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Arc devices are among the receivers with the highest power connected to power systems. Due to dynamic load changes, these receivers generate a number of disturbances that affect the quality of electric power. The most important disturbances include voltage fluctuations. It is also worth mentioning the asymmetry and deformation of the supply voltage curve. This article discusses the mutual interaction of receivers operating in parallel, operating stably, and devices with dynamic current consumption. Calculations based on model tests and the results of parameters characterizing the quality of energy, which were recorded in the line supplying the steelworks, are presented. The power supply conditions (power of the short-circuit network) were assessed to influence the degree of suppression of voltage fluctuations by loads with stable current consumption. [ABSTRACT FROM AUTHOR]

ABSTRACT In low‐voltage applications using low‐Q LC filters, alias‐free capacitor voltage acquisition can be achieved, but synchronous capacitor voltage sampling under high‐Q filters used in high‐voltage applications in grid‐forming converters causes some degree of distortion and results in degradation of the power supply quality. And the inherent 1.5 sampling periods that delay in this approach limit the control bandwidth, reduce the stability region, and result in an inadequate time domain response. Despite these shortcomings, this approach is widely accepted in practice. The conclusion of this paper is that shifting the capacitor voltage sampling instant to 2 µs before the pulse width modulation (PWM) reference voltage update results in almost the same distortion as synchronous sampling. However, it can improve the dynamic performance of the system. A distortion‐acceptable univariate feedback voltage dual‐loop active damping control topology with much reduced computational delay is proposed, which is based on an internal active damping loop using a discrete lead compensator and a proportional resonance controller in the external voltage loop. [ABSTRACT FROM AUTHOR]

To solve the problem of negative‐sequence and reactive power in electrified railway, this paper proposes a comprehensive compensation method based on V/v transformer and electromagnetic single‐phase var compensator (ESVC) for co‐phase power supply. First, based on the principles of static var generator and single‐phase rotary phase shifting transformer, the topology and model of ESVC have been established, and the compensation mechanism has been analysed. Second, the topological structure and mathematical model of co‐phase power comprehensive compensation device (CPCD) are put forward based on the principles of V/v transformer and ESVC, and the operation mode of CPCD in multiple scenarios is designed. Then the strategy of CPCD with double closed loop control is analysed: corresponding compensation mode is selected according to negative‐sequence unbalance degree and expected power factor value. In this strategy, the compensated current output by ESVC is taken as the quantity of external loop control, and the rotation angle of ESVC is taken as the quantity of internal loop control to realize double‐closed loop control of CPCD. Finally, the comprehensive CPCD compensation model is built on the simulation platform and validated the accuracy of the mathematical model and the effectiveness of the control strategy. [ABSTRACT FROM AUTHOR]

This paper examines the problem of synthesizing a two-loop control system for a three-phase voltage source inverter designed for an autonomous power supply system. This type of DC/AC converters is an essential part of power supply systems with renewable energy sources as primary sources, and, accordingly, must corresponds to the requirements for the electric power quality. These requirements are met through circuit design solutions, as well as through the construction of high-precision automatic control systems. The system integrates: a hydrogen electrolyzer, a hydrogen storage system, and a hydrogen fuel cell. The paper proposes a method for calculating the parameters of PI controllers with resonant components, based on the time-scale separation method and allowing independent adjustment of the controller components. The introduction of a resonant component ensures high tracking accuracy for a desired main voltage harmonic and selective suppression of external harmonic influences. The proposed approach allows to synthesize an automatic control system that significantly improves the quality of the voltage inverter output parameters. [ABSTRACT FROM AUTHOR]

In this research, we investigate the power quality of the grid where an Electric Arc Furnace (EAF) with a very high load operates. An Electric Arc Furnace (EAF) is a highly nonlinear load that uses very high and variable currents, causing major power quality issues such as voltage sags, flickers, and harmonic distortions. These disturbances produce electrical grid instability, affect the operation of other equipment, and require strong mitigation measures to reduce their impact. To investigate these issues, data are collected from the Point of Common Coupling where the Electric Arc Furnace is fed. The following three main factors are identified for evaluating power quality: apparent power, active and reactive power, and distorted power. Along with these powers, Total Harmonic Distortion, an important indicator of power quality, is calculated. These data are collected during the full process of producing a complete steel batch. To create a Deep Neural Network that can model and forecast power quality parameters, a network is developed using LSTM layers, Convolutional Layers, and GRU Layers, all of which demonstrate good prediction performance. The results of the prediction models are examined, as well as the primary metrics characterizing the prediction, using the following: MAE, RMSE, R-squared, and sMAPE. Predicting active and reactive power and Total Harmonic Distortion (THD) proves useful for anticipating power quality problems in an Electric Arc Furnace (EAF). By reducing the EAF's impact on the power system, accurate predictions will anticipate and minimize disturbances, optimize energy consumption, and improve grid stability. This research's principal scientific contribution is the development of a hybrid deep neural network that integrates Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), and Gated Recurrent Unit (GRU) layers. This deep neural network was designed to predict power quality metrics, including active power, reactive power, distortion power, and Total Harmonic Distortion (THD). The proposed methodology indicates an important step in improving the accuracy of power quality forecasting for Electric Arc Furnaces (EAFs). The hybrid model's ability for analyzing both time-series data and complex nonlinear patterns improves its predictive accuracy compared to traditional methods. [ABSTRACT FROM AUTHOR]

The increasing energy consumption and changing load variations place a significant burden on the sophisticated utility grid, which affects the source's dependability and quality. Researchers examining modern power networks must focus on those factors to prevent grid breakdowns. Superior power quality (PQ) is still intended to make sure everything runs smoothly under diverse organizations. The main cause of PQ problems, however, is now renewable energy used in power electronic converters that are integrated into the electrical grid. Even though new, better solutions are still being developed, adhering to international standards have been strongly advised. Consequently, microgrid clusters powered through renewable energy and incorporating multiple structures in an urban area has been proposed in this paper. This increases the dependability of the power sources by managing the energy that is available inside the cluster instead of having it focused around the utility grid. Additionally, a deep belief network model based on Improved Dwarf Mongoose Optimization is recommended for regulating the inverter by generating optimal pulse‐width modulated signals that increases the quality of the power supplies. When compared to other conventional techniques, the suggested technique possesses less real power and reactive power setting duration of 0.8 ms and 0.75 ms, respectively. [ABSTRACT FROM AUTHOR]

Industrial end-users always demand for better power quality to retain grid's efficiency and maintain machinery health. However, increasing complexity of multiple energy systems increase the risk of deterioration in the quality of power supplies. An effective power quality disturbances detection tool is highly needed to automatically detect the unusual event exhibiting inside the systems. Power quality disturbances can be categorised into two category. i.e. (a) short and fast transient disturbances and (b) long and slow disturbances, which complicates the process of classification using similar model. In this paper, a hybrid deep learning model consisting of multi-resolution transformation and deep neural network is proposed for power quality disturbances detection. Transformer network has been proposed to improve the classification and computation performance with its multi-head attention mechanism and parallel computing characteristics. The proposed hybrid model first transforms input signal into multiple frequency components using multi-level signal decomposition signal via wavelet transform. A layer of convolutional kernel is used to obtain the spatial and temporal features from the wavelet components. The process is followed by higher order latent feature extraction using transformer network which includes a layer of transformer encoder and a pooling mechanism. The proposed model is able to outperform other deep neural network models with better accuracy despite of the noisy condition. [ABSTRACT FROM AUTHOR]

The noticeable dynamic development of electromobility poses new challenges for the energy industry and users of electric vehicles. One of these challenges is coping with the change in the way we refuel. In the case of electric vehicles, the batteries can also be charged via home electrical installations. The presence of a new, non-linear load with significant power may affect the quality parameters of electricity in this installation and therefore indirectly affect the operation of other loads. In order to investigate the possible impact of the electric vehicle charging process on these parameters, a number of measurements were carried out. This paper presents the results of observing voltage distortions in the installation as a result of the harmonics of the current supplying the AC/DC converter in the vehicle. The test results confirm the compliance of the voltage with the requirements of the standards; however, the large share of current harmonics requires the analysis of the anti-shock protections existing in the installation to ensure that they are effective when currents at higher frequencies flow. The research results may be a guide for designers and users of home electrical installations. [ABSTRACT FROM AUTHOR]

In view of the complexity and importance of nuclear research reactor (NRR) installations, it is imperative to uphold high standards of reliability and quality in the electricity being supplied to them. In this paper, the performance of low-voltage (LV) distribution feeders integrated with NRRs is improved in terms of reduced distribution loss, improved voltage profile, and reduced greenhouse gas (GHG) emissions by determining the optimal location and size of photovoltaic (PV) systems. In the second stage, the power quality of the feeder is optimized by reducing the total harmonic distortion (THD) by optimally allocating D-STATCOM units. In the third and fourth stages, the reliability and resilience aspects of the feeder are optimized using optimal network reconfiguration (ONR) and by integrating an energy storage system (ESS). To solve the non-linear complex optimization problems at all these stages, an efficient meta-heuristic Chernobyl disaster optimizer (CDO) is proposed. Simulations are performed on a modified IEEE 33-bus feeder considering the non-linear characteristics of NRRs, variability of the feeder loading profile, and PV variability. The study reveals that the proposed methodology can significantly improve the service requirements of NRRs for attaining sustainable research activities. [ABSTRACT FROM AUTHOR]

The impact of the quality of electricity on the pantograph is an important parameter for the supply of locomotives in railway companies (RCs). The subject of this research is the analysis of the quality of electricity on the pantograph of the 441-series locomotivelocated at distances of 1 km or 35 km from the power station in the electric traction system of Serbian Railways. The analysis included the simulation of the system in the MATLAB-Simulink software package (R2016a), which resulted in data that were often difficult to measure due to the complexity of the electric traction system. The obtained values indicate that the total harmonic voltage distortion on the pantograph of the 441 locomotive is 16.34% for 1 km and 51.06% for 35 km, while the EN 50160 standard prescribes a maximum of 8%. The total harmonic distortion current in the electric traction substation and through the locomotive pantograph is 33.42% (for 1 km) and 32.53% (for 35 km), showing anomalies in the supply of locomotives in RCs. [ABSTRACT FROM AUTHOR]

Abstract The efficiency of the power‐to‐hydrogen (P2H) alkaline electrolyzer (AE) is the primary factor constraint on its large‐scale application. Decreasing the specific energy consumption (SEC) of AE is positive to enhancing the efficiency of P2H system. However, the factors influencing the SEC of AE are yet to be fully revealed. In this paper, the influence of power quality and stack temperature on the SEC of AE is explored. Firstly, the models of double star rectifier and PWM current‐type rectifier are established. And the mathematical model on the SEC of rectifiers is proposed. The influence of power quality on the SEC is analyzed by comparing the current and voltage waveforms under four types of rectifiers. Secondly, the model of AE that considers the stack temperature is proposed. Unlike the existing simplified models, the proposed model can assess the SEC considering changes in stack temperature. Finally, the results show that the SEC with the 6‐pulse rectifier is 10.99% and 11.98% higher than that with the double‐star rectifier and PWM current‐type rectifier. The stack temperature is inversely related to the SEC of AE. This study provides a reference for reducing the SEC and enhancing the efficiency of the P2H system.

Abstract Recently, there has been a push to integrate renewable energy system (RES) into grid‐connected load system in enhancing reliability and reducing losses. However, integrating these systems introduces power quality (PQ) issues, especially with non‐linear, critical, and imbalanced loads. Addressing this, a hybrid mantis search‐reptile search algorithm (HMS‐RSA) combined with a unified power quality conditioner (UPQC) to mitigate PQ problems related to current and voltages in RES systems. In other words, the UPQC, enhanced by fractional order proportional integral derivative controller parameters tuned using the proposed HMS‐RSA assists in enhancing the power quality. The approach has been validated by connecting a non‐linear load to the system, which typically creates PQ issues. The proposed method is implemented in MATLAB/Simulink and their performance is analysed in three scenarios, such as sag, swell, and disturbance, and the total harmonic distortion is evaluated to quantify improvements in PQ. Finally, the proposed method is compared with existing approaches, such as ant colony optimization (ACO), artificial bee colony optimization (ABC), and bacterial foraging optimization (BFO). The method also outperforms ACO, ABC, and BFO in terms of convergence speed and effectiveness in mitigating PQ issues.

Abstract To solve the problem of negative‐sequence and reactive power in electrified railway, this paper proposes a comprehensive compensation method based on V/v transformer and electromagnetic single‐phase var compensator (ESVC) for co‐phase power supply. First, based on the principles of static var generator and single‐phase rotary phase shifting transformer, the topology and model of ESVC have been established, and the compensation mechanism has been analysed. Second, the topological structure and mathematical model of co‐phase power comprehensive compensation device (CPCD) are put forward based on the principles of V/v transformer and ESVC, and the operation mode of CPCD in multiple scenarios is designed. Then the strategy of CPCD with double closed loop control is analysed: corresponding compensation mode is selected according to negative‐sequence unbalance degree and expected power factor value. In this strategy, the compensated current output by ESVC is taken as the quantity of external loop control, and the rotation angle of ESVC is taken as the quantity of internal loop control to realize double‐closed loop control of CPCD. Finally, the comprehensive CPCD compensation model is built on the simulation platform and validated the accuracy of the mathematical model and the effectiveness of the control strategy.

Abstract The presented work operated a PIPO Current fed front end converter‐based solid‐state transformer (SST) for maximum power point tracking (MPPT) and voltage boost operation in medium power range PV applications. The proposed system employed the perturb and observe (P&O)‐based MPPT technique and upheld the ZVS and ZCS operations of all primary side switches and secondary side rectifier diodes, respectively. The proposed system introduced a new fundamental extractor titled ‘Pre‐filter double fundamental signal extractor (DFSE) based multi‐layered DFSE (p‐DFSE‐MDFSE)’ and utilised it in the grid controller for synchronisation and harmonics mitigation operation. The primary goal was to achieve a compact size, reduced weight and cheaper magnetic component‐based front‐end converter of SST on the PV array side and a fast, secure and trustworthy mitigation control of current harmonics on the utility grid side. The proposed system was inspected on the OPAL‐RT (RT‐LABv2021.3.2.307) platform for various grid anomalies, and its conduct was found to be well within the IEEE 519 norms.

Abstract During the operation of the ITER machine, hundreds of MW/Var of active and reactive power will be exchanged with the grid. The E‐STATCOM scheme composed of the Modular Multilevel Converter (MMC) and split supercapacitor energy storage has been proposed to improve the power compensation performance of the existing reactive power compensation system in the previous study. However, one of the main technical challenges which is lack of research is to precharge all submodule capacitors and supercapacitors from zero to their nominal voltage values efficiently during a startup process. As the capacitance and operating voltage of supercapacitors are much different from capacitors in each submodule, the startup of E‐STATCOM is a more complicated process. To coordinate the energy exchange between submodule capacitors and supercapacitors, submodule capacitors and the grid, this paper presents an optimized four‐stage AC side startup strategy for the E‐STATCOM. The proposed method minimizes the use of current‐limiting resistors while suppressing the surge current in the zero‐voltage startup process of supercapacitors, in addition to optimizing the energy consumption. The pulse current charging, constant current charging and constant power charging strategies of supercapacitors are adopted in different charging stages, and the detailed coordinated control scheme between submodule capacitors and supercapacitors are described and analyzed. The effectiveness and performance of the proposed method are verified by simulation results and hardware‐in‐the‐loop (HIL) experiments.

The integration of nonconventional energy sources such as solar, wind, and fuel cells into electrical power networks introduces significant challenges in maintaining frequency stability and consistent tie-line power flows. These fluctuations can adversely affect the quality and reliability of power supplied to consumers. This paper addresses this issue by proposing a Proportional–Integral–Derivative (PID) controller optimized through a hybrid Particle Swarm Optimization–Artificial Hummingbird Algorithm (PSO-AHA) approach. The PID controller is tuned using the Integral Time Absolute Error (ITAE) as a fitness function to enhance control performance. The PSO-AHA-PID controller's effectiveness is evaluated in two networks: a two-area thermal tie-line interconnected power system (IPS) and a one-area multi-source power network incorporating thermal, solar, wind, and fuel cell sources. Comparative analyses under various operational conditions, including parameter variations and load changes, demonstrate the superior performance of the PSO-AHA-PID controller over the conventional PSO-PID controller. Statistical results indicate that in the one-area multi-source network, the PSO-AHA-PID controller achieves a 76.6% reduction in overshoot, an 88.9% reduction in undershoot, and a 97.5% reduction in settling time compared to the PSO-PID controller. In the dual-area system, the PSO-AHA-PID controller reduces the overshoot by 75.2%, reduces the undershoot by 85.7%, and improves the fall time by 71.6%. These improvements provide a robust and reliable solution for enhancing the stability of interconnected power systems in the presence of diverse and variable energy sources. [ABSTRACT FROM AUTHOR]

During the operation of the ITER machine, hundreds of MW/Var of active and reactive power will be exchanged with the grid. The E‐STATCOM scheme composed of the Modular Multilevel Converter (MMC) and split supercapacitor energy storage has been proposed to improve the power compensation performance of the existing reactive power compensation system in the previous study. However, one of the main technical challenges which is lack of research is to precharge all submodule capacitors and supercapacitors from zero to their nominal voltage values efficiently during a startup process. As the capacitance and operating voltage of supercapacitors are much different from capacitors in each submodule, the startup of E‐STATCOM is a more complicated process. To coordinate the energy exchange between submodule capacitors and supercapacitors, submodule capacitors and the grid, this paper presents an optimized four‐stage AC side startup strategy for the E‐STATCOM. The proposed method minimizes the use of current‐limiting resistors while suppressing the surge current in the zero‐voltage startup process of supercapacitors, in addition to optimizing the energy consumption. The pulse current charging, constant current charging and constant power charging strategies of supercapacitors are adopted in different charging stages, and the detailed coordinated control scheme between submodule capacitors and supercapacitors are described and analyzed. The effectiveness and performance of the proposed method are verified by simulation results and hardware‐in‐the‐loop (HIL) experiments. [ABSTRACT FROM AUTHOR]

Constructing agricultural microbial gasification plants near livestock farms is essential for technical, economic, and environmental reasons. Utilising substrates from these farms allows for producing electricity, heat, and environmentally friendly manure. However, biogas plants often face technical challenges. This study evaluates the power quality of an agricultural biogas plant on a dairy farm. It was found that the plant was connected via a cable with an insufficient conductor cross-section, leading to significant voltage overshoots exceeding 14.6%, which prevented the activation of the second generator. Both generators could operate after replacing the feed-in cable, but considerable fluctuations in the feed-in voltage persisted. Further measurements indicated the need for changes in the digester design. Specifically, replacing the current two mixers with more lower-powered mixers operating alternately was proposed. Sharing these solutions more broadly can help prevent similar issues in future microbial gas plant constructions and optimise electricity production. [ABSTRACT FROM AUTHOR]

Hybrid Renewable Energy Systems (HRES) have recently been proposed as a way to improve dependability and reduce losses in grid-connected load systems. This research study suggests a novel hybrid optimization technique that regulates UPQC in order to address the Power Quality (PQ) problems in the HRES system. The load system serves as the primary link between the battery energy storage systems (BESS), wind turbine (WT), and solar photovoltaic (PV) components of the HRES system. The major objective of the study is to reduce PQ issues and make up for the load requirement inside the HRES system. The addition of an Optimized Fractional Order Proportional Integral Derivative (O-FOPID) controller improves the efficiency of the UPQC. The Crow-Tunicate Swarm Optimization Algorithm (CT-SOA), an enhanced variant of the traditional Tunicate Swarm Optimization (TSA) and Crow Search Optimization (CSO), is used to optimize the control parameters of the FOPID controller. Utilizing the MATLAB/Simulink platform, the proposed method is put into practice, and the system's performance is assessed for sag, swell, and Total Harmonic Distortion (THD). The THD values for the PI, FOPID, and CSA techniques, respectively, are 5.9038%, 4.9592%, and 3.7027%, under the sag condition. This validates the superiority of the proposed approach over existing approaches. [ABSTRACT FROM AUTHOR]

Aiming at the rich bifurcation and chaotic characteristics in the inverter with proportion integral derivative (PID) controller, the discrete iterative model of such an inverter was derived based on the stroboscopic mapping theory; the nonlinear evolution and the cause of instability in this inverter are analyzed. It was observed that the low‐frequency oscillation following instability was due to the Hopf bifurcation, which will decrease the power supplied quality by the inverter. To address the potential issue of the system instability caused by nonlinear behaviors, an improved exponential time‐delay feedback control scheme was proposed. The controlled object's output current first subtracted its own delay a period of time to form a difference term, which was subsequently fed into an exponential link to make difference with the constant 1. The resulting value was then fed into a proportional link to obtain the control term, which was applied to the PID controlled inverter in a feedback manner. Moreover, the range of the feedback proportional coefficient was solved via the Jury criterion. Finally, the effectiveness of this scheme was verified through the comparative simulations, demonstrating that this scheme can not only increase the stability domain for each parameter by more than 50% in the PID controlled inverter but also stabilize the quasi‐periodic behavior due to the low scale oscillation caused by the Hopf bifurcation at the switching frequency. [ABSTRACT FROM AUTHOR]

Summary: This study addresses a significant research gap in the field of wind energy, focusing on the underutilized potential of synchronous reluctance generators (SynRG) in wind power conversion systems (WPCS). Despite notable advancements in wind energy controls, the capabilities of SynRG within these systems have not been fully explored. In response, we introduce an innovative model‐free control (MFC) approach, termed intelligent proportional (iP), specifically designed and optimized for WPCS equipped with SynRG. This research encompasses the modeling, control, and simulation of SynRG‐based WPCS, aiming to optimize system performance and enhance the quality of grid power supply. The proposed vector control (VC) method utilizes a MFC approach (VC‐iP) to address the limitations inherent in traditional VC methods with proportional‐integral (PI) controllers (VC‐PI). Although widely used for their simplicity, VC‐PI methods often lead to power fluctuations and decreased power and current quality, consequently reducing overall system efficiency. In contrast, VC‐iP markedly enhances power quality and system efficiency, especially in situations involving fluctuating power demand and variable wind speeds. The efficacy of VC‐iP is demonstrated through simulations in two distinct test scenarios that include variations in power demand and random wind speed fluctuations. The results affirm the superiority of VC‐iP in maintaining stable, high‐quality power output from WPCS. This method notably minimizes fluctuations, improves current quality, reduces harmonic distortion and steady‐state error, ensures reliable grid integration, and contributes to a more efficient and sustainable energy system. [ABSTRACT FROM AUTHOR]

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This paper investigates the secondary control problem of shipboard microgrids (SMGs) with a high percentage of new energy sources under general noise. Firstly, a polymorphic SMG model is constructed, which enables the software-defined functionality of the control strategy and allows heterogeneous distributed generators (DGs) in AC SMGs to exchange packets of different types. Secondly, due to the presence of highly dynamic and high-power loads in the SMGs, a containment-based distributed secondary control strategy is proposed to improve the flexibility of the DG voltage regulation. Then, considering the complexity and diversity of disturbances during ship navigation, general noise is introduced instead of white noise to describe various disturbances. Furthermore, based on the random differential equations (RDEs), the NOS stability of the proposed strategy is proved using Lyapunov theory, which proves the effectiveness of the containment-based distributed secondary control strategy under general noise. And, the containment error is obtained to prove that the voltage and frequency of the system converge to the convex hull spanned by the virtual leaders, ensuring the high quality of the power supply. Finally, the validity of the proposed containment-based strategy is verified by an AC SMG model with four DGs in three cases. [ABSTRACT FROM AUTHOR]

Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as "Porpoising". This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems. [ABSTRACT FROM AUTHOR]

In the paper problem of power supply unbalance voltage states with the same Voltage Unbalance Factor (VUF) value for power converters is tackled. This factor is being used to assess the quality of power supply. There are many sources of voltage unbalance phenomenon such as system asymmetries and uneven distribution of demand throughout phases. Based on literature three unbalance states are presented: lines overvoltage, lines undervoltage and phase angle asymmetry. VUF value alone cannot provide information on the type of voltage unbalance state. Moreover, the same VUF percentage can be obtained for different amount of unbalanced phases. In this paper simulation experiments were conducted in order to obtain data of rectifier output voltage during different unbalance states with same VUF. Ripple, mean value and frequency components of said voltage were used in order to detect and categorise power supply voltage unbalance. Such approach does not require complex power quality measuring tools as power supply unbalance can be initially diagnosed using single voltage sensor. [ABSTRACT FROM AUTHOR]

In today's electric power network, fast changes are the norm, and auxiliary services such as automatic generation control (AGC) play a crucial role in maintaining the quality of the power supply. AGC ensures a balance between power generation, demand, and losses to sustain frequency stability and variation in tie‐line power within a set limit, even when the load changes. To accomplish this, it is always beneficial to consider new approaches to controlling the situation. This paper introduces the design of new AGC regulators that consider deviation in DC tie‐line power as an extra control variable for the turbine controller. In this study, three different deregulated power systems (containing two control areas), namely three thermal generations, the combination of one thermal and two hydro generations, and three hydro generations, including two power distribution companies (DISCOs) in each control area. These optimal AGC regulators are implemented in the proposed thermal–thermal–thermal system to carry out the various power contracts. The results have shown that the dynamic outcomes meet the AGC standards. To improve further dynamic results and the proposed systems' stability margins by incorporating redox flow batteries (RFB). In actual operating conditions, the system parameters do not remain constant due to the aging effect, assumptions made in simplifying the mathematical model, etc. Thus, ±50% deviations in the nominal value of system parameters to assess how well the optimal AGC regulators perform in the system under investigation. The suggested realistic AGC system incorporates many parameter fluctuations and works well with the optimal AGC regulators developed for the proposed plans. This study expanded to include a two‐area, thermal‐hydro‐hydro (THH) system under a deregulated framework connected via an asynchronous transmission link with or without a thyristor‐controlled phase shifter (TCPS) and RFB. The genetic algorithm (GA) can solve many issues and has global search, flexibility to varied problem types, intrinsic parallelism, and the ability to handle massive, complex search spaces. Thus, a two‐area deregulated hydro‐hydro‐hydro system with parallel tie‐lines utilizes GA‐PID, GA‐FOPID, and GA‐(1 + PI)‐FOPID controllers. Moreover, a random load disturbance (RLD) is employed in each section of the offered approach to show the resilience and elite performance of the proposed control strategy. To produce various dynamic reactions in the plans, MATLAB software version R2013a is employed. [ABSTRACT FROM AUTHOR]

Faced with rapid development and increasingly complex power grid structure structure of the power grid, it is necessary to accurately locate faults in modern intelligent distribution networks in order to ensure power supply reliability and improve power supply service quality. Aiming at the low positioning accuracy, long time consumption, and limited coverage types in existing positioning algorithms, a new intelligent distribution network fault positioning algorithm is designed by combining two algorithms to complete the monitoring task. Firstly, intelligent distribution network fault location methods under different distributed power grid connection methods are analyzed. Then, considering the distributed power grid connection, a fault location algorithm is designed by combining differential evolution algorithm, Sine chaotic mapping, and whale algorithm. The research results indicated that the designed method had good benchmark performance, with accuracy and recall values as high as 0.98 and 0.97, respectively. During the training process, it only required 175 iterations to reach a stable state. In practical applications, the accuracy of this algorithm in testing three types of faulty power grids was 98.90%, 98.41%, and 98.25%, respectively. The method can effectively improve the fault location accuracy, providing better positioning technology for fault monitoring problems in power systems. [ABSTRACT FROM AUTHOR]

This study explores the feasibility of using impedance relays in electrical distribution systems, a context where their application is not as common as in transmission systems. Given the dynamic nature and complex topology of medium-voltage distribution systems, this work proposes an innovative methodology integrating clustering algorithms and metaheuristic techniques to optimize the placement of impedance relays and enhance system reliability and resilience. Using CYME simulation and the Ant Colony Optimization (ACO) method, case studies were designed to validate the effectiveness of the proposed methodology. The results demonstrated that strategic placement of impedance relays reduces failure frequency and significantly improves the system's response to such failures. This approach allows for a more efficient configuration and quicker response, which is crucial for maintaining continuity and quality of power supply. A detailed analysis of system behavior under various fault scenarios illustrates the robustness and adaptability of the proposed solution, marking a significant advancement in the protection and optimization of electrical distribution systems. [ABSTRACT FROM AUTHOR]

Due to the environment's instability, to reduce inconsistent power supply it is preferable to connect two or more RES in a grid. Harmonics and other power quality issues are introduced into the distribution grid as a result of integrating these Hybrid Renewable Energy Storage (HRES) with nonlinear loads, which is a significant concern for the utility and the consumers, respectively. With the use of the Unified Power Quality Conditioner (UPQC), power quality problems such as voltage interruptions, actual power, and reactive power can be reduced. For optimal operation of the series and shunt compensator of UPQC, the outputs of the converters are controlled by PWM signals, which are optimally tuned by controllers implemented with updated algorithms. An optimized Hybrid metaheuristic-assisted collateral controller comprising of fractional-order proportional integral derivative (FOPID) controller cum (proportional integral (PI) controller for the enhancement of the Three-Phase HRES system-based Distribution Grid integrated with UPQC is developed in this paper. The UPQC reduces the harmonics that non-linear loads feed into the power supply and power quality concerns. The DC link voltage regulation and controller optimization are achieved with the optimal tuning of gain parameters, fractional orders and weight parameters using a hybrid Metaheuristic Algorithm named Amplified Slime Mould with WildeBeest Herd Optimization (ASM-WHO) Algorithm. The proposed system is developed in MATLAB Simulink to compare the effectiveness of compensation for voltage sags and surges and total harmonic distortion (THD) to more traditional approaches, UPQC with PI controller, FOPID-PI controller, FOPID-PI with Chicken Swarm Optimization (CSO), SOA, SMA, and WHO optimization. The settling time for the proposed FOPID-PI controller with ASM –WHO is 147.27 s, which is 1.7%, 13.78%, 1.338% and 13.66% better than the controller without optimization, the proposed collateral controller method with either SOA or CSO or SMA, WHO optimization and PI controller respectively. [ABSTRACT FROM AUTHOR]

Electric power quality is becoming more critical with time because of the increasing use of electronic devices in all areas of society: in industry, in the household, etc. Many kinds of disturbances can be produced in the grid due to external or internal causes, such as, for example, switching operations. Among them, distortion and imbalance are long-term disturbances, which makes them very dangerous for electric equipment. In addition, the identification of the distortion and/or imbalance sources is quite difficult because they are instantaneously scattered by the grid. This paper presents a study of the algorithms published in the technical literature which identify distortion and imbalance sources in electrical installations and compares the results of applying them to a specific installation constituted by linear and non-linear, balanced and unbalanced loads, and a standard module to inject energy to the grid. Only two algorithms have been found in the review carried out and the results provided by both are presented and discussed. Neither of these algorithms is completely reliable, although one of them is more promising. [ABSTRACT FROM AUTHOR]

The non-technical losses caused by abnormal power consumption behavior of power users seriously affect the revenue of power companies and the quality of power supply. To assist electric power companies in improving the efficiency of power consumption audit and regulating the power consumption behavior of users, this paper proposes a power consumption anomaly detection method named High-LowDAAE (Autoencoder model for dual adversarial training of high low-level temporal features). High-LowDAAE adds an extra "discriminator" named AE3 to USAD (UnSupervised Anomaly Detection on Multivariate Time Series), which performs the same function as AE2 in USAD. AE3 performs the same function as AE2 in USAD, i.e., it is trained against AE1 to enhance its ability to reconstruct average data. However, AE3 differs from AE2 because the two "discriminators" correspond to the high-level and low-level time series features output from the shared encoder network. By utilizing different levels of temporal features to reconstruct the data and conducting adversarial training, AE1 can reconstruct the time-series data more efficiently, thus improving the accuracy of detecting abnormal electricity usage. In addition, to enhance the model's feature extraction ability for time-series data, the self-encoder is constructed with a long short-term memory (LSTM) network, and the fully connected layer in the USAD model is no longer used. This modification improves the extraction of temporal features and provides richer hidden features for the adversarial training of the dual "discriminators". Finally, the ablation and comparison experiments are conducted using accurate electricity consumption data from users, and the results show that the proposed method has higher accuracy. [ABSTRACT FROM AUTHOR]

Abstract To improve the power density of series‐connected multi‐pulse rectifiers (MPRs), the harmonic generation principle is studied and the optimization design method for main transformers is proposed. According to the topology of series‐connected 18‐pulse rectifier, its operation waveforms are analysed, and the Fourier series of the waveforms is obtained. Based on the operation waveforms and its Fourier analysis, the principle for harmonic generation of the rectifier is researched, and the phenomenon of autotransformer cannot be applied to series‐connected MPRs is researched. According to the characteristics of the transformer, its vector graphics are analysed. Based on the vector graphics, the optimal structure of the transformer with the highest power density is obtained. The results show that the premise of the normal operation of series‐connected MPRs is the potential difference between the neutral points of different secondary windings, and only isolation/semi‐isolation transformers meet the requirement; the kilovolt‐ampere (kVA) rating of the optimal isolation type transformer is 104.6% pu, and the kVA rating of the optimal semi‐isolation type transformer is about 71.23% pu.

With the development of new energy industries, the demand for the driving range and power quality of electric vehicle (EV) drive systems is growing rapidly. The drive motor is faced with the challenge of continuously improving power density and performance. This paper proposes a multiobjective optimization method for an interior permanent magnet synchronous motor for a traction drive (IPMSMTD). Based on the flat wire winding technology, the multiobjective optimization design of the IPMSMTD is carried out to improve the motor power density and high‐efficiency range, reduce the torque ripple, and suppress the electromagnetic vibration and noise. The structure and size equation of the IPMSMTD are described. The mathematical model considering iron losses is established, and the optimization objectives are determined. Based on the genetic algorithm, a multiobjective optimization mechanism of the magnetic pole structure is established. The operation performance of the motor is analyzed by the finite element simulation and efficiency map. In order to ensure the comprehensive operation index of the IPMSMTD, the vibration noise and modal analysis are carried out, which verifies the rationality of the designed motor and the optimization method. [ABSTRACT FROM AUTHOR]

The power communication system provides powerful technical support for realizing the intelligent operation and information management of the power grid and improving the operation efficiency and power supply quality of the power grid. Quantum key distribution (QKD) is considered one of the most promising technologies for commercialization. QKD uses a single photon to encrypt data to produce a more secure and reliable password. This paper intends to study the hierarchical, centralized control architecture of power dispatching based on quantum essential supply (QKD). The performance indexes of MDI-QKD under symmetric and asymmetric conditions were studied by local optimization. The optimal key formation rate of the algorithm is analyzed. From the perspective of quantum critical utilization, a quantum key utilization scheme for grid backbone dispatching service is proposed. The dynamic adjustment test of multi-node time slot and service key update rate is carried out. Experiments show that the MDI scheme can effectively improve the effectiveness of a multi-node QKD system. Thus, the security of data transmission of the core business of power dispatching data networks can be ensured to the greatest extent. AMDI can effectively reduce the transmission timeout of low-priority data streams because the delay of high-priority data streams reaches the proportion. It can be an excellent solution to the power system and the password requirements. [ABSTRACT FROM AUTHOR]

The article is concerned with the operation of electric power quality meters and analyzers when incorrectly installed on a three-phase electrical network. An analytical study of the meter's errors under the conditions of faulty installation was carried out. All possible types of installation errors are considered according to the proposed classification, as well as possible combinations of a pair of installation faults simultaneously. Classification of installation faults is also proposed. Matrix expressions are derived that allow modeling of any type of installation faults to quantify power and symmetry measurement errors. The proposed method allows to obtain quantitative signs that can identify a specific installation fault. The results of this study can help the development of an algorithm for the automatic detection of installation faults and their correction. The analytical results were confirmed by simulation studies on a three-phase network model in the MATLAB/SIMULINK environment. Experimental results, obtained from a commercial power quality analyzer operated under controlled laboratory conditions, are also reported. [ABSTRACT FROM AUTHOR]

To improve the power density of series‐connected multi‐pulse rectifiers (MPRs), the harmonic generation principle is studied and the optimization design method for main transformers is proposed. According to the topology of series‐connected 18‐pulse rectifier, its operation waveforms are analysed, and the Fourier series of the waveforms is obtained. Based on the operation waveforms and its Fourier analysis, the principle for harmonic generation of the rectifier is researched, and the phenomenon of autotransformer cannot be applied to series‐connected MPRs is researched. According to the characteristics of the transformer, its vector graphics are analysed. Based on the vector graphics, the optimal structure of the transformer with the highest power density is obtained. The results show that the premise of the normal operation of series‐connected MPRs is the potential difference between the neutral points of different secondary windings, and only isolation/semi‐isolation transformers meet the requirement; the kilovolt‐ampere (kVA) rating of the optimal isolation type transformer is 104.6% pu, and the kVA rating of the optimal semi‐isolation type transformer is about 71.23% pu. [ABSTRACT FROM AUTHOR]

Increasing numbers of devices of various types are now connected to power lines. Their nonlinear nature harms the operation of the lines, as the line voltage is distorted from a sine wave, which causes disturbances in the operation of other loads. This study proposes a method of active parallel compensation that can be realised using a power supply. The proposed device is a dual-function system: it supplies the load connected to its DC link, and operates as a parallel active filter. This kind of device, with a relatively low value of the rated output power, could be implemented in electrical systems to provide distributed compensation. The second novel aspect of this work is the use of a tunable inductive filter, which is included at the input of the power electronics controlled current source and forms a main part of the power supply. The use of this tunable inductive filter increases the frequency response of the current source, while at the same time, in the quasi-steady state of power supply operation, the pulse modulation component of the input current source remains at a minimum level. This paper discusses the structure of an electrical system with the proposed power supply and the rules of operation for the system, and presents test results based on both a simulation and a laboratory model of the system. [ABSTRACT FROM AUTHOR]

Investing in renewable energy is of utmost importance, especially in the context of addressing climate change. However, while numerous studies have explored the role of renewable energy in achieving carbon neutrality, there is a noticeable gap in the literature regarding how uncertainties affect the impact of renewable energy on electric power CO2. To bridge this gap, the present study employs recently developed nonparametric techniques, namely multivariate quantile-on-quantile regression (MQQR) and time-varying quantile causality (TVQC), to investigate the relationship between renewable energy and electric power CO2 in the presence of uncertainties. The study utilizes monthly data spanning from January 1988 to May 2023. The bivariate results reveal that renewable energy and low uncertainties contribute to improving ecological quality by reducing electric power CO2. Furthermore, the multivariate quantile-on-quantile regression results highlight the substantial influence of low uncertainties on the impact of renewable energy in lowering electric power CO2. Additionally, the TVQC analysis demonstrates that both renewable energy and uncertainties possess predictive power regarding electric power sector CO2. The study discoveries showcase that the influence of renewable energy on electric power CO2 is subject to external moderation. The suggested policy framework in this study is structured to assist the United States in accomplishing the goals outlined in SDG 7. [ABSTRACT FROM AUTHOR]

Motors that work with high voltage and consume a lot of power, specifically those of 6 kV and 650 kW, generate harmonics of voltage and current harmful to the electro-energy system, causing problems in its correct operation. In this study, the quality of the electrical energy of a motor having those characteristics is analyzed by measuring voltage, current intensity, power factor, active power, reactive power, as well as voltage and current harmonics. Results show that the main problem lies in the fact that the total current harmonic distortion reached a value of 17.1%, which is above the maximum value permissible according to the standard for the motor object of study. However, the total voltage harmonic distortion resulted within the allowable values, reaching a maximum of 3.3%. To mitigate the harmful effects of the total current harmonic distortion, passive and active filters were designed and simulated to improve the motor's operation and solve the problems. For the design and simulation of the filters, MATLAB R2015a software and LabView 2014 software were used. [ABSTRACT FROM AUTHOR]

With the increasing demand for electrical services, wind farm layout optimization has been one of the biggest challenges that we have to deal with. Despite the promising performance of the heuristic algorithm on the route network design problem, the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored. In this paper, the wind farm layout optimization problem is defined. Then, a multiobjective algorithm based on Graph Neural Network (GNN) and Variable Neighborhood Search (VNS) algorithm is proposed. GNN provides the basis representations for the following search algorithm so that the expressiveness and search accuracy of the algorithm can be improved. The multi-objective VNS algorithm is put forward by combining it with the multi-objective optimization algorithm to solve the problem with multiple objectives. The proposed algorithm is applied to the 18-node simulation example to evaluate the feasibility and practicality of the developed optimization strategy. The experiment on the simulation example shows that the proposed algorithm yields a reduction of 6.1% in Point of Common Coupling (PCC) over the current state-of-the-art algorithm, which means that the proposed algorithm designs a layout that improves the quality of the power supply by 6.1% at the same cost. The ablation experiments show that the proposed algorithm improves the power quality by more than 8.6% and 7.8% compared to both the original VNS algorithm and the multi-objective VNS algorithm. [ABSTRACT FROM AUTHOR]

In order to play a positive role of decentralised wind power on-grid for voltage stability improvement and loss reduction of distribution network, a multi-objective two-stage decentralised wind power planning method is proposed in the paper, which takes into account the network loss correction for the extreme cold region. Firstly, an electro-thermal model is introduced to reflect the effect of temperature on conductor resistance and to correct the results of active network loss calculation; secondly, a two-stagemulti-objective two-stage decentralised wind power siting and capacity allocation and reactive voltage optimisation control model is constructed to take account of the network loss correction, and the multi-objective multi-planning model is established in the first stage to consider the whole-life cycle investment cost of WTGs, the system operating cost and the voltage quality of power supply, and the multi-objective planning model is established in the second stage. planning model, and the second stage further develops the reactive voltage control strategy of WTGs on this basis, and obtains the distribution network loss reduction method based on WTG siting and capacity allocation and reactive power control strategy. Finally, the optimal configuration scheme is solved by the manta ray foraging optimisation (MRFO) algorithm, and the loss of each branch line and bus loss of the distribution network before and after the adoption of this loss reduction method is calculated by taking the IEEE33 distribution system as an example, which verifies the practicability and validity of the proposed method, and provides a reference introduction for decision-making for the distributed energy planning of the distribution network. [ABSTRACT FROM AUTHOR]

This article explores the resilient operations of active distribution networks (ADNs) in the face of challenges posed by distributed renewable energy and extreme climate events. The authors propose a cellular architecture for ADNs that enhances resilience and presents a two-stage resilient model and a multi-level distributed control strategy. The model optimally schedules flexibility resources and coordinates network reconfiguration and repair crew to minimize costs and maintain reliable power supplies. The study also discusses the autonomous resilient operations of distribution networks under extreme climates, including pre-disaster prevention and post-disaster recovery stages. Future research will focus on integrating diversified flexibility resources into active distribution networks. [Extracted from the article]

During the construction of smart grids, due to technological limitations, traditional sequential control systems have been unable to meet the needs of grid operation, exposing problems such as single control methods and functions, low operational efficiency, inability to independently complete complex tasks, and poor anti-interference ability, which in turn affect the power supply quality and operational stability of the grid, and fail to truly achieve the reliability, safety, and reliability of smart grids Economic and efficient goals. For this purpose, the author describes an adaptive intelligent control method for an integrated biomass energy heat conversion system consisting of more than one suction biomass gasifier, biomass gas burner, and steam boiler. The system uses PLC as a tool and takes the boiler outlet steam pressure as the control parameter. Based on the changes in the boiler outlet steam pressure, it automatically adjusts the feed and gas production of the gasifier, and subsequently adjusts the air supply of the burner. Ultimately, it achieves the goal of automatically adjusting the boiler heating volume with changes in steam pressure. The integrated heating and adaptive intelligent control system based on biomass gasification has been reliably verified in industrial applications. [ABSTRACT FROM AUTHOR]

The power supply is crucial in the present day due to the negative impacts of poor power quality on the electric grid. In this research, we employed deep learning methods to investigate the power factor, which is a significant indicator of power quality. A multi-step forecast was developed for the power factor in the power supply installation of a hot rolling mill, extending beyond the horizontal line. This was conducted using data obtained from the respective electrical supply system. The forecast was developed via hybrid RNN (recurrent neural networks) incorporating LSTM (long short-term memory) and GRU (gated recurrent unit) layers. This research utilized hybrid recurrent neural network designs with deep learning methods to build several power factor models. These layers have advantages for time series forecasting. After conducting time series forecasting, qualitative indicators of the prediction were identified, including the sMAPE (Symmetric Mean Absolute Percentage Error) and regression coefficient. In this paper, the authors examined the quality of applied models and forecasts utilizing these indicators, both in the short term and long term. [ABSTRACT FROM AUTHOR]