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The conventional inverter is undergoing a transformation into a smart inverter, driven by the expanding penetration of Photovoltaic (PV) power production in Low Voltage (LV) systems. The adoption of smart inverters is on the rise. Power companies are keen on integrating them into their networks to acquire essential frequency and voltage support as required. These inverters actively exchange actual and reactive power in connection with the grid, altering the system's operational state. This dynamic behavior within the distribution level of power networks might give rise to unprecedented issues. This paper investigates the influence of diverse connection prerequisites that explore the methods for determining the Hosting Capacity (HC) of PV solar systems and their applicability within the low-voltage utility grid. Smart inverters provided with different Volt-VAr and Power Factor (PF) regulation capabilities are analyzed using MATLAB SIMULINK. The outcomes reveal a notable augmentation in the network's HC. This progress improves the grid's attributes, and the incorporation of smart inverter functionalities stands to considerably facilitate incorporating PV solar installations into electrical networks. [ABSTRACT FROM AUTHOR]

This paper presents a distributed consensus-based voltage and frequency control (VFC) strategy for isolated microgrids with distributed energy resources (DERs) and induction motor loads. The proposed controller coordinates the DERs to regulate microgrid frequency and voltage while mitigating fault-induced delayed voltage recovery (FIDVR), a phenomenon where system voltage remains depressed for several seconds after fault clearance due to induction motor stalling. The VFC loop adjusts DER voltage setpoints based on frequency deviation and voltage level to regulate voltage and mitigate FIDVR events, while the active power control loop maintains frequency stability by coordinating active power sharing among DERs and compensating for the constant power load behavior of stalled induction motors. A proximity-based reactive power support prioritization and a distributed voltage estimator enhance the controller's response to FIDVR events. Coordination between the VFC and active power control loops is achieved through adaptive gain adjustment and a voltage recovery coordination term. Simulation results demonstrate the effectiveness of the proposed controller in maintaining microgrid stability, ensuring fast voltage recovery, and providing robust performance under various operating conditions, including communication delays and different fault durations. [ABSTRACT FROM AUTHOR]

In this paper, a novel direct power control technique founded on fuzzy logic controller (FLC-DPC) is selected to master and control the DFIG for wind energy conversion system (WECS). The fuzzy logic controller replaces both hysteresis regulators and the switching table in the proposed strategy. Seeking to enhance the control and overcome the defects associated with the conventional DPC (C-DPC) technique, this control depends on the errors of both active and reactive powers. The suitable rotor voltage vector for the inverter is obtained by FLC-DPC. The proposed control strategy is applied to the WT-DFIG system, in order to study its effectiveness. To reflect a real WECS operation, this study considers the wind's random behaviour in successive and continuous ways throughout all WT-DFIG operating modes. Also, it takes into consideration all compensated local reactive power modes. The studied system and the proposed control were tested under MATLAB/Simulink environment. The obtained results showed the high effectiveness of the proposed control in terms of response time, robustness and ease. Consequently, C-DPC's drawbacks are eliminated, and the ripples in compensated local reactive and produced active powers are reduced. Additionally, the total harmonic distortions (THDs) of injected currents are reduced, which improves their quality. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal series inductance to minimize reactive power and conduction losses in the single-phase-shift modulation of a dual-active-bridge (DAB) converter. Considerable variations in the root mean square (RMS) current of the DAB converter occur due to changes in input voltages. This study visually analyzes the multivariate variation of RMS current in three-dimensional space, considering inductance and input voltage conditions. Additionally, the series inductance is optimized to ensure consistent performance under varying input voltages, using the coefficient of variation. Analytical examination and validation of RMS current changes with respect to series inductance under different input voltage conditions are conducted using a prototype 48 V–12 V DAB converter. Based on this analysis, an appropriate series inductance for optimizing performance is proposed. [ABSTRACT FROM AUTHOR]

This study focuses on reactive power planning in the IEEE30-bus test system, specifically involving the integration of flexible AC transmission systems (FACTS) within the utility system. The primary objective is to minimize power loss and voltage deviation. To address this, a recently developed optimization algorithm called modified ant-lion optimizer (MALO) is applied to solve the optimal reactive power dispatch (ORPD) problem on the IEEE 30-bus system. A comparative analysis is conducted between the results obtained with and without FACTS devices. The findings reveal that the utilization of FACTS devices leads to significantly improved outcomes compared to scenarios without FACTS devices. Among the FACTS devices studied, the unified power flow controller (UPFC) demonstrates superior performance compared to the static synchronous compensator (STATCOM) and interline power flow controller (IPFC). [ABSTRACT FROM AUTHOR]

This research introduces a resilient Sensor-Less 1st Sliding Mode (SL-FOSM) approach employing a novel observer, the Artificial Neural Network with Model Reference Adaptive System-Adaptive (Neural-MRAS), for wind turbine chains. The proposed model is implemented on a Doubly Powered Induction Generator (DPIG) operating under genuine variable speed conditions in the Adrar region in Algeria. The control objective is to independently regulate the active and reactive power of the DPIG stator, achieved through decoupling using the field-oriented control technique and control application via FOSM-C. Notably, this methodology reduces both the control scheme cost and the DPIG size by eliminating the need for a speed sensor (encoder). To enhance the MRAS-PI, an Artificial Neural Network (ANN) is suggested to replace the typical classical Proportional-Integral (PI) controller in the adaptation mechanism of MRAS. The rotor position estimation is scrutinized and discussed across various load conditions in low, zero, and high-speed regions. Optimal controller parameters are determined through particle swarm optimization (PSO). The results demonstrate that the proposed observer (Neural-MRAS) exhibits compelling attributes, including guaranteed finite time convergence, robust performance in response to speed variations, high resilience against machine parameter fluctuations, and adaptability to load variations when compared to the MRAS-PI. Consequently, the estimated rotor speed converges to its actual value, showcasing the capability to accurately estimate position across different speed regions (low/zero/high). [ABSTRACT FROM AUTHOR]

In wind energy generation systems, ensuring high energy quality is critical but is often compromised due to the limited performance and durability of conventional regulators. To address this, this work presents a novel controller for managing the machine-side inverter of a single-rotor large wind turbine system using an induction machine-type generator. The proposed controller is designed using proportional, integral, and derivative error-based mechanisms, which fundamentally differ from traditional proportional-integral (PI) regulators. Key features of the proposed regulator include its simplicity, cost-effectiveness, ease of implementation, reduced number of gains, and rapid dynamic response. This regulator enhances the direct power control (DPC) approach, as it integrates two tailored controllers alongside a pulse width modulation strategy to manage the machine inverter. The DPC strategy incorporating the proposed controller was implemented and tested using MATLAB, with various simulations to evaluate its performance and effectiveness. The proposed regulator demonstrated a significant improvement over the PI regulator, with reductions in active power ripples of 69%, 61.70%, and 59.14% across different tests. Additionally, the steady-state error of reactive power was reduced by 54.84%, 85.23%, and 62.68%, and the total harmonic distortion of current decreased by 48.12%, 50.55%, and 56.05%. These results underscore the high efficiency, robustness, and effectiveness of the proposed controller in improving system performance compared to conventional PI regulators. The controller's outstanding performance makes it a promising solution for broader industrial applications. [ABSTRACT FROM AUTHOR]

This paper presents the findings from the initial phases of the SIF BLADE project, focused on demonstrating the capabilities of an offshore wind power plant (OWPP) for power system restoration (PSR). It provides an overview of PSR, highlighting its challenges and operational requirements, alongside the various scenarios considered in the project. The study includes a steady-state analysis to assess whether the OWPP can meet local network demands for both active and reactive power. Results indicate that the OWPP can operate within an envelope that covers all local power requirements. Additionally, electromagnetic transient (EMT) analysis was conducted to evaluate different percentages of grid-forming (GFM) converter penetration during the energisation process. These analyses aimed to determine compliance with transmission system operator (TSO) requirements. Findings demonstrate that all GFM penetration levels met the necessary TSO standards. Furthermore, a novel small-signal analysis was performed to identify the optimal percentage of GFM converters for enhancing system stability during block loading. The analysis suggests that for top-up scenarios, a GFM penetration between 20% and 40% is optimal, while for anchor scenarios, 40% to 60% GFM penetration enhances stability and robustness. [ABSTRACT FROM AUTHOR]

This article concerns the connection process of a squirrel-cage induction generator to the grid/microgrid. Typically, the generator is unexcited, and its connection to the grid is made directly via a switch. This connection causes a high inrush current and grid voltage drop, which local consumers notice. This article proposes a robust power system consisting of the squirrel-cage induction generator, a power electronic converter, and a capacitor bank, all connected in parallel. The proposed configuration and a dedicated control system eliminate the inrush current and compensate for the generator's reactive power during grid-tied operation. The converter controls the generator voltage build-up to adjust the generator voltage to the grid voltage (controlled excitation) and connects the generator to the grid, minimising distortions. Moreover, the system is robust because the failure of the converter does not stop the power generation, unlike a system with a back-to-back converter, where the converter links the generator and the grid. Furthermore, the parallel-connected converter has a significantly reduced power rating because it is only rated for a part of the reactive generator power. The rest of the reactive generator power is delivered by the fixed capacitor bank. The article presents the system configuration, the control method, and laboratory results confirming the system's effectiveness in maintaining high-quality grid voltage during generator-to-grid connection and high-quality power supplied to the grid. [ABSTRACT FROM AUTHOR]

The grid-current-feedback active damping (GCFAD) strategy has been widely utilized in LCL-type cascaded H-bridge static var generator (SVG) systems. Although digital control in GCFAD enhances sampling accuracy, it introduces delays in the subsequent calculation and execution processes, thereby reducing the effective damping region and weakening the robustness of the LCL-type cascaded H-bridge SVG system under a broad domain of grid impedance changes. This paper expands the effective damping area from (0, fR) (fR ∈ (fs/6, fs/3)) to (0, 0.45fs) by introducing a phase-lead compensator into the active damping feedback loop to reduce the delay. This reduces the negative effect of the digital control on the system's effective damping region and significantly enhances its robustness under an extensive domain of grid impedance variations. The improved GCFAD is employed to establish the system's discrete domain model and the controller parameters are adjusted in conjunction with the mentioned model. Simulation outcomes indicate the efficiency of the presented approach. [ABSTRACT FROM AUTHOR]

Energy consumption demands are rapidly increasing every year, with an 8% annual growth rate projected for the next five years. As buildings represent over 35% of this demand, a metering system is required for monitoring to accurately calculate costs. This paper explores the evolution and impact of energy management through smart meters, emphasizing their superiority over traditional electromechanical devices, in applications such as minimizing power losses and enhancing grid reliability. This study compares the performance of five distinct metering systems, including electromechanical and advanced smart meters. Real-time testing across various scenarios is incorporated, examining parameters such as real and reactive power measurement, accuracy and adaptability to smart grids. Key findings revealed that smart meters, notably the EDMI Mk10A, outperform legacy systems in precision, data transmission and energy optimization. In addition, the potential of smart meters to enable dynamic cost calculation and prevent electricity theft is evident. Despite their advantages, challenges such as data privacy, installation costs and electromagnetic radiation concerns, persist. Future investigations to address the identified limitations are required. [ABSTRACT FROM AUTHOR]

It is known that the energies associated with reactive power periodically exchange between power supply and energy storage component(s) of capacitor and/or inductor. However, reactive power may be altered by power electronic devices without capacitors or/and inductors, which cannot be reasonably explained following electrical power theory. In this work, the transmission, dissipation, and storage of electromagnetic energy of either a sinusoidal alternating current or an electromagnetic wave traveling in a transmission line are addressed; a positive definite expression of time-averaged stored energy density instead of the usual non-positive definite one is proposed. It is demonstrated that, under certain conditions, the product of voltage and current intensity may be applied to represent instantaneous power, and active power is consistent with dissipated energy. However, reactive power is related to part of stored energy, which indicates that reactive power relates to part of the energy exchange between the power supply and the considered circuit. Furthermore, it is shown that influences of thyristors on stored energy may be attributed to the change of (fundamental frequency) current intensity induced by the thyristor and the contribution of the resistor to stored energy, which may also alter the value of reactive power. This work may be helpful to establish a bridge between electrical power theory and Poynting's theorem, deepen the understanding of reactive power, and improve electrical power theory. [ABSTRACT FROM AUTHOR]

The operation of converter valves in converter stations often results in high reactive power consumption and harmonic generation, necessitating measures to maintain reactive power balance and ensure power quality. To achieve this, the filter bank circuit breaker is frequently switched on and off during daily operation. In recent years, multiple incidents of circuit breaker breakdown during the opening process have been reported. In this study, power systems computer-aided design (PSCAD)/electromagnetic transients including DC (EMTDC) V5.0 electromagnetic transient simulation software is used to simulate and calculate the overvoltage and inrush current under different configurations of circuit breaker operating mechanism dispersion, opening phase angle, and operating speed. Additionally, the suppression effects of two measures are compared: "phase selection opening" and "phase selection opening combined with controlled opening speed" to mitigate overvoltage and inrush current. The results demonstrate that for BP11/13 filters, HP24/36 filters, and HP3 filters, the combined strategy of "phase-selective opening with controlled opening speed" is more effective in suppressing inrush current and overvoltage. However, for SC filters, the suppression effect of this combined strategy is not significant. Considering economic and practical factors, it is more reasonable to adopt the phase-selective opening measure for SC filters. These findings provide guidance for ensuring the safe operation of AC filter circuit breakers. [ABSTRACT FROM AUTHOR]

In the motor systems, an increase of the power factor is conducive to the improvement of overload capacity and operation reliability. In this paper, a deadbeat strategy based on a power model is proposed. With the help of the power model, the reference power expression is derived, and the reference voltage expressed by the active power, reactive power and power regulation coefficient (m) is obtained. The method proposed in this paper realizes the traditional deadbeat strategy effect, and improves the power factor to some extent. Meanwhile, a new double-vector synthesis method is proposed. Under different reference voltages, different double-vector synthesis modes are directly selected. This results in good steady-state performance with low complexity. In performance comparisons, the proposed method surpasses the widely used duty-cycle double-vector method. Simulation and experimental results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

AC transmission expansion planning (ACTEP) is one of the most critical issues in electric power system expansion planning. In existing research on ACTEP, the reduction of power losses is often overlooked due to the significant computational workload associated with ACTEP problem. While in some instances, minimizing power loss is included as an objective function in the TEP problem, this approach may impact the addition of new lines. Consequently, to address this issue, a four-stage strategy is proposed in this paper for resolving ACTEP problem while considering power loss reduction. Specifically, the reduction of power losses is addressed after the deployment of new transmission lines. Moreover, a hybrid approach, referred to as differential evolution (DE) combined with teaching–learning-based optimization (TLBO) algorithms, called (DE-TLBO), is proposed for optimizing reactive power planning and determining the size of thyristor-controlled series compensators (TCSC) to minimize power loss in ACTEP problem. Simulation results conducted on Graver 6 bus, IEEE 24 bus, and modified IEEE 118 bus systems demonstrate the efficacy of the proposed algorithm when compared to conventional methods such as differential evolution (DE), modified artificial bee colony, and real genetic algorithms (RGA). Additionally, the proposed method also illustrates the effectiveness of utilizing TCSC to reduce power loss in the Graver 6 bus and the IEEE 24 bus systems by 3.72% and 11.95%, respectively. [ABSTRACT FROM AUTHOR]

Researching cluster partitioning and adjustment methods is essential for effectively implementing cluster control strategies and ensuring the safe operation of power grids amid challenges like reverse power flow and voltage violations resulting from large-scale distributed photovoltaic grid integration. The paper comprehensively evaluates factors including electrical distance, supply-demand balance, and power transmission. It introduces a method for partitioning and dynamically adjusting distributed photovoltaic clusters, based on an improved adaptive genetic algorithm (AGA). Firstly, a comprehensive performance index is introduced based on modularity, incorporating intra-cluster power supply rate and inter-cluster power transmission. Next, an unweighted adjacency matrix is employed to encode chromosomes, and an adaptive optimization parameter adjustment strategy is introduced to enhance the AGA, ensuring both direct node connectivity within clusters and improved global solution performance during optimization. By integrating these comprehensive indicators with AGA, a cluster partitioning optimization model is formulated based on the comprehensive indicator system. The IEEE 33-node system is utilized for cluster partitioning simulation analysis with this model. The outcomes demonstrate that, in contrast to the single modularity index-based cluster partitioning approach, the proposed comprehensive indicator method enhances the intra-cluster active and reactive power supply rates by approximately 20.34% and 28.61%, respectively, while decreasing inter-cluster power transmission by roughly 24.98%. Furthermore, in scenarios of insufficient photovoltaic power output, the cluster scheme, after dynamic strategy adjustment, notably mitigates system voltage fluctuations and network losses. [ABSTRACT FROM AUTHOR]

Reliability of the power system can be sustained with a distance relay function of accurate tripping signal. Blocking the relay during a power swing and unblocking with the occurrence of a fault can ensure this function. A fault detection technique is required to achieve blocking and unblocking conditions. Detection of the fault is difficult during a power swing, even more challenging with series compensation due to nonlinear functioning components such as thyristor-controlled reactor and metal oxide varistor. By considering different states of the power system, a new approach is proposed for transmission lines to detect fault during power swing. The proposed technique is based on observation of envelopes defined by local maxima values and uses DC offset current and fifth harmonic values as main parameters. The DC offset voltage and a reactive power tracker are added to provide high accuracy with both fixed and thyristor-controlled series compensation. The proposed method focuses on symmetrical faults. Performance of the proposed technique is presented and verified with a two machine test system. The method is also tested and compared in detail with Western system coordinating council three machine nine bus system by varying selected system parameters. [ABSTRACT FROM AUTHOR]

In the framework of contemporary power systems, a distributed generation (DG) system has benefits, but it also presents several operational challenges. In a networked distributed generation system, islanding is one such problem. Because of the negative consequences, an islanding event should be distinguished from other events, like transients within the minimum time. A multi-level adaptive neuro-fuzzy inference system (ANFIS) is being developed in this work to effectively detect islanding. To train the ANFIS model, a novel hybrid scheme based on Lévy flights and teaching–learning-based optimiser is suggested. The performance of the developed algorithm is evaluated using the IEEE CEC-C06 and other traditional benchmark functions. The ANFIS model's classification regime is significantly improved by the optimisation algorithm. In the test system, renewable energy sources are used to power a voltage source converter unit in a network-forming mode via an energy storage medium. Based on measured frequency, RMS voltage and current, active and reactive power, voltage, and current THD at the point of common coupling (PCC), the trained ANFIS controller deduces the islanding detection command to the circuit breaker. The plan is verified following the UL1741 standard for islanding prevention, yielding notable outcomes with an average detection time of 0.04s and an accuracy of 89.3%. [ABSTRACT FROM AUTHOR]

This paper proposes a Power Harmonic Suppression (Damping) (PHS) based reference current generation scheme, which focuses on simultaneous mitigation of harmonic pulsations in electromagnetic torque, stator real and reactive powers, and DC‐link voltage while retaining sinusoidal stator and grid currents and unity power factor at grid side. The crux of this PHS method lies in its ability to eliminate the harmonic powers developed in the DFIG stator and grid at 100Hz, 200Hz, 300Hz, 400Hz, and 600 Hz owing to second, fifth, and seventh harmonic grid voltages. This is achieved as a result of the elimination of natural fluxes developed in the DFIG air gap due to second, fifth, and seventh harmonic distortions in grid voltage. For this, a single concurrent reference current generation technique is developed for RSC and GSC to mitigate the oscillations of electromagnetic torque, stator real and reactive powers, and ripples in DC‐link voltage. Further, the reference rotor currents (positive, negative, fifth, and seventh sequence) are compared with the actual rotor currents using a PI controller to retain sinusoidal stator and grid currents. The proposed scheme's efficacy is validated with PSCAD/EMTDC simulations and using OPAL‐RT OP4510 real‐time simulator, on a 2.3 kVA DFIG. [ABSTRACT FROM AUTHOR]

Power quality issues caused by current harmonics from nonlinear and unbalanced loads are a growing concern. This paper presents a novel control strategy for four-wire shunt active power filters (SAPF) that surpasses existing conventional methods in mitigating harmonics and power factor correction. The strategy employs an improved synchronous detection method (SDM) enhanced by an adaptive linear neural network (ADALINE) trained using the least mean square (LMS) algorithm. This approach accurately estimates harmonic frequencies, enabling the SAPF to generate precise compensation currents. The effectiveness of the proposed method is validated through MATLAB-Simulink simulations under balanced supply conditions, encompassing diverse load scenarios. These simulation results are compared with those obtained using instantaneous power theory (IPT). They demonstrate the ability of the proposed method to achieve excellent harmonic identification and elimination, to comply with IEEE 519 harmonic limits, to ensure sinusoidal and balanced line currents, and to compensate for reactive power and neutral current. Furthermore, its simple architecture and noise robustness make it a promising solution for enhancing power quality. [ABSTRACT FROM AUTHOR]

The integration of renewable energy sources, particularly grid-tied solar photovoltaic (PV) systems, into the modern power grid has become increasingly prevalent. However, ensuring the reliable and efficient operation of grid-tied PV systems under various grid conditions, including fault scenarios, poses a significant challenge. In the event of grid faults or disturbances, traditional control methods often fall short in maintaining stable and reliable operation. This paper introduces a multi-layer neural network (MLNN) based MPPT controller that adapts intelligently to grid fault conditions, mitigating the impact on the grid-tied PV system's performance and providing low voltage ride through (LVRT). The research employs a detailed simulation framework on MATLAB to validate the effectiveness of the proposed controller under fault conditions. The LVRT capability of the designed system was analyzed and validated according to Indian grid code. The proposed controller leverages its capacity to learn and make real-time decisions to optimize the active and reactive power outputs of the PV system as per the grid code. Simulation results demonstrate that the proposed controller not only improves the fault tolerance of grid-tied PV systems but also enhances their performance, ensuring a stable and continuous power supply in the face of grid disturbances. [ABSTRACT FROM AUTHOR]

The fiber-optical current transformer (FOCT) is the core measuring equipment of the flexible DC converter station, which affects the operation control of the system. In order to solve the problem of the influence of the abnormal FOCT on the operation of the converter valve being unclear, the common fault modes of temperature and optical path of the FOCT are analyzed in this paper. Then, based on the traditional optical current transformer (OCT) model and considering the influence of temperature parameters on the FOCT, the FOCT dynamic model considering multiple factors is constructed. Finally, the simulation analysis is carried out on the MATLAB 2021b/Simulink platform, and the results show that (1) when the FOCT temperature compensation is abnormal, the transmission power of the converter valve increases with the increase in temperature, but the increase in temperature change is small; (2) when the FOCT light source compensation is abnormal, the light source attenuates, the converter valve active power decreases, and the reactive power increases; and (3) when the optical fiber sensing ring is broken, the transmission power increases and seriously deviates from the preset value (the active power increases by about 87.5% and the reactive power increases by about 90%). It can be seen that the abnormal FOCT in the converter station has a serious influence on the operation of the converter valve. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the impedance of each line of the parallel system of the wind–solar–storage virtual synchronous machine (VSG) is inconsistent, resulting in the power circulation between the parallel VSG, a multi-parameter collaborative adaptive control strategy for the parallel virtual synchronizers of a wind–solar–storage microgrid based on a neural network was proposed. Firstly, the topology of the virtual synchronous machine parallel system of the wind–solar–storage microgrid was built, and the VSG was analyzed. Then, the neural network algorithm was used to realize the adaptive adjustment of each parameter of VSG, which improves the uneven power distribution and the influence of circulation. Next, the parameters of multiple parallel VSG control systems were configured. Finally, MATLAB2021a/Simulink was used to model the system, and the VSG capacity under different scale conditions was simulated and analyzed. The simulation results show that when the capacity ratio of VSG1 and VSG2 is 1:1, the active power output is 9000 W, and the reactive power output is 7500 Var, which realizes accurate distribution, and when the capacity ratio of VSG1 and VSG2 is 2:1, the output values of active power and reactive power are 12,000 W/6000 W and 10,000 Var/5000 Var, and the output is carried out according to the ratio of 2:1, which shows that the control strategy can effectively improve the power allocation accuracy, suppressing circulation. [ABSTRACT FROM AUTHOR]

With the ongoing integration of renewable energy and energy storage into the power grid, the voltage safety issue has become a significant challenge for the distribution power system. Therefore, this study proposes a coordinated operation for energy storage systems with reactive power compensators. Taking into account the benefits of energy storage equipped with reactive power compensators and the market clearing process, a bi-level optimization model is formulated. In the proposed model, the upper-level model formulates the bidding strategy for energy storage and aims at maximizing the energy storage revenue; the lower-level model carries out a market-clearing process that takes into account various constraints for ensuring the safe operation of the grid. Afterward, by applying several math tricks such as the KKT optimality condition, the strong duality theorem, and the big M method, the bi-level equilibrium programming problem is transformed into an equivalent and tractable single-level mixed-integer linear programming problem. The results show that the coordinated operation of energy storage and reactive power compensators increases the benefit of energy storage by 3.47%. The benefit increment and security improvement brought by the collaborative operation of energy storage and reactive power compensators are verified. [ABSTRACT FROM AUTHOR]

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The aim of this paper is to present a new improved grey wolf optimizer (IGWO) to solve the optimal reactive power dispatch (ORPD) problem with and without penetration of renewable energy resources (RERs). It is a nonlinear multivariable problem of optimization, with multiconstraints. The purpose is to minimize real power losses and improve the voltage profile of a given electric system by adjusting control variables, such as generator voltages, tap ratios of a transformer, switching VAr sources, without violating technical constraints that are presented as equalities and inequalities. Methodology. Metaheuristics are stochastic algorithms that can be applied to solve a wide variety of optimization problems without needing specific problem structure information. The penetration of RERs into electric power networks has been increased considerably to reduce the dependence of conventional energy resources, reducing the generation cost and greenhouse emissions. It is essential to include these sources in power flow studies. The wind and photovoltaic based systems are the most applied technologies in electrical systems compared to other technologies of RERs. Moreover, grey wolf optimizer (GWO) is a powerful metaheuristic algorithm that can be used to solve optimization problems. It is inspired from the social hierarchy and hunting behavior of grey wolves in the wild. The novelty. This paper presents an IGWO to solve the ORPD problem in presence of RERs. Methods. The IGWO based on enhancing the exploitation phase of the conventional GWO. The robustness of the method is tested on the IEEE 30 bus test system. For the control variables, a mixed representation (continuous/discrete), is proposed. The obtained results demonstrate the effectiveness of the introduced improvement and ability of the proposed algorithm for finding better solutions compared to other presented methods. [ABSTRACT FROM AUTHOR]

In the article the reactive power of an asynchronous machine (AM) in a stable mode is obtained as a function of three variables: the angular speed of rotation of the AM shaft, the module of the rotor flux coupling and the moment of static load on the shaft. The AM power factor decreases in electric drives (ED) of industrial mechanisms in which the load moment while maintaining its direction of action can take a static value less than the nominal value. Therefore, in order to ensure a high power factor of an asynchronous ED in long-term operating modes with a variable load, a vector AM control system was created, in which the magnitude of the rotor flux coupling is regulated by the reactive power channel as a function of the moment of static load on the shaft. To identify the moment of loading, as well as the angular speed of the rotor and its flux coupling, a Kalman observer is synthesized, which allows creating a vector control system with simultaneous regulation of the speed and power factor of the AM without physical sensors of the reference vector of the rotor flux coupling and its angular speed of rotation. The significant dependence of the extreme values of the rotor flux coupling for reactive power on the torque on the AM shaft and insignificant dependence on the speed has been proved. Stability and high control quality are achieved by simultaneous use of relay control laws, invariant to coordinate and parametric perturbations, and the effectiveness of the Kalman filter algorithm for identifying variable states in the feedback loop. Thus, the article theoretically substantiates the idea of creating a sensorless relay-vector control system for an asynchronous ED with simultaneous speed regulation and optimization of AM energy indicators. The mathematical model is created as a program written in the Matlab programming language. The operability of the proposed asynchronous ED control system was confirmed by the method of mathematical modeling. [ABSTRACT FROM AUTHOR]

The modes of reactive power compensation in the power supply system powered by a synchronous generator through a cascade of intermediate transformers have been studied. It is shown that the reactive component of the common complex resistance of the generator and the power transmission path can cause relatively large levels of reactive power in the system. Experiments show that this power remains in the system even after the application of transverse capacitive compensation, which is not able to provide full compensation of reactive power in a power supply system with a cascade of transformers. Under these conditions, the optimal value of the capacitance of the transverse compensation capacitor was found using the search optimization method on the computer model. The results of the study show the possibility of achieving the mode of full compensation of reactive power due to a relatively small increase in the capacity of the compensating capacitor, which provides transverse compensation. [ABSTRACT FROM AUTHOR]

When a large number of distributed photovoltaic (PV) systems are integrated into the distribution network, power flow becomes bidirectionally fluctuating, resulting in variable line losses. In the scenario of reverse flow, the increase in line loss is particularly significant. The bidirectional reactive power regulation of photovoltaic inverters is an effective approach to reduce losses in the distribution network. However, despite the benefits of reducing losses, reactive power regulation by photovoltaic inverters also incurs additional costs. Therefore, there is a need for research into a comprehensive benefit optimization method for inverters participation in reducing reactive power losses in distribution networks. Firstly, the cost quantification models for the investment, transformation, operation, and lifespan loss of the photovoltaic inverters involved in reactive power loss reduction are established. Secondly, the benefit quantification models for loss reduction and power factor improvement are developed. Thirdly, considering various operational scenarios of both photovoltaic systems and loads, a comprehensive benefit optimization method for photovoltaic inverters participating in reactive power loss reduction in distribution networks is proposed. Finally, through example analysis, the cost and benefit are calculated and fitted in different scenarios, and the optimization calculation is carried out. Compared to the scenario where the photovoltaic inverter operates at the maximum reactive power regulation capacity, the optimized comprehensive benefit is increased by 21.20%. The proposed method is validated to effectively enhance the comprehensive benefits of inverters participation in reactive power loss reduction. [ABSTRACT FROM AUTHOR]

In this paper, an improved voltage control strategy for microgrids (MG) is proposed, using an artificial neural network (ANN)-based adaptive proportional-integral (PI) controller combined with droop control and virtual impedance techniques (VIT). The control strategy is developed to improve voltage control, power sharing and total harmonic distortion (THD) reduction in the MG systems with renewable and distributed generation (DG) sources. The VIT is used to decouple active and reactive power, reduce negative power interactions between DG's and improve the robustness of the system under varying load and generation conditions. Simulation findings under different tests have shown significant improvements in performance and computational simulation. The rise time is reduced by 60%, the overshoot is reduced by 80%, the THD of the voltage is reduced by 75% (from 0.99 to 0.20%), and the THD of the current is reduced by 69% (from 10.73 to 3.36%) compared to the conventional PI controller technique. Furthermore, voltage and current THD values were maintained below the IEEE-519 standard limits of 5% and 8%, respectively, for the power quality enhancement. Fluctuations in voltage and frequency were also maintained at 2% tolerance and 1% tolerance, respectively, across all voltage limits, which is consistent with international norms. Power-sharing errors were reduced by 50% after conducting the robustness tests against the DC supply and load disturbances. In addition, the proposed strategy outperforms the previous control techniques presented at the state of the art in terms of adaptability, stability and, especially, the ability to reduce the THD, which validates its effectiveness for MG systems control and optimization under uncertain conditions. [ABSTRACT FROM AUTHOR]

An analytical equation for limiting the minimum reactive power of a salient-pole generator according to the condition of ensuring static stability for a given safety factor, current active power and voltage is obtained. Overall, group reactive power controllers have proven to be a highly effective solution for controlling reactive power in power systems. They offer several advantages over traditional individual controllers, including increased system stability, reduced losses, and reduced costs. When designing and deploying these controllers, it is important to consider factors such as system topology, load characteristics, and more. Overall, group reactive power controllers represent a promising technology for improving the efficiency and reliability of power systems, and further research and development in this area is needed. (provided to the authors on August 27, 2024 for printing in IJHE from the archive of Fermaltech Montenegro Limited, made by A.L. Gusev using Designer. On the DALL E 3 platform.). [Display omitted] [ABSTRACT FROM AUTHOR]

This paper investigates on dynamic topology reconfiguration of distribution networks to enhance PV hosting capacity. Firstly, a dynamic topology reconfiguration model of distribution networks considering N-1 security constraints is proposed to accommodate intermittent PV generation, and thus high penetration of renewable resources can be ensured to satisfy operational requirements under both normal and fault conditions with load transfer of feeders. Then, a hosting capacity enhancement strategy is presented to decrease risks of voltage and line overloading with reactive power flexibility of energy storage inverters, and is implemented to enhance the maximum hosting capacity of distributed renewable energy sources. Finally, simulation results have validated the effectiveness of the proposed method for PV hosting capacity enhancement of distribution networks. [ABSTRACT FROM AUTHOR]

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

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

The diffusion of offshore wind power plants (OWPPs), useful to fulfil renewable diffusion policy targets, implies several technological challenges for integration in power transmission network. The definition of the OWPP connection to the transmission network affects possible exploitation of the assets, involves an evaluation of active power losses and loadability and points out the need for compensation devices, in order to comply with connection rules fixed by the grid operator. This paper proposes a methodology to determine the most suitable electric connection for an OWPP based on high‐voltage alternating current (HVAC) cables, for providing indications for transmission system operators. In particular, different HVAC connection schemes for OWPPs are analysed, focusing on new 66 kV standard voltage and high‐voltage levels, providing technical insight on transmission cable optimal operation conditions. An economic analysis is carried out by proper estimation of construction costs and production forecast, accounting for active power losses and reliability impact. The most suitable connection solution depending on OWPP size and distance in Italian framework is evaluated by means of synthetic techno‐economic indicators, further analysing possible sensitivities of energy price and capacity factor. [ABSTRACT FROM AUTHOR]

Aiming at the load fluctuation problem caused by a high proportion of new energy grid connections, a reactive power optimization method based on deep reinforcement learning (DRL) considering topological characteristics is proposed. The proposed method transforms the reactive power optimization problem into a Markov decision process and models and solves it through the deep reinforcement learning framework. The Dueling Double Deep Q-Network (D3QN) algorithm is adopted to improve the accuracy and efficiency of calculation. Aiming at the problem that deep reinforcement learning algorithms are difficult to simulate the topological characteristics of power flow, the Graph Convolutional Dueling Double Deep Q-Network (GCD3QN) algorithm is proposed. The graph convolutional neural network (GCN) is integrated into the D3QN model, and the information aggregation of topological nodes is realized through the graph convolution operator, which solves the calculation problem of deep learning algorithms in non-European space and improves the accuracy of reactive power optimization. The IEEE standard node system is used for simulation analysis, and the effectiveness of the proposed method is verified. [ABSTRACT FROM AUTHOR]

The integration of electrolyzers and fuel cells can cause voltage fluctuations within microgrids if not properly scheduled. Therefore, controlling voltage and reactive power becomes crucial to mitigate the impact of fluctuating voltage levels, ensuring system stability and preventing damage to equipment. This paper, therefore, seeks to enhance voltage and reactive power control within reconfigurable microgrids in the presence of innovative power-to-hydrogen technologies via electrolyzers and hydrogen-to-power through fuel cells. Specifically, it focuses on the simultaneous coordination of an electrolyzer, hydrogen storage, and a fuel cell alongside on-load tap changers, smart photovoltaic inverters, renewable energy sources, diesel generators, and electric vehicle aggregation within the microgrid system. Additionally, dynamic network reconfiguration is employed to enhance microgrid flexibility and improve the overall system adaptability. Given the inherent unpredictability linked to resources, the unscented transformation method is employed to account for these uncertainties in the proposed voltage and reactive power management. Finally, the model is formulated as a convex optimization problem and is solved through GUROBI version 11, which leads to having a time-efficient model with high accuracy. To assess the effectiveness of the model, it is eventually examined on a modified 33-bus microgrid in several cases. Through the results of the under-study microgrid, the developed model is a great remedy for the simultaneous operation of diverse resources in reconfigurable microgrids with a flatter voltage profile across the microgrid. [ABSTRACT FROM AUTHOR]

After the large-scale access of distributed power sources to the distribution network, significant high/low voltage problems have emerged. Using a virtual power plant to provide reactive power voltage regulation as an ancillary service effectively addresses voltage issues. However, since a third party manages the virtual power plant and contains both discrete and continuous regulation devices internally, there is a need to consider privacy protection. To address this, a training method that requires minimal boundary information and reward–penalty information for interaction between discrete and continuous action agents is proposed. This method uses distributed two-layer multi-agent deep reinforcement learning for the virtual power plant's reactive power voltage support strategy. By utilizing actual engineering data and comparing it with the "centralized training" framework algorithm, this study proves the effectiveness of the deep reinforcement learning training method and reactive power voltage control strategy. It demonstrates advantages such as protecting the privacy of the virtual power plant and low training difficulty. [ABSTRACT FROM AUTHOR]