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This paper presents a novel optimization algorithm called hyper-heuristic fitness-distance balance success-history-based adaptive differential evolution (HH-FDB-SHADE). The hyper-heuristic algorithms have two main structures: a hyper-selection framework and a low-level heuristic (LLH) pool. In the proposed algorithm, the FDB method is preferred as a high-level selection framework to evaluate the LLH pool algorithms. In addition, a total of 10 different strategies is derived from five mutation operators and two crossover methods for using them as the LLH pool. Balancing the exploration and exploitation capability of FDB is the main reason for being the selection framework of the proposed algorithm. The success of the HH-FDB-SHADE algorithm was tested on CEC-17 and CEC-20 benchmark test suits for different dimensional search spaces, and the obtained solutions from the HH-FDB-SHADE were compared to 10 different LLH pool algorithms. In addition, the HH-FDB-SHADE algorithm has been applied to optimize the control parameters of PID, PIDF, FOPID, and PIDD2 in the optimal automatic voltage regulator (AVR) design problem to reveal the improved algorithm's performance more clearly and prove its success in solving engineering problems. The results obtained from the AVR system are compared with five other effective meta-heuristic search algorithms such as the fitness-distance balance Lévy Flight distribution, differential evolution, Harris–Hawks optimization, Barnacles mating optimizer, and Moth–Flame optimization algorithms in the literature. The results of the statistical analyses indicate that HH-FDB-SHADE is the best-ranked algorithm for solving CEC-17 and CEC-20 benchmark problems and gives better results compared to the LLH pool algorithms. Besides, the proposed algorithm is more effective and robust than five other meta-heuristic algorithms in solving optimal AVR design problems. [ABSTRACT FROM AUTHOR]

This research focuses on the importance of maintaining generator output voltage stabilization using automatic voltage regulator (AVR), especially in dealing with load impacts and environmental changes. Through the implementation of internet of things (IoT), this system can be controlled and monitored remotely, enabling real-time monitoring without physical presence at the generator location. The main objective of this research is to increase energy efficiency by optimizing generator operation. System development methods include design, prototyping and testing stages. Test results show that the automatic voltage regulator is effective in maintaining a stable output voltage of around 220 V, even though the current varies according to the existing load. The power produced ranges from 23 to 670 W, with a power factor between 0.7 and 1. Despite a slight voltage drop to 217 V, the power factor increases to 0.93. The system uses NodeMCU to send data to Blynk and Google Spreadsheets servers, as well as servo motors and PZEM-004T sensors for control and monitoring. Overall, this research shows that the internet of things-based automatic voltage regulator system is effective in maintaining stability and increasing generator operational efficiency, with the ability to manage voltage, current, power, and power factor efficiently. [ABSTRACT FROM AUTHOR]

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Blackouts in maritime activities can cause propulsion loss and dangerous maritime conditions. Bayesian risk analysis is applied to ship blackout incidents in this study to improve understanding and reduce risks. Using Fault Tree Analysis (FTA), a Bayesian Network (BN) model incorporates fuel quality, lubricating oil quality, sensor error, injector error, and mechanical defects to estimate blackout probability. The model analyses how hazards and their interactions affect this situation using probabilistic inference. Sensitivity analysis identifies variables that affect blackout probabilities and prioritises risk mitigation solutions. Based on prior and posterior probabilities, ‘Automatic Voltage Regulator Failure’ (0.03 prior, 0.17 posterior), ‘Rotor Mechanical Fault’ (0.03 prior, 0.15 posterior), and ‘High Cooling Water Temperature’ (0.03 prior, 0.13 posterior) are the top three blackout causes. Other significant variables include ‘Switchboard Line Failure,’ ‘Faulty Fuel Pump,’ ‘Rotor Open Circuit,’ and ‘Temperature Sensor Failure’ in relative amounts. Bayesian risk analysis can identify and minimise marine blackout concerns, giving decision-makers a comprehensive framework for informed decision-making and proactive risk management. This research emphasises blackout accidents’ importance, improving maritime transportation safety and reliability. [ABSTRACT FROM AUTHOR]

In this work, a hybrid PID controller, combining Zeigler–Nichols (ZN) theory and the dominant pole placement, has been developed for the automatic voltage regulator (AVR) systems. Furthermore, the reduced order models (ROMs) of AVR systems, namely, AVR-1, AVR-2, and AVR-3, have been established using Particle Swarm Optimization (PSO), Big Bang Big Crunch (BBBC), and Pade’s approximation, respectively. Then, the proposed PID controller has been applied to both the original and developed lower order models of AVR to check the efficacy and robustness of the developed hybrid controller. It is shown that the proposed hybrid PID controller provides a very small value of the percentage peak overshoot (%Mp) and settling time (ts). Also, the gain margin (GM) and phase margin (PM) are found to be in the desired range. Finally, the sensitivity analysis has also been performed to check the robustness of the proposed controller. The sensitivity function, complementary sensitivity function, and various performance indices have been evaluated for the proposed controller based on Bode’s Integral (BI), Tyreus–Lyuben (T–L), and Internal Model Control (IMC) approaches. The comparative studies of the results show that the proposed controller has smaller values of performance indices and sensitivity function. [ABSTRACT FROM AUTHOR]

In this paper, a method for determining line drop compensator (LDC) parameters for step voltage regulators and on‐load tap changers is proposed to avoid voltage violations in distribution systems with voltage fluctuations due to photovoltaic (PV) generation and electric vehicle (EV) charging. Distribution system operators need to effectively solve voltage problems caused by the widespread installation of distributed energy resources with the existing voltage regulators to construct an efficient and rational infrastructure. Our focus was on improving the method for determining the LDC parameters for the existing voltage regulators based on LDC control. A mechanism to dynamically change the LDC parameters depending on the situations in the distribution system was developed by using a mixture of experts, one of the machine learning techniques, and real‐time voltage and power flow information from information technology switches. The power flow calculations were performed using a distribution system model constructed based on the topology, loads, and generation characteristics of an actual distribution system in the Hokuriku region. The effectiveness of the proposed method was evaluated in terms of its improved effect on PV and EV hosting capacity, as well as the impact on the frequency of tap operations of voltage regulators. © 2024 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Automatic voltage regulators (AVR) are designed to manipulate a synchronous generator's voltage level automatically. Proportional integral derivative (PID) controllers are typically used in AVR systems to regulate voltage. Although advanced PID tuning methods have been proposed, the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties. This requires continuous fine tuning of the PID parameters. However, manual adjustment of these parameters can compromise the stability and robustness of the AVR system. This study focuses on the online self-tuning of PID controllers called indirect design approach-2 (IDA-2) in AVR systems while preserving robustness. In particular, we indirectly tune the PID controller by shifting the frequency response. The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters. Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously, thereby improving the control performance and robustness. We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins (GMs) and phase margins (PMs) with previously optimized PID parameters during parameter uncertainties. The proposed method is further evaluated in terms of disturbance rejection, measurement noise, and frequency response analysis during parameter uncertainty calculations against existing methods. Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system. In summary, online self-tuning enables automated PID parameter adjustment in an AVR system, while maintaining stability and robustness. [ABSTRACT FROM AUTHOR]

Twenty years ago, legal scholars and regulators alike were convinced that information-forcing regulations heralded a new era in environmental law. Coming off the success of the Toxics Release Inventory (TRI), which seemed to decrease toxic chemical pollution solely by forcing industry to disclose if they released certain chemicals, many called information regulation the third wave of environmental law. New information disclosure policies were enacted and old policies reinvigorated, leading to a plethora of informationbased regulations throughout environmental law. Now, twenty years later, the emergence of big data and artificial intelligence (AI) approaches to environmental analysis have only further increased the belief in the benefits of information-forcing approaches. In this time, the central premise that information regulation works to change behavior and improve environmental outcomes has been largely unquestioned. Despite the widespread enthusiasm, after decades of implementation it is increasingly clear that information regulation largely fails to achieve its environmental goals. This Article makes two main contributions. By drawing on quantitative and qualitative case studies of information-forcing regulations, it first answers the question of whether this approach to environmental regulation is effective. It evaluates the success of information-forcing policies, finding that these policies often fail both to change behavior towards improving environmental conditions and to achieve other stated goals. This Article then analyzes the mechanisms behind information forcing in conjunction with these case studies to propose characteristics that determine the success, or failure, of information regulation. It finds that contrary to popular belief, persuasive and economic mechanisms do not drive environmental behavior change. Instead, informationforcing regulations with legal mechanisms of action show the most promise and efficacy. Moving beyond sweeping promises of efficiency and transparency to understand the specific characteristics that make these programs successful is essential moving forward into an era of big environmental data. [ABSTRACT FROM AUTHOR]

The efficacy of automatic voltage regulator (AVR) systems is contingent on crucial parameters like voltage regulation, response time, stability, and efficiency. Integration of controllers with AVR systems facilitates centralized monitoring and regulation, enhancing voltage output efficiency. This study employs a modified sinh cosh optimizer (m-SCHO) and a modified time-domain metrics-based objective function to fine-tune a fractional-order proportional-integral-derivative with double derivative (FOPIDD2) controller tailored for AVR system control. The m-SCHO is strengthened with an adaptive local search mechanism and an experience-based perturbed learning strategy and enhances solution diversity and navigational efficacy, leading to improved optimization quality. This investigation illustrates the superior performance of the m-SCHO-based FOPIDD2 controller in addressing the multifaceted challenges of AVR control, surpassing other techniques in stability, speed of response, robustness, and efficiency. To validate the method's efficacy, a comparative analysis is conducted using existing controllers with various tuning algorithms. Results indicate that the proposed m-SCHO-based FOPIDD2 controller achieves superior performance metrics, showcasing its capability. The study extends its scope by considering nineteen different controllers reported in the literature for a comprehensive comparison which also exhibits the best stability, further affirming its effectiveness. [ABSTRACT FROM AUTHOR]

Meta-heuristic algorithms (MHAs) have gained popularity in recent years due to their successful results in solving a wide variety of scientific problems. They offer ease of use, fast implementation, and effective convergence toward the optimal solution. Although MHAs have been extensively tested in solving well-known mathematical benchmark problems with one or more dimensions as well as civil and mechanical engineering problems in their initial demonstrations, controller design problems are not typically considered. Furthermore, the literature lacks a standardized optimization process for controller design problems using MHAs. Due to variations in iteration numbers, population sizes, number of trials, objective functions, and insufficient analysis presented in research papers, it becomes challenging to compare and evaluate the controller design performance of MHAs in a successful and fair manner. This work aims to establish a standardized approach for evaluating the performance of MHAs in controller design by proposing a consistent function evaluation metric. To achieve this goal, we present the most comprehensive and comparative study of MHAs' performance in controller design conducted to date. In this paper, we utilize two commonly used objective functions in controller design: Zwe Lee Gaing and Integral Time Absolute Error. Additionally, we employ a total of twenty algorithms, consisting of ten classical algorithms and ten recently popular algorithms. We evaluate the performance of these algorithms on the "automatic voltage regulation" electric power system problem, which serves as a widely used benchmark for meta-heuristically optimized controllers. We consider three different controllers with three (PID), five (FOPID), and seven (FOPIDD) parameters. The performance results of the selected algorithms are thoroughly discussed, considering various analysis techniques such as box plot analysis, convergence curves, and transient response performances, as well as statistical tests like Wilcoxon and Friedman tests. As a result, symbiotic organisms search, teaching–learning based optimization, chaos game optimization, supply–demand based optimization, and jellyfish search algorithms generally emerge as the best-performing algorithms across all optimization processes for the three types of controllers. Researchers interested in conducting further analysis and comparing the improved algorithms can access all the models,parameters, and codes used in this study from the provided link (https://www.mathworks.com/matlabcentral/fileexchange/161336-fractional-order-controller-optimization-for-avr). [ABSTRACT FROM AUTHOR]

The tuning of fractional-order proportional-integral-derivative (FOPID) controllers for automatic voltage regulator (AVR) systems presents a complex challenge, necessitating the solution of real-order integral and differential equations. This study introduces the Dumbo Octopus Algorithm (DOA), a novel metaheuristic inspired by machine learning with animal behaviors, as an innovative approach to address this issue. For the first time, the DOA is invented and employed to optimize FOPID parameters, and its performance is rigorously evaluated against 11 existing metaheuristic algorithms using 23 classical benchmark functions and CEC2019 test sets. The evaluation includes a comprehensive quantitative analysis and qualitative analysis. Statistical significance was assessed using the Friedman's test, highlighting the superior performance of the DOA compared to competing algorithms. To further validate its effectiveness, the DOA was applied to the FOPID parameter tuning of an AVR system, demonstrating exceptional performance in practical engineering applications. The results indicate that the DOA outperforms other algorithms in terms of convergence accuracy, robustness, and practical problem-solving capability. This establishes the DOA as a superior and promising solution for complex optimization problems, offering significant advancements in the tuning of FOPID for AVR systems. [ABSTRACT FROM AUTHOR]

The wind power exchange system (WECS) covered in this paper consists of a voltage source inverter (VSI), a DSSB regulator, and an uncontrolled rectifier. An AC grid or a heavy inductive or resistive load (RL) can be supplied by this system. The DSSB is a recently developed DC-DC regulator consisting of an improved single-ended primary inductance regulator (SEPIC) followed by a buck regulator. It has a peak efficiency of 95–98% and a voltage gain of ( D   (1 + D) / (1 − D) . where D is the regulator transistor's on-to-off switching ratio. The proposed regulator improves the voltage stability and MPPT strategy (optimal or maximum power-point tracking). The combination of the DSSB and the proposed regulator improves the efficiency of the system and increases the power output of the wind turbine by reducing the harmonics of the system voltages and current. This method also reduces the influence of air density as well as wind speed variations on the MPPT strategy. Classical proportional–integral (PI) controllers are used in conjunction with a vector-controlled voltage source inverter, which adheres to the suggested DSSB regulator, to control the PMSM speed and d-q axis currents and to correct for current error. In addition to the vector-controlled voltage source inverter (which follows the recommended DSSB regulator), classical proportional–integral controllers are used to regulate the PMSM speed and d-q axis currents, and to correct current errors. In addition, a model Predictive Controller (PPC) is used with the pitch angle control (PAC) of WECS. This is done to show how well the proposed WECS (WECS with DSSB regulator) enhances voltage stability. A software-based simulation (MATLAB/Simulink) evaluates the results for ideal and unoptimized parameters of the WT and WECS under a variety of conditions. The results of the simulation show an increase in MPPT precision and output power performance. [ABSTRACT FROM AUTHOR]

Agricultural mechanization although reduces the food demand and supply gap through improved and smart technologies, it also risks the lower‐limb disability of workers due to accidents that restrict them to participate in agricultural operations due to the unavailability of appropriate assistive technologies. The lack of use of ergonomics further minimizes the inclusion of female workers in farming operations. Therefore, this study is focused on the development of a sensor‐based wireless hand control system for tractor clutch and brake operation to assist lower‐limb‐disabled agricultural workers and abled females in tractor operation. Actuation force and speed of conventional clutch and brake pedals were evaluated using an integrated foot transducer and used as a reference for the design of the system (clutch: 92–310 N, 36–43 mm/s; brake: 106–329 N, 57–63 mm/s). The hand control system consists of a transmitter and a receiver node incorporating a single‐board computer, matrix keypad, voltage regulators, relay switches, wireless communication through radio frequency modules, and electric linear actuators connected with the pedals through L‐shaped clips, nuts, bolts, and chains. The response time of the developed system was determined as 100 ms and the stopping distance of the tractor using the hand control system ranged from 44.0 to 190.7 cm at a forward speed of 2.1–7.9 km/h. The ergonomic evaluation measured using the K4b2 oxygen analyzer identified the foot control usage in tractors as high energy consuming (9.7–15.1 kJ/min) compared with the hand control usage (7.3–14.1 kJ/min). Electromyography‐root mean square (EMG‐RMS) of upper limb muscle, extension digitorum was found to be highest (14.76–45.29 µV) and was significantly affected by forward speed, gender, subjects, and type of control (p < 0.01) whereas, EMG‐RMS of other selected upper limb muscles, middle deltoid, flexor carpi radialis, and brachioradialis was not significantly affected by the type of control (foot or hand). Muscle workload of all the muscles was observed within the recommended limit (<30%) during the tractor operation with the developed hand control system. The developed hand control system provides options to bypass foot‐based actuation requirement for lower limb disabled as well as female workers. The novel design requires minimal workplace and operating forces and is inclusive of operator ergonomics. [ABSTRACT FROM AUTHOR]

In this paper, a new hybrid optimization algorithm known as particle swarm optimization and grey wolf optimizer (PSO-GWO) based proportional integral derivative (PID) controller is suggested for automatic voltage regulator (AVR) system terminal tracking problem. The main objective of the suggested approach is to reduce crucial performance factors such as rise time, settling time, peak overshoot and peak time of the voltage of the power system in order to improve the AVR system's transient response. This analysis was compared to results obtained from existing heuristic algorithmbased approaches found in the literature, proving the improved PID controller's enhanced performance obtained through the suggested approach. Furthermore, the performance of the tuned controller with respect to disturbance rejection and its robustness to parametric uncertainties were evaluated separately and compared with existing control approaches. According to the obtained comparison results and from all simulations, using MATLAB-Simulink tool, it has been noted that the PID controller optimized using PSO-GWO algorithm has superior control performance compared to PID controllers tuned by ABC, DE, BBO and PSO algorithms. The main conclusion of the presented study highlights that the recommended strategy can be effectively implemented to improve the performance of the AVR system. [ABSTRACT FROM AUTHOR]

Improving photovoltaic systems to better withstand variations in temperature and irradiance, lessen steady-state ripples, maintain high efficiency, require less tracking time, and have minimal complexity is becoming increasingly important. The PV array's overall power output is negatively impacted by partial shading because the shaded cells produce less power and consume less power overall, which lowers efficiency and creates localized hotspots. Although bypass diodes may be used to counteract these impacts by rerouting current around cells that are shaded, they can result in several peaks, which complicates maximum power point tracking (MPPT). To manage several peaks and optimize power output, metaheuristic algorithms are compulsory. A recently developed game-based optimization methodology known as Golf Optimization Approach (GOA) is used in this study to find a way to MPPT in a grid-connected photovoltaic (PV) system under partial shading conditions (PSCs). Additionally, the same suggested approach is applied to get optimal parameters for the inverter with the goal of optimizing its voltage and current regulators. It aims to evaluate a plan to lower the output voltage and current's total harmonic distortion and DC voltage error. The proposed technique is contrasted to other tracking approaches such as the traditional Perturb & Observe (P&O), Gray Wolf Optimization (GWO), and Sea-gull Optimization Approach (SOA). Simulation is performed in MATLAB R2022b/SIMULINK environment. The obtained outcomes demonstrate the ability of the suggested technique to enhance the utility grid's power quality and improve the tracking system under various partial shading effects and temperature alterations. The proposed technique achieves a tracking efficiency of 99.8 %, surpassing the effectiveness of both of the previous methods which are at 97.2 % and 96.7 %. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching–Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications. [ABSTRACT FROM AUTHOR]

The growing number of distributed renewable energy sources and dynamic constant-power loads (e.g. electric vehicle charging stations) pose new challenges for network operators. These changes result in alterations to network load profiles and load flows, leading to greater voltage volatility. One effective solution to these problems can be the use of automatic voltage regulators (AVRs), which stabilize and symmetrize voltage output, whether at distribution transformers (DTs) or elsewhere in the distribution network. The device developed by the authors consists of two bidirectional power converters and three single-phase transformers connected in series to the low-voltage grid as a stabilizer. The proposed control system provides accurate and fast regulation of the AVR output voltage (within the range of ±10% of the nominal grid voltage), with each phase being independently adjusted, regardless of the type of power load. The article includes test results demonstrating selected functionalities of the developed AVR. The physical model of the device discussed in the article is a research component of the LINTE2 laboratory of the Gdańsk University of Technology. [ABSTRACT FROM AUTHOR]

The LM2990-integrated circuit family was among the first low-dropout voltage regulators to use a coupling diode to reduce a quiescent current. In certain conditions, the coupling diode, connected between the output terminal and the driver transistor collector contact, activates to supply the serial power transistor base current from the load. Nonetheless, an indirect characterization of the serial NPN transistor was affected, making it difficult to estimate its forward emitted current gain and a base current as a function of the absorbed total ionizing dose. The original SPICE simulation model had some limitations with generating the faithful simulation of radiation effects in samples supplied with a non-ideal voltage source. Therefore, a novel four-step computer simulation method was developed to specify bias and load conditions when the coupling diode reaction would not negatively affect the characterization of the serial power transistor. The previously reported method for estimating the serial transistor base current could be successfully used for dropout voltages that slightly exceed three equivalent diode voltage drops (that is, 2.4V) at the base-emitter junctions of the output amplifier transistors. [ABSTRACT FROM AUTHOR]

This article proposes the use of a three-phase induction generator (IG), connected through a single-phase connection (Fukami configuration), to be used as a rotating exciter for synchronous generators. This proposal aims at presenting an alternative to replace the permanent magnet generators (PMGs) used in the rotating exciters for synchronous generators (SGs). In order to obtain the results, a six-pole IG and a four-pole SG were used, a DC motor (DCM) was employed as the primary machine, and the speed control for the aforementioned primary machine is presented and described in this work. To carry out performance tests of the rotating exciter with the IG and the terminal voltage control of the SG, a voltage controller was proposed. The performance of the voltage regulator was tested when the SG supplied a dynamic load, as established by the NEMA MG-1 standard. This article validates its proposal by comparing the results obtained through computational simulation and experimental testing of the SG terminal voltage waveform when faced with a sudden load change. [ABSTRACT FROM AUTHOR]

The primary objective of a power system is to provide safe and reliable electrical energy to consumers. This objective is achieved by maintaining the stability of the power system, a multifaceted concept that can be divided into three distinct classes. The focus of this study is on one of these classes, voltage stability. A critical component in maintaining voltage stability is the automatic voltage regulator (AVR) system of synchronous generators. In this paper, a novel control method, the sigmoid-based fractional-order PID (SFOPID), is introduced with the aim of improving the dynamic response and the robustness of the AVR system. The dandelion optimizer (DO), a successful optimization algorithm, is used to optimize the parameters of the proposed SFOPID control strategy. The optimization process for the DO-SFOPID control strategy includes a variety of objective functions, including error-based metrics such as integral of absolute error, integral of squared error, integral of time absolute error, and integral of time squared error, in addition to the user-defined Zwee Lee Gaing's metric. The effectiveness of the DO-SFOPID control technique on the AVR system has been rigorously investigated through a series of tests and analyses, including aspects such as time domain, robustness, frequency domain, and evaluation of nonlinearity effects. The simulation results are compared between the proposed DO-SFOPID control technique and the fractional-order PID (FOPID) and sigmoid-based PID (SPID) control techniques, both of which have been tuned using different metaheuristic algorithms that have gained significant recognition in recent years. As a result of these comparative analyses, the superiority of the DO-SFOPID control technique is confirmed as it shows an improved performance with respect to the other control techniques. Furthermore, the performance of the proposed DO-SFOPID control technique is validated within an experimental setup for the AVR system. The simulation results show that the proposed DO-SFOPID control technique is highly successful in terms of stability and robustness. In summary, this study provides comprehensive evidence supporting the effectiveness and superiority of the DO-SFOPID control technique on the AVR system through both simulation and experimental results. [ABSTRACT FROM AUTHOR]

The high penetration of distributed photovoltaics (PV) in distribution networks (DNs) results in voltage violations, imbalances, and flickers, leading to significant disruptions in DN stability. To address this issue, this paper proposes a multi-timescale voltage regulation approach that involves the coordinated control of a step voltage regulator (SVR), switched capacitor (SC), battery energy storage system (BESS), and electric vehicle (EV) across different timescales. During the day-ahead stage, the proposed method utilizes artificial hummingbird algorithm optimization-based least squares support vector machine (AHA-LSSVM) forecasting to predict the PV output, enabling the formulation of a day-ahead schedule for SVR and SC adjustments to maintain the voltage and voltage unbalance factor (VUF) within the limits. In the intra-day stage, a novel floating voltage threshold band (FVTB) control strategy is introduced to refine the day-ahead schedule, enhancing the voltage quality while reducing the erratic operation of SVR and SC under dead band control. For real-time operation, the African vulture optimization algorithm (AVOA) is employed to optimize the BESS output for precise voltage regulation. Additionally, a novel smoothing fluctuation threshold band (SFTB) control strategy and an initiate charging and discharging strategy (ICD) for the BESS are proposed to effectively smooth voltage fluctuations and expand the BESS capacity. To enhance user-side participation and optimize the BESS capacity curtailment, some BESSs are replaced by EVs for voltage regulation. Finally, a simulation conducted on a modified IEEE 33 system validates the efficacy of the proposed voltage regulation strategy. [ABSTRACT FROM AUTHOR]

As microprocessor currents exceed 500 A and slew rate reaches 1000 A/µs, increasing the decoupling capacitance on the motherboard to ensure normal operation of the microprocessor is inevitable because of the limited response capability of the voltage regulator. However, the area of the motherboard used for capacitors is usually narrow. To reduce the required capacitance, a novel buck converter with an auxiliary circuit for charge compensation using switched capacitors is proposed. The auxiliary circuit is not activated during the steady state. When the load current changes rapidly, the switched capacitors can quickly absorb or release charge to suppress voltage fluctuations. A 12 V–0.9 V buck converter has been built and tested under a 480 A load current step and a 960 A/µs current slew rate. The proposed scheme with 9.964 mF capacitance has an overshoot of 115 mV and an undershoot of 89 mV. Compared with the conventional PID scheme, the proposed scheme can save 58.4% of the capacitance for the same voltage fluctuations or suppress 39.5% of overshoot and 37.3% of undershoot with the same capacitance. [ABSTRACT FROM AUTHOR]

Hardware masking is used to protect against side-channel attacks by splitting sensitive information into different parts, called hardware masking shares. Ideally, a side-channel attack would only work if all these parts were completely independent. But in real-world VLSI implementations, things are not perfect. Information from a hardware masking share can leak to another, making it possible for side-channel attacks to succeed without needing data from every hardware masking share. The theoretically supposed independence of these shares often does not hold up in practice. The effectiveness of hardware masking is reduced because of the parasitic impedance that stems from power delivery networks or the internal structure of the integrated circuit. When the coupling effect and noise spread among the hardware masking shares powered by the same power delivery network, side-channel attacks can be carried out with fewer measurements. To address this, we propose a new method of distributing on-chip voltage regulators to improve hardware masking security. The benefits of distributed on-chip voltage regulators are evident. Placing the regulators close to the load minimizes power loss due to resistive losses in the power delivery network. Localized regulation allows for more efficient adjustments to the varying power demands of different chip sections, improving overall power efficiency. Additionally, distributed regulators can quickly respond to power demand changes, maintaining stable voltage levels for high-performance circuits, leading to improved control over noise. We introduce a new DLDO voltage regulator that uses random clocking and randomizing limit cycle oscillations to enhance security. Our simulations show that with these distributed DLDO regulators, the t-test value can be as low as 2.019, and typically, a circuit with a t-test value below 4.5 is considered secure. [ABSTRACT FROM AUTHOR]

In recent years, there has been a growing emphasis on diversifying and decarbonizing the energy matrix, paving the way for the emergence of new energy technologies as promising solutions for sustainable development. Among the emerging energies that have already achieved commercial maturity and deployment in Brazil are photovoltaic panels. This work proposes to analyze the potential impacts of on-load TAP-changers (OLTC) in transformers in industries located in distribution networks with a significant presence of photovoltaic distributed generation (PVDG). Thus, three industries are strategically allocated at different points of the IEEE 8500-node system using the OpenDSS program. The impacts are evaluated in several PVDG penetration scenarios in the network. The results show substantial fluctuations in the flow of energy generated by PVDG within the low-voltage network. This, in turn, induces frequent voltage changes in the medium-voltage network, leading to an increased operational frequency of OLTCs and a subsequent reduction in their lifetime. Moreover, this paper proposes alternative configurations for voltage regulator devices to enhance their lifetime in the face of intermittent voltage variations. The results suggest that adjusting the equipment's actuation delay and bandwidth of the OLTCs can decrease the OLTC switching frequency in a range of 65–85%, resulting in the preservation of the equipment's lifetime. [ABSTRACT FROM AUTHOR]

This paper proposes a new approach for evaluating distribution voltage regulators using quasi-static hardware-in-the-loop (HIL) simulation. Distribution voltage regulators are used to control the voltage using tap change transformers and are equipped with static control algorithms in order to accomplish different configurations of the distribution electric grid with typical load profiles. The growing penetration of renewable energy in electrical distribution systems is a great challenge for this equipment, and it becomes paramount that its measurement and control algorithms adapt to this new reality. Hardware-in-the-loop testing (HIL) techniques could be used for assessing the performance of the voltage regulator equipment. Most applications of HIL are concerned with accessing the dynamics of electrical system including not only grid modeling, but also the real equipment involved and should be used to test the efficiency of voltage regulation. However, a more simplified approach concerning the HIL tool could be applied to testing distribution voltage regulators in the laboratory prior to installation, evaluating the performance of algorithms and equipment by conducting quasi-static simulations. This paper presents this approach, joining NI LABVIEW laboratory controller software (National Instruments, LabVIEW. Available at https://www.ni.com/pt-br/support/downloads/software-products/download.labview.html#460283, 2023) and an open-source program OpenDSS (The Electric Power Institute, OpenDSS. Available at em https://opendds.org/, 2023). The effectiveness of quasi-static HIL platforms for assessing several aspects of static voltage tap regulators before installing them in the electric grid is demonstrated. The major advantage is the smaller computation complexity of a static simulations compared to dynamic simulators, allowing simpler hardware requirements. In this sense, a large number of medium to long term simulations could be easily performed providing a broader view of the behavior of the electric system including voltage regulators. [ABSTRACT FROM AUTHOR]

For regulating the Synchronous Generator (SG) output voltage, the Automatic Voltage Regulator (AVR) system is a significant device. This work propounds a survey on Optimization Algorithms (OAs) utilized for tuning the controller parameters on the AVR system. A device wielded for adjusting the SG's Terminal Voltage (TV) is named AVR. A Controller is utilized for improving stability and getting a superior response by mitigating maximum Over Shoot (OS), reducing Rise Time (RT), reducing Settling Time (ST), and enhancing Steady State Error (SSE) since output voltage has a slower response and instability. The controllers utilized here are Proportional-Integral-Derivative (PID), Intelligent Controller (IC), along with Fraction Order PID (FOPID). Owing to the occurrence of time delays, nonlinear loads, variable operating points, and others, OAs are wielded for tuning the controller. (a) Particle Swarm Optimization (PSO), (b) Genetic Algorithm (GA), (c) Gray Wolf Optimizer (GWO), (d) Harmony Search Algorithm (HSA), (e) Artificial Bee Colony (ABC), (f) Teaching Learned Based Optimization (TLBO), et cetera are the various sorts of OA. For enhancing the TV response along with stability, various OAs were tried by researchers. [ABSTRACT FROM AUTHOR]

An improved DC-Link voltage controller (IPOVR), which is built upon the perturb & observe-based voltage regulator (POVR), is proposed in this paper. The aim is to achieve the best balance between tracking time and steady-state oscillation while maintaining good tracking accuracy. This is achieved by implementing a dynamic step-size (∆D) changing strategy and operating region detection technique. Quick tracking time is produced with large initial ∆D, and low steady-state oscillation is obtained through continuous ∆D reduction. Additionally, through the operating region determination technique, the IPOVR operates over a much wider range, typically with lower PV current (IPV), which helps in reducing the losses of the system. It is found that the IPOVR has the lowest steady-state ripple and the highest tracking accuracy, which are averaged at 0.44% and 99.98%, respectively. In terms of tracking time, the IPOVR is averaged at 0.15 s, which is only 0.07 s slower compared to the POVR with high ∆D but is 0.19 s faster than the POVR with low ∆D. Furthermore, the IPOVR recorded higher efficiencies under all tested conditions compared to the POVR. The IPOVR is also demonstrated to be working decently when being connected to a multilevel inverter to generate AC power. [ABSTRACT FROM AUTHOR]

This paper introduces a new direct step‐up ac‐ac converter designed based on the SEPIC. It provides a higher step‐up conversion ratio than other counterparts with valuable features like high efficiency, reasonable input and output total harmonic distortions (THD), continuous input current waveform, common ground, few components, and single‐stage conversion without snubber and LC filters. Unlike most counterparts, the duty cycle can be varied between zero and one in boost operation and is not limited to any value below one. The voltage stress on one switch is reduced by increasing the winding coefficient of the utilized coupled inductor, and current stress on another is independent of this coefficient. It reduces the switches' losses and improves the converter efficiency. Thanks to the above attributes, the proposed converter is suitable for inductive power transfer from low‐voltage ac sources, operating as an ac voltage regulator for sensitive ac loads, and any applications that require a boost converter with few components. This article shows the converter's operation principle and evaluates its performance through experiments on a 225 W prototype. Accordingly, the maximum obtained efficiency is 95.4%. The input and output current THDs for the nominal inductive load equal 4.5 and 2.8%, respectively. Results confirm the claims. [ABSTRACT FROM AUTHOR]

Voltage instability, power imbalance, and unreliability are caused mainly by equipment failure in the distribution system, so it is important to accurately and quickly assess the status of distribution network equipment. However, it is challenging to detect equipment failures, the traditional XGBoost algorithm is unsuitable because some evaluation indices are incompetent to quantify. To address these issues, we propose a fast evaluation method for the state of electrical distribution equipment based on fuzzy decision-making. Firstly, key indices are selected from the multi-source equipment information. Secondly, this paper constructs the mapping between key indices and equipment status scores by combining the fuzzy iterative method and the XGBoost algorithm. Finally, the proposed assessment model is confirmed by using the distribution transformers as an example. The result shows that the proposed multi-source information assessment method can quickly and accurately determine the operation status of electrical distribution equipment, and the proposed method has better accuracy than the traditional method. [ABSTRACT FROM AUTHOR]

Distributed generators (DGs) have the potential to act as alternative power sources for balancing and restoring service in distribution system breakdowns. Nevertheless, DGs variety of characteristics and uncertain behavior pose difficulties in optimizing their operation while restoring the system. In this paper, a hierarchical structure is introduced to manage the unbalanced and islanded distribution networks with the optimal coordination strategy of DGs. The proposed approach encompasses multiple control tiers that manage DGs coordination process into three specific levels, each accountable for distinct functions involving voltage and frequency regulation, power distribution within individual islands, and overseeing power exchange between these units for minimizing imbalance and maximizing the load restoration. This research delivers a comprehensive solution for optimally coordinating DGs in unbalanced and isolated networks during restoration, thus elevating system reliability and resilience. The proposed model for distributed control restoration is validated using a modified IEEE 123-bus test setup. [ABSTRACT FROM AUTHOR]

Due to their numerous advantages, wind turbines with changeable speed power production systems are increasingly being used. This study proposes the architecture and specifications of an induction turbine-generating wind system, as well as a PI controller-based DC voltage link regulator and optimal torque control system. The suggested control technique as stated in this paper allows the system to function in grid-linked mode as well as the islanded mode and also in parallel with other power generation units, loads, FACTS devices, etc. This paper involves the analysis of different test cases in grid-connected mode as well as an islanded mode with a PV generation unit, passive loads, induction motor loads, and other wind energy generation systems. The paper also includes an analysis of the response of the system with the switching on and off of the other units. MATLAB 2013a thereby validates the system findings and analysis. [ABSTRACT FROM AUTHOR]

Abstract Superconducting magnetic energy storage‐battery hybrid energy storage system (HESS) has a broad application prospect in balancing direct current (DC) power grid voltage due to its fast dynamic response ability under low‐frequency/high‐frequency disturbances. Model‐predictive‐control (MPC) with characteristics such as high sampling rate and wide applicability could be applied to HESS. However, considering that the relevant circuit parameters would change with ambient temperature, interference and ageing, the effect of MPC may deteriorate inevitably. This article proposes an improved MPC strategy for SMES‐Battery HESS, taking moth‐flame‐optimisation (MFO) algorithm to calculate the circuit parameters in real time. The actual parameters are updated by MFO and then sent to model predictive controller to minimise the model mismatches. The advantages of high accuracy and fast convergence speed is verified by comparison with grey wolf optimisation and particle swarm optimisation. The simulation shows that by taking the proposed scheme, DC bus voltage are more stable and the superconducting magnetic energy storage can maintain more than 95% capacity utilisation and avoid over‐discharge even if the model parameters are inconsistent with the actual ones under circumstances of alternating current grid fault and fluctuation of new energy output.

The increasing adoption of battery storage units alongside private PV systems may prove to be a new challenge for distribution grid operators. This study explored the potential impact of marketing aggregated battery discharge power as a Fast Frequency Reserve (FFR) and its effect on the distribution grid stability. We investigated the efficacy of Line Voltage Regulators (LVRs) in mitigating voltage surges caused by simultaneous battery activation. For this purpose, a simulation was developed via Matlab (Version R2023a) to simulate the voltage at the nodes of an arbitrary distribution grid, using the feed-in and consumed power of the customers as the input. We applied the model to a distribution grid section in Sundsvall (Sweden). The results confirmed that LVRs can amplify voltage surges when their adjustments are not synchronized with the FFR activation. This study underscored the need for proactive measures to address the voltage maintenance challenges arising from the integration of battery storage units and renewable energy sources. [ABSTRACT FROM AUTHOR]

In modern power systems, conventional energy production units are being replaced by clean and environmentally friendly renewable energy resources (RESs). Integrating RESs into power systems presents numerous challenges, notably the need for enhanced grid stability and reliability. RES-dominated power systems fail to meet sufficient demand due to insufficient inertia responses. To address this issue, various virtual inertia emulation techniques are proposed to bolster power system stability amidst the increased integration of renewable energy sources into the grid. This review article explores state-of-the-art virtual inertia support strategies tailored to accommodate the increased penetration of RESs. Beginning with an overview of this study, it explores the existing virtual inertia techniques and investigates the various methodologies, including control algorithms, parameters, configurations, key contributions, sources, controllers, and simulation platforms. The promising virtual inertia control strategies are categorised based on the techniques used in their control algorithms and their applications. Furthermore, this review explains evolving research trends and identifies promising avenues for future investigations. Emphasis is placed on addressing key challenges such as dynamic response characteristics, scalability, and interoperability with conventional grid assets. The initial database search reveals 1529 publications. Finally, 106 articles were selected for this study, adding 6 articles manually for the review analysis. By synthesising current knowledge and outlining prospective research directions, this review aims to facilitate the current state of research paths concerning virtual inertia control techniques, along with the categorisation and analysis of these approaches, and showcases a comprehensive understanding of the research domain, which is essential for the sustainable integration of renewable energy into modern power systems via power electronic interface. [ABSTRACT FROM AUTHOR]

Distributed Energies Resources (DERs) can be controlled for supporting the voltage regulation at nodes of an Active Distribution Network (ADN) where they are connected. However, since the ADN is a Multi-Input Multi-Output (MIMO) system with coupled dynamics, the controller of a DER mutually interacts with all other controllers through the distribution lines. These interactions lead to operating conflicts which may drive the ADN to work close to its voltage stability boundaries. To achieve a stable voltage regulation without new investment in the existing ADNs, the present paper proposes a straightforward decentralized design of the multi-loop controllers based on the property of integral controllability. The main feature of the method is that the design problem can be expressed by a single parameter designed both for reducing the effects of the undesired coupling and for increasing the degree of robust stability in the presence of parameter uncertainty in the matrix plant. Simulation studies are developed to illustrate the design result and the performance achieved under different operating conditions. The performance is also compared with the one obtained by another method in terms of the integral absolute error. [ABSTRACT FROM AUTHOR]

Summary: Fast battery charging units act as non‐linear loads, which induce a more harmonic effect in the utility grid. Hence, maintaining the stable voltage, current ripple, and total harmonic distortions within the permissible IEEE std level during the charging time of grid to electric vehicle (G2V) has become an important task for researchers in the future. In order to mitigate power fluctuations during every charging cycle, it will enhance the battery life cycle in electric vehicles (EVs). Three phase–three level–three switch Vienna rectifier with fuzzy logic controller tuned PID controller is used here for AC/DC conversion with minimum switching loss. A fuzzy intelligent control strategy has been employed with the DC link voltage regulator in order to sustain the DC link voltage as constant and progress the voltage/current profile by injecting active power at the point of common coupling. Unit vector template (UVT)‐based control strategy is employed here to identify the fundamental components from the load side and also estimate the reference phase current. This scheme enhances the performance and reduces the mathematical system complexity to diminish the harmonics in the distribution grid. The adaptability and feasibility of this proposed control method have been verified by the MATLAB simulation tool. To validate the response of the Vienna Rectifier with UVT controller are simulated with different unbalanced load conditions and also verified with 30 kW laboratory prototype experimental results using dsPIC30F4011 controller and the switch is IRFP260 with power diode RHRG30120. [ABSTRACT FROM AUTHOR]