damping are significantly improved compared to not using it or applying the conventional method based on passivity theory. Therefore, the LVRT capability of the proposed DFIG-WT system is significantly enhanced, and it has enough ability to continue to provide electrical energy to the power network. [ABSTRACT FROM AUTHOR]

This paper proposes an improved Wind Turbine Emulator (WTE) structure using Sliding Mode Control (SMC) technique based on the Two-Phase Induction Motor (TPIM) for software simulation laboratory purposes. Since the power electronic converters application with various control strategies in the AC machine drive field facilitates the wind turbine characteristics imitation, an advanced SVM controlled-2ϕ-inverter is adopted. Considering the asymmetry between the TPIM main and auxiliary windings, mathematical equations were studied allowing control of the speed and the torque under different conditions. The 2-phase-inverter is controlled through an appropriate adjustment of four space voltage vectors. In order to enhance the speed and flux regulation loops and to increase the system robustness against the motor parameters variation and the wind sudden fluctuations, the SMC theory, which contains the adaptive rotor flux observer is used here to develop a control law that governs the system to track the reference speed set by the WT mathematical model to obtain the desired output. Several parameters, such as electromagnetic torque, rotor fluxes, stator currents, and rotor speed, were analyzed. Static and dynamic characteristics and the WTE transient and steady-state responses are satisfactorily reproduced by the proposed emulator scheme. [ABSTRACT FROM AUTHOR]

This paper addresses a comprehensive review on various adaptive grid-following inverter control schemes developed for enhancing the power quality in renewable energy generation systems (REGS). The grid interfacing inverter with various adaptive control schemes has been well researched in recent years and their performance has been found with better characteristics compared to the conventional control schemes. Better fundamental component separation (FCS), dc offset rejection, grid synchronization, amplitude tracking, frequency tracking, phase angle estimation, and low complexity are the few silent features of the adaptive-based control schemes. This survey is very useful for researchers who are working on power quality, AC and DC Microgrid, grid-connected inverter control, multilevel inverter, power electronics, and other related research areas to select the suitable controller for grid interfacing inverter. This paper also focuses the power quality issues, basic standards, power quality monitoring schemes, and solutions. Moreover, power quality improvement techniques by using the power quality conditioners with adaptive control schemes are discussed in the paper. Finally, an extensive comparative study of the recently developed control techniques is performed to select a suitable controller in terms of better FCS, dc offset rejection, grid synchronization, amplitude tracking, frequency tracking, phase angle estimation, and low complexity for grid-following inverter in REGS applications. [ABSTRACT FROM AUTHOR]