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The stable and efficient regulation of voltage and frequency is a critical issue associated with the functioning of modern power system network having renewable integration. This manuscript focuses on the concurrent regulation of voltage and frequency in a power network comprising multiple generating sources. Herein, along with conventional thermal and diesel plants, renewable generations from different sources have been considered such as wind and solar photovoltaic (PV) resources. Further, in a fresh attempt, the authors have modeled wind and solar PV generation using two different stochastic modeling methods concerning combined voltage and frequency loops in the regulated power system model. Furthermore, the novel Leader Harris Hawks Optimized Model Predictive Controller (MPC‐LHHO) has been applied to concurrently minimize the voltage and frequency deviations in the given power network. To address the intermittent nature of load and renewable generations, various auxiliary frequency controllers, such as the unified power flow controller (UPFC) and electric vehicle (EV) integration with the grid, have been implemented. The robustness of the proposed control method has been successfully validated through diverse scenarios of random loadings. [ABSTRACT FROM AUTHOR]

Off-grid wind energy systems play a pivotal role in providing clean and sustainable power to remote areas. However, the intermittent nature of wind and the absence of grid connectivity pose significant challenges to maintaining consistent power quality. The wind energy conversion system plays a central role in tapping renewable energy from wind sources. Operational parameters such as rotor and stator currents, output voltages of rectifiers and converters, and grid phase voltage variations are crucial for stable power generation and grid integration. Additionally, optimizing power conversion output through voltage gain analysis in boost converters is essential. Moreover, ensuring electricity quality via total harmonic distortion reduction in inverters is vital for grid compatibility. Goal. Enhancing the power quality of grid-integrated wind energy conversion systems. Methods. The proposed topology is implemented in MATLAB/Simulink with optimized control strategies for enhancing power quality in off-grid wind energy systems. Results. Control strategies with a grid-connected wind energy conversion system yields substantial improvements in power quality. This includes effectively mitigating voltage fluctuations and harmonics, resulting in smoother operation and reduced disturbances on the grid. Practical value. The proposed topology has proven to be extremely useful for off grid-integrated wind system. References 18, table 1, figures 11. [ABSTRACT FROM AUTHOR]

Highlights This study reports the test results of a total of 16 low‐voltage (415 V) 15 and 30 kVA alternators manufactured using optimized polyester resin nanocomposites. These tests consist of the open‐circuit characteristics (OCC), short‐circuit characteristics (SCC), voltage regulation, and temperature rise tests. The test results obtained are reported in terms of efficiency, voltage regulation, OCC and SCC curves, and temperature rise in stator and rotor windings. The results show that the temperature rise in the windings reduced significantly and the efficiency improved marginally using polyester resin nanocomposite insulation. Finally, the calculations show that the reduction in temperature rise can double the life of the alternator. Notably, the manufactured alternators passed all the performance tests as per the test standards, without adversely affecting its performance. For the insulation design of any low‐voltage rotating machine utilizing polyester resin as its base insulation, a similar approach can thus be adopted. Fabrication of alternator prototype using polyester nanocomposite insulation. Alternator prototype fabrication using standard industry manufacturing process. Reduction in temperature rise in stator and rotor windings by 10 °C. Enhancement in alternator efficiency by 3%–4%. Polyester nanocomposite insulation doubles the service life of alternator. [ABSTRACT FROM AUTHOR]

The paper conducts a comprehensive analysis of the impact of very large-scale photovoltaic generation systems on various aspects of power systems, including voltage profile, frequency, active power, and reactive power. It specifically investigates IEEE 9-bus, 39-bus, and 118-bus test systems, emphasizing the influence of different levels of photovoltaic penetration. Additionally, it explores the effectiveness of battery energy storage systems in enhancing system stability and transient response. The transition to PV generation alters system stability characteristics, impacting frequency response and requiring careful management of PV plant locations and interactions with synchronous generators to maintain system reliability. This study highlights how high penetration of photovoltaic systems can improve steady-state voltage levels but may lead to greater voltage dips in contingency scenarios. It also explores how battery energy storage system integration supports system stability, showing that a balance between battery energy storage system capacity and synchronous generation is essential to avoid instability. In scenarios integrating photovoltaic systems into the grid, voltage levels remained stable at 1 per unit and frequency was tightly controlled between 49.985 Hz and 50.015 Hz. The inclusion of battery energy storage systems further enhanced stability, with 25% and 50% battery energy storage system levels maintaining strong voltage and frequency due to robust grid support and sufficient synchronous generation. At 75% battery energy storage system, minor instabilities arose as asynchronous generation increased, while 100% battery energy storage system led to significant instability and oscillations due to minimal synchronous generation. These findings underline the importance of synchronous generation for grid reliability as battery energy storage system integration increases. [ABSTRACT FROM AUTHOR]

High-penetration photovoltaic (PV) integration into a distribution network can cause serious voltage overruns. This study proposes a voltage hierarchical control method based on active and reactive power coordination to enhance the regional voltage autonomy of an active distribution network and improve the sustainability of new energy consumption. First, considering the reactive power margin and spatiotemporal characteristics of distributed photovoltaics, a reactive voltage modularity function is proposed to divide a distribution grid into voltage regions. Voltage region types and their weak points are then defined, and the voltage characteristics and governance needs of different regions are obtained through photovoltaic voltage regulation. Subsequently, a dual-layer optimal configuration model of energy storage that accounts for regional voltage regulation is established. The upper-layer model focuses on planned configurations to minimize the annual comprehensive operating cost of the energy storage system (ESS), while the lower-layer model focuses on optimal dispatch to achieve the best regional voltage quality. KKT conditions and the Big-M method are employed to convert the dual-layer model into a single-layer linear model for optimization and solution. Finally, an IEEE 33-node system with high-penetration photovoltaics is modeled using MATLAB (2022a). A comparative analysis of four scenarios shows that the comprehensive cost of an ESS decreased by 8.49%, total revenue increased by 19.36%, and the overall voltage deviation in the distribution network was reduced to 0.217%. [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]

With the growing distributed PV installation rate in distribution systems, voltage regulation difficulties such as local voltage violations and fluctuations have become common. To solve the voltage regulation problems, the local voltage regulation method using volt‐var (VV) function is effective for its high regulation speed, high accuracy, and flexibility. However, there are still hurdles on real application, such as parameter setting difficulties, insufficient voltage fluctuation mitigation effect, and unfairness of reactive power generation between PV customers. To further improve the VV function, this paper proposes a PID closed‐loop based VV function and mode‐switching function of PV smart inverter (SI). To validate the proposed methods, numerical simulations were conducted using a 6‐feeder distribution system model based on the JST‐CREST 126 distribution feeder model. According to the simulation result, the proposed method can better mitigate the local voltage violation compared to basic VV function based on the VV curve, also improve the fairness between PV customers, while the total reactive power generation and tap operations increases for the aim of more adequate voltage regulation. © 2024 The Authors. IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Renewable energy, particularly wind energy, is expected to contribute significantly to the overall power generation. Induction machines are extensively used as generators in wind power generation because of their multiple benefits, such as robustness, reliability, and low cost and maintenance. However, due to the reactive power demand from the system to which they are connected, this type of generator brings new problems related to power quality, generally consisting of voltage regulation and reactive power compensation. These problems may cause voltage drops and dynamic instability. This study presents a metaheuristic method to attain a microgrid system with an optimal distribution based on its different constraints. The numerical model of an induction generator constructed in MATLAB/Simulink was used, and the simulation results obtained demonstrate the efficacy of the proposed metaheuristic technique. [ABSTRACT FROM AUTHOR]

Integrating photovoltaic systems (PV) into the grid has garnered significant attention due to increasing interest in renewable energy sources. Maximizing the PV systems output power is crucial for improving energy efficiency and reducing operating costs. This paper presents a comparative analysis of two different techniques of maximum power point tracking (MPPT): perturb and observe (P&O) and artificial neural network (ANN) MPPT, focusing on their application in grid-connected PV systems. The paper evaluates their performance under various operating conditions, including changes in irradiance and temperature, that are discussed in three cases. The comparative analysis includes metrics such as voltage regulation and power loss. MATLAB Simulink is utilized to implement P&O and ANN MPPT methods, which include a PV cell connected to an MPPT-controlled boost converter. The simulation demonstrates the power loss of the PV model as well as the voltage regulation in the three cases for the two methods. The results obtained in simulation and implementations show that the ANN method outperforms the P&O in the three cases discussed in terms of power loss, voltage regulation, and efficiency. The results also show that the change in output power from PV is noticeable when compared to changes in radiation, while the change is slight when temperatures change. [ABSTRACT FROM AUTHOR]

The use of distributed photovoltaics (PVs) on a large scale often causes voltage over-limit problems in distribution networks. This paper proposes a distributed photovoltaic cluster collaborative optimization voltage control strategy based on an improved community algorithm to address the issue of centralized control being unable to respond quickly to the randomness of distributed photovoltaics and the difficulty of achieving overall coordination with local control. First, by improving the community algorithm, the division of reactive and active clusters, considering the power balance and node coupling degree, is realized. Then, the cluster-coordinated voltage control strategy is proposed by making full use of the power control ability of a photovoltaic inverter. Finally, a voltage regulation ability evaluation index is proposed to assess the node regulation ability within the cluster and select key nodes. This effectively reduces the number of control nodes. The simulation analysis of the improved IEEE 69 distribution network shows that the proposed voltage control strategy can mitigate the issue of voltage over-limit in high-permeability distributed photovoltaic access distribution and enhance the photovoltaic consumption capacity. [ABSTRACT FROM AUTHOR]

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

High-voltage aqueous zinc ion batteries (AZIBs) with a high-safety near-neutral electrolyte is of great significance for practical sustainable application; however, they suffer from anode and electrode/electrolyte interfacial incompatibility. Herein, a conversion-type anode chemistry with a low anodic potential, which is guided by the Gibbs free energy change of conversion reaction, was designed for high-voltage near-neutral AZIBs. A reversible conversion reaction between ZnC2O4·2H2O particles and three-dimensional Zn metal networks well-matched in CH3COOLi-based electrolyte was revealed. This mechanism can be universally validated in the battery systems with sodium or iodine ions. More importantly, a cathodic crowded micellar electrolyte with a water confinement effect was proposed in which lies the core for the stability and reversibility of the cathode under an operating platform voltage beyond 2.0 V, obtaining a capacity retention of 95% after 100 cycles. Remarkably, the scientific and technological challenges from the coin cell to Ah-scale battery, sluggish kinetics of the solid-solid electrode reaction, capacity excitation under high loading of active material, and preparation complexities associated with large-area quasi-solid electrolytes, were explored, successfully achieving an 88% capacity retention under high loading of more than 20 mg cm−2 and particularly a practical 1.1 Ah-level pouch cell. This work provides a path for designing low-cost, eco-friendly and high-voltage aqueous batteries. [ABSTRACT FROM AUTHOR]

Integrating renewable energy sources and distributed energy resources (DERs) in the Malaysian low voltage distribution network has introduced voltage stability challenges, particularly voltage rises, leading to detrimental impacts on network performance. This paper presents a novel reactive power control strategy for addressing these challenges. Unlike conventional methods with fixed reactive power references, the proposed technique dynamically adjusts the reactive power reference in real time, considering voltage and active power injection. It calculates the rate of change in reactive power reference (ΔQ) per second by analyzing Volt-VAR and Watt-VAR components and updates the reference accordingly. Simulations conducted on a low voltage distribution network in Taman Impian Putra, Malaysia, showcase the adverse effects of high photovoltaic (PV) penetration on voltage stability and highlight the success of the proposed strategy in mitigating voltage rise. The technique effectively reduces average voltage, maintains voltage regulation during high sun irradiance and low load demand periods, and surpasses the adaptability of existing methods dependent on PV active injection or network voltage alone. The proposed strategy ensures accurate control and efficiently addresses dynamic network changes by accounting for both PV active power injection and network voltage. This approach offers enhanced voltage regulation, adaptability to varying network conditions, and reduced losses, making it a promising solution for mitigating voltage rise in the Malaysian low voltage distribution network. The simulations, validated using MATLAB Simulation and OpenDSS, confirm the strategy’s efficacy and potential for real-world implementation. [ABSTRACT FROM AUTHOR]

Distributed photovoltaics (DPVs) are widely distributed and the output is random, which brings challenges to the safe operation of the distribution network, so the construction of photovoltaic aggregations can effectively participate in the flexible regulation of the power system. At present, the extraction of DPV clustering features is not sufficient, only considering the output characteristics of PVs. Certain PVs under some nodes may have a more pronounced regulation effect, but they may be ignored in the clustering process. To address the above problems, this paper proposes a DPV aggregation approach considering the distribution network topology. It combines the voltage sensitivity and the power curve and regards them as clustering features to form the DPV aggregation with the highest average voltage sensitivity participating in voltage regulation. The simulation on the IEEE 33-node system verifies that the proposed aggregation approach can select DPV aggregation more suitable for voltage regulation, and make full use of the aggregation to realize the optimal voltage regulation effect. [ABSTRACT FROM AUTHOR]

Global demand for fossil fuels is highly increasing, necessitating energy efficiency to be enhanced in transitioning to low-carbon energy systems. Electric railways are highly efficient in reducing the transportation demand for fossil fuels as they are lightweight and their energy demand can be fed by renewable energy resources. Further, the regenerative braking energy of decelerating trains can be fed to accelerating trains and stored in onboard energy storage systems (ESSs) and stationary ESSs. It is fundamental to model electric railways accurately before investigating approaches to enhancing their energy efficiency. However, electric railways are challenging to model as they are nonlinear, resulting from the rectifier substations, overvoltage protection circuits, and the unpredictability and uncertainty of the load according to the train position. There have been few studies that have examined the ESS location's impact on improving the energy efficiency of electric railways while using specialised simulation tools in electric railways. However, no single study exists that has studied the location impact of stationary ESSs on the energy efficiency of electric railways while the trains are supported by onboard ESSs. Given these goals and challenges, the main objective of this work is to develop a model using commercial software used by industry practitioners. Further, the energy saving is aimed to be maximised using stationary ESSs installed in optimal locations while trains are supported by onboard ESSs. The model includes trains, onboard ESSs, rail tracks, passenger stations, stationary ESSs, and traction power systems involving power lines, connectors, switches, sectioning, and isolators. In this article, a test scenario is presented comprising two trains running on a 20 km with three passenger stations and two substations. The trains and track are modelled in OpenTrack simulation software (Version 1.9) while the power system is modelled in OpenPowerNet simulation software (Version 1.11). The two simulation tools are used in the railway industry and can produce realistic results by taking into account the entire electrical network structure. A stationary ESS is added on the wayside and moved in steps of 1 km to obtain the optimal location before investigating the impact of stationary ESSs on the performance and energy management of onboard ESSs. It is found that the energy saving when installing a stationary ESS at the optimal location is 56.05%, the peak-power reduction of Substation 1 is 4.37%, and the peak-power reduction of Substation 2 is 18.67%. [ABSTRACT FROM AUTHOR]

This paper introduces a Fuzzy Logic Controller designed for an on-load tap changer within medium voltage distribution systems with bulk penetration of Distributed Energy Resources. As the on-load tap changer remains one of the most essential forms of voltage regulation in medium voltage distribution networks, improving its operation is a cost-effective response to the emerging voltage violations caused by intermittent generation during the early stages of the energy system transformation. Software-in-the-loop simulations were conducted to validate the effectiveness of the proposed algorithm compared to the conventional methods. A modified CIGRE Medium Voltage Distribution Network Benchmark in European Configuration was modelled while the controller code developed in Python 3.12 was running on a PC, both coupled in a real-time closed-loop environment. The analyses showed that the proposed algorithm managed to reduce overvoltage from 7.02% to 4.85% in the benchmark network, thus demonstrating that the algorithm is efficient and ready for on-field implementation. [ABSTRACT FROM AUTHOR]

The two-stage power converter is currently the most widespread topology for three-phase grid-connected photovoltaic (PV) systems. The PV power is injected to the grid through the regulation of the dc-link voltage. This method is commonly called the voltage control method, whereby the current is controlled indirectly. This paper focuses on the modelling of power converters and the parameter design of proportional-integral (PI) controllers, based on the bandwidth of the inner current loop and the outer voltage loop. It is assumed that the inner loop has a bandwidth that is ten-fold bigger than that of the outer loop, in order to fully decouple the dual loops. The PI parameters are thus determined through this relationship, and two sets of simulations are run to validate the methodology used. Results show that the controllers give highly satisfactory performance even in the presence of transients introduced by rapidly varying irradiance model. [ABSTRACT FROM AUTHOR]

This research paper aims to investigate the application of a unified power flow controller (UPFC) for relieving power congestion on a 500/230 kV grid, Power congestion occurs when the demand for electrical power exceeds the transmission capacity of the grid resulting in potential stability issues and voltage fluctuations. The UPFC is a flexible and advanced power electronic device that can regulate power flow and voltage levels in real-time hence offering a potential solution to alleviate congestion. This study explores the principles of UPFC operation its control strategies and the impact of its installation on power system stability and reliability. The research methodology involves computer simulations and analysis of the results obtained. [ABSTRACT FROM AUTHOR]

This paper explores the impact of integrating Flexible AC Transmission Systems (FACTS) controllers, specifically the Static Synchronous Series Compensator (SSSC) and the Static Synchronous Compensator (STATCOM), on power system performance. The objective of this study is to evaluate how these controllers can enhance various aspects of power system operation, including voltage regulation, power flow stability, and overall system efficiency. The methodology involves simulating power systems with and without the deployment of SSSC and STATCOM and analyzing their effects on voltage profiles, power flow characteristics, and system losses. The findings reveal that both SSSC and STATCOM significantly improve voltage stability and power flow control, leading to reduced system losses and enhanced operational efficiency. This study introduces a novel approach by comparing the performance enhancements provided by SSSC and STATCOM in different operational scenarios, offering valuable insights into their effectiveness. The results underscore the potential of FACTS technology in advancing power system stability and efficiency, making a substantial contribution to the field of power system optimization [ABSTRACT FROM AUTHOR]

In this study, an optimized dual-layer configuration model is proposed to address voltages that exceed their limits following substantial integration of photovoltaic systems into distribution networks. Initially, the model involved segmenting the distribution network's voltage zones based on distributed photovoltaic governance resources, thereby elucidating the characteristics and governance requisites for voltages across distinct regions. Subsequently, a governance model for voltage limit exceedances, grounded in optimizing energy storage configurations, was formulated to mitigate photovoltaic power fluctuations by deploying energy storage systems. This model coordinates the reactive power output of photovoltaic installations with the active power consumption of energy storage systems, thereby augmenting voltage autonomy in the power grid. This study leveraged Karush–Kuhn–Tucker (KKT) conditions and the Big-M method to transform the dual-layer model into a single-layer linear model, thereby enhancing solution efficiency and precision. Finally, a simulation was carried out to demonstrate that the strategy proposed from this research not only achieves commendable economic efficiency, but also significantly improves the regional voltage effect by 28.7% compared to the optical storage capacity optimization model. [ABSTRACT FROM AUTHOR]

A new passivity-based voltage tracker for islanded Direct Current (DC) microgrids is presented in this paper. The proposed design develops a new sufficient condition for passivity-based state feedback with proportional and integral control using the attracting ellipsoid method. In this paper, we consider the time behavior of the extended vector, which completely describes the principle properties of the closed-loop system such as the boundedness of the trajectories within some ellipsoid and the dependence of its "size" on the feedback gains. The next step, which we are realizing in this paper, is the minimization of the attractive ellipsoid by selecting the "best" admissible feedback parameters. Here, it is important to note that the applied feedback is of PD-type (proportional differential) on the system state and I-type (integral) on the output. This is a new construction of the suggested feedback which gives several advantages for a designer. The suggested control is decentralized and uses only the local states; it is cost-effective and avoids the time delays in the communication networks which are needed if centralized control is used. The suggested control is carried out in the bilinear matrix inequality (BMI) framework. Extensive simulation is performed on a test system composed of renewable energy sources, under plug and play (PnP) operations, and uncertainties in distribution lines and loads. The performance of the proposed decentralized voltage controller is compared with that of a voltage tracker present in the literature. The comparison shows the improvements introduced by the proposed control ensure the stability of the dc bus voltage and a quick response under different scenarios of operating conditions. [ABSTRACT FROM AUTHOR]

As the electricity market expands with increasing demand, power systems are under more pressure to operate within secure limits. One way to ensure this is through load flow studies, which analyze the steady-state conditions of a power system under various load and generator scenarios. However, the complexity of power systems and the growing demand for electricity make it difficult to accurately predict and analyze power flow. The use of simulation software like electrical transient and analysis program (ETAP) can improve the accuracy and efficiency of load flow studies, but it still poses challenges such as complexity and lack of standardization in use. This paper focuses on voltage stability, voltage regulation, and the impact of capacitor banks on buses through load flow studies. Real data from four hydropower plants is used to analyze voltage drop, voltage regulation and power losses at each bus. The findings highlight the effectiveness of capacitor banks in improving voltage profiles and reducing power losses, thus proposing an optimized system design. These enhancements facilitate better planning, operation, and expansion of power systems, ensuring more reliable and efficient electricity supply. [ABSTRACT FROM AUTHOR]

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

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Distribution systems are integrating a growing number of distributed energy resources and converter-interfaced generators to form active distribution networks (ADNs). Numerous studies have been undertaken to mitigate various challenges in ADNs. However, voltage deviation and reactive power control still requires more attention from researchers and power system engineers. The Volt/VAr control (VVC) concept has been developed to improve the voltage quality, minimize active power losses, and maintain the voltage profile in ADNs. The deployed utility-owned legacy voltage control mechanisms such as on-load tap changers, capacitor banks, and automatic voltage regulators operate in discrete, slow timescales and unidirectionally, rendering them insufficient for optimal voltage regulation in ADNs. Owing to the increasing use of smart meters, smart inverters (SIs), smart sensors, data analytics tools, and improved communication networks, data has become an important resource. Data-driven control approaches, particularly reinforcement learning (RL)-based, have therefore gained more attention in recent years in effectively solving the VVC decision-making problem. This comprehensive review presents a detailed analysis of advanced approaches used to address the VVC problem. It includes a general overview of the problem formulation, control frameworks, and basic notations, as well as detailed comparisons of the existing and recently proposed methods. This study focuses on data-driven approaches, especially RL-based algorithms. Some of the open research challenges experienced in the application of these algorithms such as safety, data, scalability, communication problems, interpretability and cybersecurity threats are presented alongside the future research perspectives such as Internet of Things (IoT), Transfer Learning (TL), hybrid and human-in-the-loop AI approaches.

Renewable energy, particularly wind energy, is expected to contribute significantly to the overall power generation. Induction machines are extensively used as generators in wind power generation because of their multiple benefits, such as robustness, reliability, and low cost and maintenance. However, due to the reactive power demand from the system to which they are connected, this type of generator brings new problems related to power quality, generally consisting of voltage regulation and reactive power compensation. These problems may cause voltage drops and dynamic instability. This study presents a metaheuristic method to attain a microgrid system with an optimal distribution based on its different constraints. The numerical model of an induction generator constructed in MATLAB/Simulink was used, and the simulation results obtained demonstrate the efficacy of the proposed metaheuristic technique.

In the recent years there has been a significant increase in the interest surrounding the interconnection of AC and DC networks due to its potential to improve the power systems reliability. Despite the potential advantages, however, the AC and DC grid coexistence can pose challenges if not appropriately managed. In this scenario, this paper presents an enhanced control scheme enabling the use of Virtual Synchronous Generators (VSGs) as elements of interconnection between AC and DC networks. The proposed solution enables VSG operation with both fast dynamics for DC voltage regulation and slow dynamics for AC inertia emulation. This approach accommodates the contrasting requirements arising from the distinct mechanisms of DC voltage regulation and AC frequency regulation. Simulation and experimental results obtained with a 8 kVA three-phase converter prototype are provided to validate the effectiveness of the proposed technique and prove its better performances with respect to the solutions currently presented in literature.

This paper proposes a tube model predictive control method considering uncertainties of renewable energy generation in the low-voltage distribution network. For relatively low dependence on communication networks, a decentralized voltage control framework is urgently needed to be developed for voltage regulation in the low-voltage distribution network. Opposed to the traditional voltage control techniques, a novel decentralized tube model predictive voltage control (TMPC) strategy is proposed. First, this strategy entails the formulation of a discrete model encompassing distributed photovoltaic units and energy storage systems intertwined with the distribution grid model based on voltage sensitivity. Then, considering the worst case of voltage deviations caused by uncertain and stochastic power fluctuation, we specifically discuss a robust positively invariant to determine the control section of controllers. Further, the strategy employs tube model predictive controllers encompassing nominal and auxiliary controllers in distribution areas. The nominal controller generates a central path for different voltage operating points of each distribution area, and the auxiliary controller makes all trajectories lie in a bounded neighborhood called a tube. The effectiveness of the proposed control strategy is investigated on a test system containing renewable energy resources.

The global capacity for renewable electricity generation has surged, with distributed photovoltaic generation being the primary driver. The increasing penetration of non-programmable renewable Distributed Energy Resources (DERs) presents challenges for properly managing distribution networks, requiring advanced voltage regulation techniques. This paper proposes an innovative decentralised voltage strategy that considers DERs, particularly inverter-based ones, as autonomous regulators in compliance with the state-of-the-art European technical standards and grid codes. The proposed method uses an optimal reactive power flow that minimises voltage deviations along all the medium voltage nodes; to check the algorithm’s performance, it has been applied to a small-scale test network and on a real Italian medium-voltage distribution network, and compared with a fully centralised ORPF. The results show that the proposed decentralised autonomous strategy effectively improves voltage profiles in both case studies, reducing voltage deviation by a few percentage points; these results are further confirmed through an analysis conducted over several days to observe how seasons affect the results.

Matching between low-voltage high-current capacity battery/fuel cell with high-voltage low-current motors in electric vehicles (EVs) requires paralleling-connection multi-stage power electronic converter with accurate modeling and control system. For high-voltage low-current drives of EVs with high-boosting/bucking gain, single-stage single-arm DC/DC converters suffer from unstable output voltage and the impractical choice of charging/discharging elements. Therefore, a multi-stage multi-arm DC/DC converter is researched to solve the problems of high boosting/bucking gain and minimized the voltage and current ripples. This paper presents parametric sizing, dynamic modeling, and analysis of all logical operational modes for a new high-gain DC/DC converter suitable for deployment in EV applications. The proposed topology composes of three-stage interleaved-input composed of cascaded two stages and double float-output as a third stage with bidirectional current capability. In this study, parametric design, and sizing for the three stages are performed according to the prerequisite ratings. Then, an analysis is conducted on rules of operating the DC/DC converter along with a discussion on considerations taken into account for such a critical design. An investigation of the dynamic behavior of the suggested DC/DC converter is carried out through a state-space model with switches’ states. Furthermore, a simulation and measurement-based validation of the derived mathematical models are conducted. The theoretical based analysis, design, and boosting gains are confirmed through a constructed and tested prototype given data on power supply and load utilization. A discussion on the choice of semiconductor equipment and reactive elements is provided for the proposed DC/DC converter. The experimental results show that the three stages can be used in a separate mode or in a cascaded booster.

Interconnected Microgrid (IMG) networks have been suggested as the best to build electrical networks in remote villages far from the main electricity grid by interconnecting the nearby distributed energy resources (DERs) through power electronic converters. Interconnecting different DERs results in voltage deviation with unequal power-sharing, while voltage performance is a significant challenge. The control strategies for these converters are essential in the operational stability of any IMG network under study. In this paper, we propose an improved droop control method aiming to manage the power flow among the IMGs by maintaining the constant desired voltages in the network with minimum voltage deviation, resulting in the minimization of power losses. We found that the minimum voltage deviation at the load side (converter-3) was between 0.58 and 0.56 V, while the voltage deviation for both converter-1 and converter-2 remained below 0.5 V. This leads to efficient voltage regulation, resulting in the stability of an IMG network. To verify the feasibility of this method, MATLAB/SIMULINK has been used.

Active power sharing and voltage regulation are two of the major control challenges in the operation of the voltage source converter based multi-terminal high-voltage DC (VSC-MTDC) system when integrating large-scale offshore wind farms (OWFs). This paper proposes two novel adaptive voltage reference based droop control methods to regulate pilot DC voltage and share the power burden autonomously. The proposed Method I utilizes DC grid lossy model with the local voltage droop control strategy, while the proposed Method II adopts a modified pilot voltage droop control (MPVDC) to avoid the large errors caused by the DC grid lossless model. Dynamic simulations of a five-terminal MTDC grid are carried out using MATLAB/Simulink SimPowerSystems /Specialized Technology to verify the proposed autonomous control methods under various types of disturbance and contingency. In addition, comparative study is implemented to demonstrate the advantages of the proposed methods.

Voltage stability is critical in electrical power systems, and automatic voltage regulators play a crucial role in maintaining voltage levels within permissible limits. Due to their simplicity and effectiveness, traditional Proportional-Integral-Derivative (PID) controllers have been widely used in automatic voltage regulation. However, they may not always perform optimally in complex power systems with varying operating conditions and external disturbances. This research introduces an integrated approach of employing a 3-degrees of freedom-PID-Acceleration (3-DOF-PIDA) controller coupled with a disturbance observer-based control strategy. This combination is embedded with a simple but effective salp swarm optimisation algorithm. This novel control approach of the combined 3-DOF-PIDA, disturbance observer and salp swarm optimisation will enhance the voltage regulation of the system. The proposed novel control strategy incorporates an acceleration component to continuously adjust its parameters based on system dynamics. Simultaneously, the disturbance observer is responsible for estimating and compensating for external disturbances, further improving the system’s performance. The salp swarm optimization is applied to optimize both the PIDA control parameters and the disturbance observer’s parameters in the automatic voltage regulation system to find optimal solutions that improve voltage regulation and disturbance rejection capabilities. The results are established by performing statistical and graphical analyses with time-varying step load fluctuations, and under various system parameter variations. The results are validated by comparisons to five popular optimization algorithms found in the reviewed literature. The investigations demonstrate that this new proposed approach provides outstanding performance, in the presence of substantial system parameter fluctuations and uncertainties.

The integration of photovoltaic (PV) panels has allowed power distribution systems (PDSs) to regulate their voltage through the injection/absorption of reactive power. The deployment of information and communication technologies (ICTs), which is required for this scheme, has made the PDS prone to various cyber threats, e.g., false data injection (FDI) attacks. To counter these attacks, this paper proposes a data-driven framework to detect FDI attacks against voltage regulation of PV-integrated PDS. Initially, an attack-free system is modeled along with its voltage regulation scheme, where the grid measurements are sent to a centralized controller and the control signals are transmitted back to PVs to be used by their local controllers. Then, a convolutional neural network (CNN) framework is proposed to detect FDI attacks. To train this framework—which should be able to distinguish between normal grid behaviors and attacks—a complete and realistic dataset is formed to cover all normal conditions and unpredictable changes of a PDS during a year. Since normal variations and fluctuations in power consumption lead to changes in the voltage profile, this dataset is enriched using features such as season, weekdays, weekends, load conditions, and PV generation power. The performance of the trained framework has been compared with other supervised Machine Learning-based and deep-learning techniques for FDI attacks against modified IEEE 33- and 141-bus PDSs. Simulation results demonstrate the superior performance of the proposed framework in detecting FDI attacks.

In this paper, a multi-objective cooperative (MOC) controller based on average consensus algorithm is designed to achieve rapid State-of-Charge (SoC) balancing, proportional load current sharing, and flexible DC bus voltage regulation for parallel battery storage units (BSUs) in shipboard DC microgrids. Different from the conventional secondary controllers, the designed MOC controller can simultaneously achieve the above three control objectives with a fully distributed manner without requiring multiple controllers, thereby effectively improving the system stability and reducing the communication burden. Furthermore, an optimized convergence factor is designed to accelerate SoC balancing, and pinning control is introduced to obtain flexible and accurate DC bus voltage regulation. The process of SoC balancing and current sharing analysis, SoC convergence performance analysis, large-signal stability analysis, and global steady-state analysis verifies the rationality and stability of the MOC controller. Finally, the Matlab/Simulink simulation and StarSim HIL experimental results demonstrate the effectiveness and robustness of the designed MOC controller in a shipboard DC microgrid under various testing scenarios. [Display omitted] • The MOC controller can achieve rapid SoC balancing, proportional load current sharing, and flexible bus voltage regulation. • An improved SoC balancing algorithm is developed to accelerate the SoC convergence speed. • The pinning control is introduced to flexibly regulate the DC bus voltage. [ABSTRACT FROM AUTHOR]

The global capacity for renewable electricity generation has surged, with distributed photovoltaic generation being the primary driver. The increasing penetration of non-programmable renewable Distributed Energy Resources (DERs) presents challenges for properly managing distribution networks, requiring advanced voltage regulation techniques. This paper proposes an innovative decentralised voltage strategy that considers DERs, particularly inverter-based ones, as autonomous regulators in compliance with the state-of-the-art European technical standards and grid codes. The proposed method uses an optimal reactive power flow that minimises voltage deviations along all the medium voltage nodes; to check the algorithm's performance, it has been applied to a small-scale test network and on a real Italian medium-voltage distribution network, and compared with a fully centralised ORPF. The results show that the proposed decentralised autonomous strategy effectively improves voltage profiles in both case studies, reducing voltage deviation by a few percentage points; these results are further confirmed through an analysis conducted over several days to observe how seasons affect the results. [ABSTRACT FROM AUTHOR]

Photovoltaics are one of the most important renewable energy sources to meet the increasing demand for energy. This led to the emergence of Microgrid s, which revealed a number of problems, the most important of which is managing and monitoring their operation, this research contributes mainly by using a maximum power tracking algorithm Which depends on artificial neurons and integrating it with a proposed algorithm for energy management in Standalone DC Microgrid, in order to control the distribution of power and maintain the DC bus voltage level. Maximum Power Point Tracking (MPPT) algorithm based on ANN+PID is used. Where ANN tracks the maximum power point by estimating the reference voltage using real-time data such as temperature and solar radiation. The PI controller reduces the error between the measured voltage and the reference voltage and makes the necessary adjustments in order to control the boost converter connected to the photovoltaic panels. While the process of controlling the DC bus voltage level is done by controlling the battery charging and discharging process through the power management algorithm and controlling the Bidirectional converter switches according to the battery's state of charge. The simulation results obtained by used MATLAB Simulink are shown that the used MPPT algorithm achieved the maximum power with the least amount of fluctuation, the method's efficiency was 99.92%, and its accuracy was 99.85%, as well as the success of the power management algorithm controlling the battery charging/discharging process and maintaining the DC voltage level at the specified value in different operating scenarios. [ABSTRACT FROM AUTHOR]

P2P power trading is necessary for efficiently using consumer electricity not subject to FIT. However, the execution rules for P2P power trading do not include restrictions on voltage, and there is a trade-off between the activation of the P2P power trading market through the mass introduction of PV and the optimization of the voltage of the power distribution system. In addition, there is a tendency for output curtailment to be biased toward consumers connected to the end of the grid. Since consumers cannot choose the interconnection location, there are concerns about unfairness. In this study, we investigate a new P2P model that includes voltage constraints for the execution rules of P2P power trading to avoid voltage deviation while ensuring benefits and fairness for the participants. In the proposed model, to increase the incentive to participate in the P2P power trading market, we consider compensating consumers who receive output curtailment signals due to voltage constraints. In addition, the profit is secured by differentiating the compensation cost unit price depending on the contract's availability. A case study was conducted on this model using the IEEE 33 bus system. The results show that the proposed model is superior. [ABSTRACT FROM AUTHOR]

DC micro-grids are gaining more attention and becoming more predominant due to its robustness and ease of control. To confront the stability issues of the DC Micro-grid system, a model free intellectual Control approach is proposed and recognized with a deep Q-learning controller to influence the functions of DC–DC boost converter. This self-reliant model of deep Q-learning controller establish a suitable communication link among the agent-environment by applying the reward/penalty algorithm for attaining the stable output voltage with its training statistics. Upon learning the state of agent, an optimal proposal is defined by the controller to attain the stabilized voltage at the output for all possible operating scenarios. The simulation and experimental studies validate the performance of the controller with higher accuracy, reduced overshoot, and faster settling time upon the transient states. [ABSTRACT FROM AUTHOR]

This paper presents a control scheme for virtual synchronous generators (VSGs) in PV inverters, designed to enhance grid frequency and voltage. Through the skillful management of active and reactive power, this control scheme enables PV inverters to interact seamlessly with the main grid in response to grid events, including voltage and frequency fluctuations. The VSG controller is implemented using Matlab Simulink, and its effectiveness is rigorously assessed under various scenarios in a case study involves a 50 kVA rated PV inverter, a 50 kW rated PV system, and a 220 V grid phase voltage. In conditions of low power generation from the PV system (solar radiation of 200 W/m²) and high load power (120 kW and 37.5 kVAr), the load voltage drops to 202.4 V. The VSG controller successfully raises the grid voltage by 17.6 V, stabilizing it at 220 V. Conversely, in scenarios of high PV power generation (solar radiation of 1000 W/m²) and low load power (20 kW and 7.5 kVAr), the grid voltage surges by 10 V, reaching 230 V. The proposed control strategy adeptly fine-tunes the voltage, ultimately stabilizing at 220 V. Additionally, when the frequency deviates within ±0.4 Hz from the nominal frequency of 50 Hz, the proposed control effectively restores the frequency to its nominal value. [ABSTRACT FROM AUTHOR]

Nonlinear controllers are useful if the equations governing the system dynamics are nonlinear. The fuel cell (FC)-fed boost converter is a nonlinear system as the VI characteristics of the fuel cell and the output voltage to duty cycle transfer function of the boost converter are nonlinear. The choice of a nonlinear controller depends on the dynamic performance of the FC-fed boost converter for wide load variations. This paper compares the performance of the system using conventional sliding mode control (CSMC) and super twisting sliding mode control (STSMC) strategies for tight voltage regulation for the load disturbance and reference voltage tracking. Simulation and experimental results of the fuel cell-fed 600 W boost converter prove the supremacy of STSMC strategy over CSMC strategy in terms of overshoot, undershoot, settling time and chattering reduction. [ABSTRACT FROM AUTHOR]

Energy storage system play a crucial role in safeguarding the reliability and steady voltage supply within microgrids. While batteries are the prevalent choice for energy storage in such applications, their limitation in handling high‐frequency discharging and charging necessitates the incorporation of high‐energy density and high‐power density storage devices to enhance power quality, maintain power balance, and reduce fluctuations. In this study, we introduce a hybrid energy storage system (HESS) solution, combining a battery and a supercapacitor, to address intermittent power supply challenges. The effective management of this HESS is pivotal for constant DC voltage and sustaining microgrid stability. To achieve this, we propose an innovative control strategy called the Adaptive Filter‐Based Method (AFBM) for DC microgrid operation, which prioritizes stable and smooth performance while addressing safety and degradation concerns related to the storage devices. Our control strategy determines the distribution of charging and discharging currents for each storage device within the DC microgrid based on their state of charge. We conducted simulations in MATLAB/Simulink, comparing the proposed AFBM method with the conventional filter‐based approach using identical configurations, parameters, and operational modes. The results demonstrate the superior performance of our proposed system, showcasing improved voltage stability, more equitable load distribution, and efficient charging and discharging of storage devices compared to the traditional method. This research contributes to the advancement of microgrid energy storage solutions, enhancing their reliability and performance. [ABSTRACT FROM AUTHOR]