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Voltage instability in power systems arises due to the shortage of reactive power and may cause abnormally low bus voltages leading to a partial or complete blackout. In order to maintain the system voltages within a safe limit, voltage control techniques such as shunt capacitor banks, Static VAR Compensators (SVCs), load shedding, and transformer tap-changer blocking, are employed. In this paper, a novel receding-horizon Model Predictive Control (MPC)-based voltage controller is proposed, which, by optimally controlling generator reactive power and SVC output, maintains the voltage stability of a power system. For this, a sensitivity-based analysis is performed to design a state-space model of the power system. The frequency and voltage dependency of load and generation are considered in the system equations. The voltage control is done step-wise, and the optimal control action in each step is calculated by minimizing a cost function subject to a set of relevant constraints. Different Voltage Stability Indices (VSIs) are used as a measure of voltage stability and also used in the constraints for the optimization problem. The performance of the proposed controller is evaluated on IEEE 9-, 39- and 118-bus systems, considering different types of loads and contingencies. [ABSTRACT FROM AUTHOR]

This paper investigates an optimal methodology for mitigating low-frequency oscillation concerns in power systems. The study explores the synergistic integration of a power system stabilizer (PSS) and a flexible alternating current transmission system (FACTS) to formulate an intelligent controller. A comprehensive analysis encompasses various PSS design strategies, including lead-lag (LL), proportional-derivative-integral (PID), and fractional-order proportional-integral-derivative (FOPID) controllers. The FACTS device selected for this investigation is a static VAR compensator (SVC), highlighting the exceptional efficacy of FOPID-based PSS over alternative strategies with a power oscillation damper. The study extends its scope to encompass a comparative assessment of two distinct optimization algorithms: the moth flame optimization (MFO) and the antlion optimization (ALO). The research is conducted using a single-machine infinite bus power system (SMIB) as the case study platform. A total of four diverse test scenarios are executed under varying operating conditions. The evaluation of the developed method employs six distinct performance indices to investigate the developed controller thoroughly. The outcomes reveal that the MFO-optimized FOPID-PSS and SVC controller outperforms other control schemes. This optimized configuration demonstrates substantial improvements across all performance indices. These findings underscore the superior capabilities of the proposed approach in enhancing power system stability and performance. [ABSTRACT FROM AUTHOR]

In this article, an event-triggered finite-time neural control strategy is proposed for nonlinear power systems with unknown disturbances and static var compensator (SVC). We first transform the power system with SVC into a three-dimensional uncertain nonlinear system and then extend it to an n -dimensional uncertain nonlinear system. The disturbance observer is established to estimate external disturbances and the unknown nonlinear terms are approximated by the radial basis function neural networks. Moreover, to avoid the complexity explosion problem in the traditional backstepping method, the command filtering technique is adopted, and the error caused by the command filters is compensated. The adaptive event-triggered finite-time controller ensures that all signals are bounded in finite time and excludes Zeno phenomena. In the end, the simulation for the two-area interconnected power system with SVC is presented to verify the availability and feasibility of the proposed approach. [ABSTRACT FROM AUTHOR]

The new power system effectively integrates a large number of distributed renewable energy sources, such as solar photovoltaic, wind energy, small hydropower, and biomass energy. This significantly reduces the reliance on fossil fuels and enhances the sustainability and environmental friendliness of energy supply. Compared to distribution networks in traditional power systems, the new-generation distribution network offers notable advantages in improving energy efficiency, reliability, environmental protection, and system flexibility, but it also faces a series of new challenges. These challenges include potential harmonic issues introduced by the widespread use of power electronic devices (such as inverters for renewable energy generation systems and electric vehicle charging stations) and the voltage fluctuations and flickering caused by the intermittency and uncertainty of renewable energy generation, which may affect the normal operation of electrical equipment. To address these challenges, this study proposes an optimization model aimed at minimizing network losses and voltage deviations, utilizing traditional capacitor adjustments and static var compensators (SVCs) as optimization measures. Furthermore, this study introduces an improved version of the multi-objective particle swarm optimization (MOPSO) algorithm, specifically enhanced to address the unique challenges of reactive power optimization in modern distribution networks. The test results show that this algorithm can effectively generate a large number of Pareto optimal solutions. The application of this algorithm on a 33-node network case study demonstrates its advantages in reactive power optimization. The optimization results highlight the effectiveness and feasibility of the proposed improved algorithm in the application of distribution network reactive power optimization, offering users a uniform and diverse range of reactive compensation solutions. [ABSTRACT FROM AUTHOR]

This paper proposes a novel methodology to improve stability in a transmission system under critical conditions of operation when additional loads that take the system to the verge of stability are placed in weak bus bars according to the fast voltage stability index (FVSI). This paper employs the Newton–Raphson method to calculate power flows accurately and, based on that information, correctly calculate the FVSI for every transmission line. First, the weakest transmission line is identified by considering N − 1 contingencies for the disconnection of transmission lines, and then all weak nodes associated with this transmission line are identified. Following this, critical scenarios generated by stochastically placed loads that will take the system to the verge of instability will be placed on the identified weak nodes. Then, the methodology will optimally size and place a single static VAR compensator SVC in the system to take the transmission system to the conditions before the additional loads are connected. Finally, the methodology will be validated by testing the system for critical contingencies when any transmission line associated with the weak nodes is disconnected. As a result, this paper's methodology found a single SVC that will improve the system's stability and voltage profiles to similar values when the additional loads are not connected and even before contingencies occur. The methodology is validated on three transmission systems: IEEE 14, 30, and 118 bus bars. [ABSTRACT FROM AUTHOR]

The paper presents a ground fault location algorithm (GFLA) in double‐circuit transmission lines (DCTL) with a T‐off connection to an industrial microgrid (IMG) containing electric arc furnaces (EAF), renewable distributed generations (RDG), and static VAR compensator (SVC). The design presented utilizes the information on the current and voltage phasors of one side of the transmission lines (TL) during the fault period, and there is no need for the availability of information on the type of faulty phase(s) and even the faulty section. To find the exact location of the fault in this design, the voltage phasor equations governing the fault point in positive, negative, and zero‐sequence (PNZS) domains, the zero‐sequence current (ZSC) equation of the fault point, and the boundary condition equation of the fault point have been used. The simulation system is implemented in Simulink/MATLAB using accurate modelling of all network components. The algorithm has been tested and evaluated in different fault conditions, including various locations, phase types, phase‐to‐ground connection resistance, occurrence time, and microgrid (MG) operation modes. The successful results of various tests of the proposed design as well as the analysis of various sensitivities confirm the satisfying performance of the suggested algorithm. [ABSTRACT FROM AUTHOR]

Flexible alternating current transmission systems (FACTSs) have been widely incorporated in electric power systems in order to control system parameters. This paper proposes the modeling of four FACTS devices, using the Branch Flow Model (BF) as an optimization problem to reduce the complexity of the Newton–Raphson (NR) load flow code with FACTS devices. The devices are represented as variable impedances, as a function of a firing angle, and as voltage source converters (VSCs) located on the buses and transmission lines. This proposed model solves the problem associated with the selection of appropriate initial conditions of the parameters of each device that guarantee convergence. The model is validated by evaluating its percentage deviation with respect to the NR method, using the standard test systems, IEEE 5-bus, IEEE 14-bus, IEEE 30-bus, and IEEE 57-bus systems. [ABSTRACT FROM AUTHOR]

This paper presents new methodologies for modeling static VAr compensators (SVCs) in the power flow problem. The proposed formulations utilize sigmoid functions to model the control equations that describe the steady-state behavior of SVCs. The first methodology introduces reactive power injection as a new state variable, while the second methodology utilizes the thyristor firing angle. These steady-state SVC methodologies were applied to the power flow problem using the full Newton formulation, which incorporates the control equations into the system of nonlinear equations. One of the main contributions of these proposed methodologies is that they eliminate the need for alternating adjustments concerning the operational limits of the SVC during the iterative power flow process. The implementation of a power flow program was tested on both small-scale tutorial systems and the medium-scale IEEE Nordic system. The presented results validate and demonstrate the effectiveness of the proposed methodology. [ABSTRACT FROM AUTHOR]

The importance of flexible alternating current transmission system (FACTS) devices is increasing day by day as they provide compensation for power systems. The installation of such devices solves many issues regarding the stability and power transferability of power systems. However, for optimizing the performance of FACTS devices, the location and sizes of FACTS devices must be selected very carefully. On the other side, the utilization of optimization techniques is increasing daily, as it is capable of solving nonlinear, random problems by its stochastic nature. As a result, it became a reliable tactic for solving stochastic problems almost in every aspect of our lives. Therefore, it is adopted for solving power system problems, like, FACTS devices allocation, distributed generators allocation, determining component's parameters, and more. In this paper, the optimal size and location of several FACTS devices are selected to achieve the following single objective functions separately: fuel cost minimization and power losses minimization, then combining the mentioned objective function into one multiobjective function for gross cost minimization. The power system optimized is the Institute of Electrical and Electronics Engineers 30‐bus standard system, and the FACTS devices installed are static VAR compensator, thyristor control series compensator, and thyristor‐controlled phase shifter, while the optimization is performed using different conventional and recent optimization algorithms, including a newly developed algorithm, typically Leader Walrus Optimization Algorithm "LWaOA," making a comparison among such algorithms to investigate the algorithm that possesses the best performance. The results of the optimization processes show the superiority of LWaOA. [ABSTRACT FROM AUTHOR]

This study aimed to optimize the incorporation of static var compensators (SVCs) into Oman's main interconnected system (MIS) using real 2023 MIS data. Leveraging the particle swarm optimization (PSO) algorithm within MATLAB, substantial enhancements were achieved in voltage profiles, with associated losses reducing by roughly 2%. A multi-objective strategy effectively managed costs while preserving improved voltage profiles and controlled losses. Validation through DigSILENT showcased the dynamic advantages of optimal SVC placement through consistently elevating voltage profiles and mitigating losses, notably within the Muscat region. Analyses encompassing harmonics, transient stability, and load distribution indicated that harmonics remained within acceptable thresholds, and overall system stability was enhanced. Optimal SVC deployment expedited the attainment of steady-state conditions, as illustrated via the QV curve, demonstrating increased stability as the buses loaded from 18% to 96%. These findings underscore the robust and efficient nature of SVC integration as a viable solution within Oman's MIS system, addressing voltage profile enhancement, loss minimization, and fortified system stability. [ABSTRACT FROM AUTHOR]

This study presents a low-cost thyristor-controlled LC compensator scheme for the improvement of overall power quality in the distribution system. The parameters of the compensator have been designed and optimal triggering angles for thyristor switching have been obtained for reducing the unbalanced condition and harmonic injection at a high power factor. Compared to the traditional static VAr compensator schemes, the proposed technique can significantly reduce the harmonic injection into the system. The particle swarm optimization technique has been applied to compute the optimal triggering angles, and different aspects of the power quality factor have been assessed through rigorous simulations. Power quality assessment has been further validated through an experimental setup in the laboratory. Finally, a comparison of the proposed scheme with other similar schemes has been carried out to highlight its efficacy. [ABSTRACT FROM AUTHOR]

Summary: This paper utilizes a static var compensator in coordination with an intelligent online controller, to enhance the oscillation damping of the power system at various operating conditions and communication delays. For system identification, a linear identifier is used that ensures a low computational burden and facilitates its real‐time implementation. This identifier accurately estimates the system's local linear model using local measurements and continuously updates its parameters in real time to account for system's changing operational states. The learning rate of the identifier is also adaptively adjusted such that the stability of the learning algorithm and optimal speed of convergence are guaranteed. The location of the controller is selected based upon the controllability and bus voltage participation factors, and an effective feedback signal is obtained using the observability. An empirical expression has also been proposed to offset the effects of communication time delays caused due to use of wide‐area signals. Time‐domain simulations are performed on single‐ and multi‐machine power systems to check the efficacy of the proposed intelligent controller. The performance of the controller is compared with the residue‐based conventional controller and also with the recently proposed wide‐area damping controller. [ABSTRACT FROM AUTHOR]

This article presents the comparison of 3D and 2D finite element models of a power transformer designed for reactive power compensation stations. There is a lack of studies in the literature on internal electromagnetic phenomena in the active part of a transformer operated in these conditions. The results of numerical 2D and 3D calculations of no-load current and losses in the transformer core were obtained by using various methods and models. The impact of considering the hysteresis loop phenomenon on the calculation of core losses was investigated by using the Jiles–Atherton core losses model. The results obtained in the paper show that the model of the core must contain the areas representing the influence of overlappings on the no-load current and also on the flux density field in the core. The capacitive load of the transformer increases the flux density in the core limbs by several percent, so the power losses there must also increase accordingly. As a summary of the research, differences in the values of losses in each core element between the capacitive load and no-load conditions are presented. The results presented in this paper indicate that considering nonlinearity related to the magnetic hysteresis loop has a significant impact on the calculation of the core losses of power transformers. [ABSTRACT FROM AUTHOR]

This work focuses on the use of the Linear Quadratic Gaussian (LQG) technique to construct a reliable Static VAr Compensator (SVC), Thyristor Controlled Series Compensator (TCSC), and Excitation System controller for damping Subsynchronous Resonance (SSR) in a power system. There is only one quantifiable feedback signal used by the controller (generator speed deviation). It is also possible to purchase this controller in a reduced-order form. The findings of the robust control are contrasted with those of the "idealistic" full state optimal control. The LQG damping controller's regulator robustness is then strengthened by the application of Loop Transfer Recovery (LTR). Nonlinear power system simulation is used to confirm the resilience of the planned controller and demonstrates how well the regulator dampens power system oscillations. The approach dampens all torsional oscillatory modes quickly while maintaining appropriate control actions, according to simulation results. [ABSTRACT FROM AUTHOR]

Reducing carbon emissions is a crucial way to achieve the goal of green and sustainable development. To accomplish this goal, electric vehicles (EVs) are considered system‐schedulable energy storage devices, suppressing the negative impact of the randomness and fluctuation of renewable energy on the system's operation. In this paper, a coordination control strategy aimed at minimising the carbon emissions of a distribution network between EVs, energy storage devices, and static var compensators (SVCs) is proposed. A model‐free deep reinforcement learning (DRL)‐based approach is developed to learn the optimal control strategy with the constraint of avoiding system overload caused by random EV access. The twin‐delayed deep deterministic policy gradient (TD3) framework is applied to design the learning method. After the model learning is completed, the neural network can quickly generate a real‐time low‐carbon scheduling strategy according to the system operating situation. Finally, simulation on the IEEE 33‐bus system verifies the effectiveness and robustness of this method. On the premise of meeting the charging demand of electric vehicles, this method can optimise the system operation by controlling the charge‐discharge process of EVs, effectively absorbing the renewable energy in the system and reducing the carbon emissions of the system operation. [ABSTRACT FROM AUTHOR]

The problem regarding the optimal placement and sizing of different FACTS (flexible alternating current transmission systems) in electrical distribution networks is addressed in this research by applying a master–slave optimization approach. The FACTS analyzed correspond to the unified power flow controller (UPFC), the thyristor-controlled shunt compensator (TCSC, also known as the thyristor switched capacitor, or TSC), and the static var compensator (SVC). The master stage is entrusted with defining the location and size of each FACTS device using hybrid discrete-continuous codification through the application of the black widow optimization (BWO) approach. The slave stage corresponds to the successive approximations power flow method based on the admittance grid formulation, which allows determining the expected costs of the energy losses for a one-year operation period. The numerical results in the IEEE 33-, 69-, and 85-bus grids demonstrate that the best FACTS device for locating in distribution networks is the SVC, given that, when compared to the UPFC and the TCSC, it allows for the best possible reduction in the equivalent annual investment and operating cost. A comparative analysis with the General Algebraic Modeling System software, with the aim to solve the exact mixed-integer nonlinear programming model, demonstrated the proposed BWO approach's effectiveness in determining the best location and size for the FACTS in radial distribution networks. Reductions of about 12.63 % and 13.97 % concerning the benchmark cases confirmed that the SVC is the best option for reactive power compensation in distribution grids. [ABSTRACT FROM AUTHOR]

An electrical power system (EPS) is subject to unexpected events that might cause the outage of elements such as transformers, generators, and transmission lines. For this reason, the EPS should be able to withstand the failure of one of these elements without changing its operational characteristics; this operativity functionality is called N − 1 contingency. This paper proposes a methodology for the optimal location and sizing of a parallel static Var compensator (SVC) in an EPS to reestablish the stability conditions of the system before N − 1 contingencies take place. The system's stability is analyzed using the fast voltage stability index (FVSI) criterion, and the optimal SVC is determined by also considering the lowest possible cost. This research considers N − 1 contingencies involving the disconnection of transmission lines. Then, the methodology analyzes every scenario in which a transmission line is disconnected. For every one of them, the algorithm finds the weakest transmission line by comparing FVSI values (the higher the FVSI, the closer the transmission line is to instability); afterward, when the weakest line is selected, by brute force, an SVC with values of 5 Mvar to 100 Mvars in steps of 5 Mvar is applied to the sending bus bar of this transmission line. Then, the SVC value capable of reestablishing each line's FVSI to its pre-contingency value while also reestablishing each bus-bar's voltage profile and having the lowest cost is selected as the optimal solution. The proposed methodology was tested on IEEE 14, 30, and 118 bus bars as case studies and was capable of reestablishing the FVSI in each contingency to its value prior to the outage, which indicates that the algorithm performs with 100% accuracy. Additionally, voltage profiles were also reestablished to their pre-contingency values, and in some cases, they were even higher than the original values. Finally, these results were achieved with a single solution for a unique SVC located in one bus bar that is capable of reestablishing operational conditions under all possible contingency scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to find the optimal location of the shunt connected Flexible AC Transmission Systems (FACTS) such as Static Var Compensator (SVC) or Static Synchronous Compensator (STATCOM) to the power system for regulating voltage levels of all buses. Three indices include Voltage Drop Index (VDI), Total Voltage Drop Index (TVDI), and Total Voltage Drop of Network Index (TVDNI) are presented to find the location of the SVC. Also, to minimize the solution space, a ranking list will be established. For the case studies, the IEEE 14-bus test system is selected, and an SVC is located in the system. Simulations are done in two cases: network loads increase with constant coefficient and randomly. According to simulation results in both cases, the proposed method can identify the optimal placement of SVC, and the voltage drop due to increasing the load will be compensated. For the IEEE 14-bus test system, the optimal location of the SVC is bus 9. Variable loads are considered for 24 h, and SVC is installed at bus 9 to validate the introduced method. Results show the voltage level for all buses is compensated so that the voltage levels are higher than the minimum voltage level, i.e. 95%. [ABSTRACT FROM AUTHOR]

The supply of growing electricity demand is possible through continuous technological advances and the expansion of national and international electrical systems. This scenario could introduce voltage drops and consequent changes in the reactive power flow throughout the electrical network. In order to control these problems, various strategies have been developed as a solution to improve the transport and distribution of electrical energy. One of them is the Flexible Alternating Current Transmission System (FACTS), and more specifically the STATic synchronous COMpensator (STATCOM). This paper investigates the influence and effectiveness of STATCOM to mitigate the losses in the transmission lines and its impacts on bus voltage drops. The simulations are performed using the software DIgSILENT PowerFactory and the results showed that STATCOM reduces the power system losses in an interval of 23.86% until 32.86%, and in addition, the STATCOM decreases the annual energy cost by 7.82% in the implemented test case. [ABSTRACT FROM AUTHOR]

Given the concern for maintaining voltage stability in power systems integrated with renewable power systems due to a mismatch in generation and demand, there remains a need to invoke flexible alternating current transmission system (FACTS) devices in the distribution network. The present paper deals with identifying the locations of placement of a static var compensator in an experimental IEEE 14-bus system; the voltage drop in different buses in an IEEE 14-bus system is calculated by the standard formula. The total voltage drop in the network (TVDN) is also calculated as a reference. The ranking of buses in order of decreasing voltage drop is made, and the weak buses are identified as those showing the maximum or near-maximum voltage drop for the installation of a Static Var Compensator (SVC). The optimum usable size is calculated using a Genetic Algorithm approach to optimize the installation cost. After size optimization, installing a 2 MW solar generator is considered for the weak and most potential bus, which suffers from voltage drops or power loss. Based on the generator at the weakest bus, the total power loss in the network is calculated and compared with a similar method to assess the efficiency of the proposed model. Thus, the voltage stability enhancement problem is solved by applying a Genetic algorithm (GA) to optimize SVC size and using the Total Voltage Drop in Network (TVDN) method to identify weak buses in the systems. It is found that the performance of the proposed system is comparable with another existing system. It is further observed that a gain in power loss to 6.56% is achievable by adopting the proposed strategy, and the gain is better than the other system. [ABSTRACT FROM AUTHOR]

A gradient-based optimizer (GBO) is a recently inspired meta-heuristic technique centered on Newton's gradient-based approach. In this paper, an advanced developed version of the GBO is merged with a crossover operator (GBOC) to enhance the diversity of the created solutions. The merged crossover operator causes the solutions in the next generation to be more random. The proposed GBOC maintains the original Gradient Search Rule (GSR) and Local Escaping Operator (LEO). The GSR directs the search to potential areas and aids in its convergence to the optimal answer, while the LEO aids the searching process in avoiding local optima. The proposed GBOC technique is employed to optimally place and size the distribution static VAR compensator (D-SVC), one of the distribution flexible AC transmission devices (D-FACTS). It is developed to maximize the yearly energy savings via power losses concerning simultaneously different levels of the peak, average, and light loadings. Its relevance is tested on three distribution systems of IEEE 33, 69, and 118 nodes. Based on the proposed GBOC, the outputs of the D-SVCs are optimally varying with the loading level. Furthermore, their installed ratings are handled as an additional constraint relating to two compensation levels of 50% and 75% of the total reactive power load to reflect a financial installation limit. The simulation applications of the proposed GBOC declare great economic savings in yearly energy losses for the three distribution systems with increasing compensation levels and iterations compared to the initial case. In addition, the effectiveness of the proposed GBOC is demonstrated compared to several techniques, such as the original GBO, the salp swarm algorithm, the dwarf mongoose algorithm, differential evolution, and honey badger optimization. [ABSTRACT FROM AUTHOR]

FACTS tools in modern power systems provide a vital solution to the problems of voltage deviation and fault ride-through (FRT) capability in electrical power systems especially during the integration of wind power. Many distinct journals highlight that the wind-driven squirrel cage generator (SCIG) still accounts for around 15% of operating wind generators so far. To enhance voltage stability and FRT capacity, this paper recommends a cost-effective static VAR compensator (SVC) which has a size rating of six MVAR, and this improves the efficiency of the electrical power system. Different events are considered in this study such as high turbulent wind speed, low turbulent wind speed, unsymmetrical faults, and symmetrical faults to validate the suggested option. Moreover, the suggested solution is compared with the static synchronous compensator (STATCOM) and a fixed capacitor to ensure that during the studied wind speed profiles and faults, voltage stability, reactive power consumption, and FRT capability are realized. An overall comparison among them is performed under all studied scenarios to summarize their benefits and impacts. The simulated results show the effectiveness and superiority of SVC in improving the operation of an integrated wind system based on a grid-linked SCIG and the performance of the power system. The modeling of SCIG, SVC, and STATCOM is designed by MATLAB/Simulink toolbox. [ABSTRACT FROM AUTHOR]

This paper proposes a new control strategy based on multimodel linear optimization control (MMLOC) to damp power system low-frequency oscillations (LFO) faster. The multimodel control strategy is used to anticipate synchronous generator dynamic behavior and linear optimization control for generating a control signal uncomplicatedly. The third-order model of synchronous machine is considered for each of the models. The probability of each model's validity is evaluated from the difference between model outputs and the same actual power system outputs via the Bayesian approach. To improve the postfault dynamics of the case study power system, which contains a static VAR compensator, a linear optimal controller (LOC) is designed. The 8th order model of the machines is used in simulations to represent the plant as accurately as possible. [ABSTRACT FROM AUTHOR]

Flexible Alternating Current Transmission Systems (FACTS) play a very prominent role in enhancing the performance of power system networks and in the quality up-gradation of power system by stabilizing the system parameters like voltage deviation, system security, power loss and system load-ability being a few to name. This work therefore handles two of the important performance parameters of a power system network namely power flow which is modeled as the System Load-ability (SL) and voltage profile which is represented as Voltage Stability Index (VSI). In this paper the maximization of VSI and SL of IEEE 30 Bus and 57 Bus networks have been exploited through the optimal placement of Thyristor Controlled Series Capacitor (TCSC), Static VAR Compensator (SVC) and Unified Power Flow Controller (UPFC) in the networks using the proposed and enhanced form of a recently developed meta-heuristic technique named as Salp Swarm Optimization (SSO). The outcomes of the simulations have been scrutinized with an established swarm-based optimization procedure. [ABSTRACT FROM AUTHOR]

This study presents a novel improved differential evolutionary (IDE) algorithm for optimizing reactive power management (RPM) problems. The effectiveness of IDE algorithm is tested on different unimodal and multimodal benchmark functions. The objective function of the RPM is considered as the minimization of active power losses. Initially, the power flow analysis approach is employed to detect the optimal position of flexible AC transmission system (FACTS) devices. The proposed method is used to determine the optimal value of control variables such as generator's reactive power generation, transformer tap settings, and reactive power sources. Furthermore, the efficacy of the IDE approach is compared with other promising optimization methods such as variants of differential evolution algorithm, moth flame optimization (MFO), brainstorm‐based optimization algorithm (BSOA), and particle swarm optimization (PSO) on various IEEE standard test bus (i.e., IEEE‐30, ‐57, ‐118, and ‐300) systems with active and reactive loading incorporating FACTS devices. A Static VAR compensator (SVC) for shunt compensation and a thyristor‐controlled series compensator (TCSC) for series compensation were used as FACTS devices. The proposed IDE method significantly reduces the active power loss, that is, 55.65% in IEEE 30, 39.68% in IEEE 57, 16.32% in IEEE 118, and 8.56% in IEEE 300 bus system at nominal loading. Finally, the statistical analysis such as Wilcoxon signed‐rank test (WSRT) and ANOVA test were thoroughly analysed to demonstrate the firmness and accuracy of the proposed technique. [ABSTRACT FROM AUTHOR]

Modern power systems need the expansion of EHV and UHV power Transmission networks due to the exponential rise in power demand. The Ferranti effect needs the attention of researchers on the dynamic variation of loads in interconnected power systems. This article focuses on the development of closed-loop control circuitry for both Static Synchronous Compensator (STATCOM) and Static Var Compensator (SVC). The developed transmission system Simulink model has been simulated and Ferranti Effect is observed for both no-load and lightly loaded conditions. The closed-loop control circuits along with power circuits of STATCOM and SVC have been developed and simulated and the results show the significant suppression of the Ferranti effect by both of the shunt devices. [ABSTRACT FROM AUTHOR]

The support vector machine (SVM) is a very important machine learning algorithm with state-of-the-art performance on many classification problems. However, on large datasets it is very slow and requires much memory. To solve this defficiency, we propose the fast support vector classifier (FSVC) that includes: 1) an efficient closed-form training free of any numerical iterative procedure; 2) a small collection of class prototypes that avoids to store in memory an excessive number of support vectors; and 3) a fast method that selects the spread of the radial basis function kernel directly from data, without classifier execution nor iterative hyper-parameter tuning. The memory requirements of FSVC are very low, spending in average only 6 $\cdot 10^{-7}$ · 10 - 7 sec. per pattern, input and class, and processing datasets up to 31 millions of patterns, 30,000 inputs and 131 classes in less than 1.5 hours (less than 3 hours with only 2GB of RAM). In average, the FSVC is 10 times faster, requires 12 times less memory and achieves 4.7 percent more performance than Liblinear, that fails on the 4 largest datasets by lack of memory, being 100 times faster and achieving only 6.7 percent less performance than Libsvm. The time spent by FSVC only depends on the dataset size and thus it can be accurately estimated for new datasets, while Libsvm or Liblinear are much slower on “difficult” datasets, even if they are small. The FSVC adjusts its requirements to the available memory, classifying large datasets in computers with limited memory. Code for the proposed algorithm in the Octave scientific programming language is provided.1 [ABSTRACT FROM AUTHOR]

The strategic intent of the African Union is to develop a "Smart Integrated African Electric Power Super Grid" driven by modern tools and advances in high-voltage direct current (HVDC) engineering and flexible alternating current technology systems (FACTS), which is central in supporting Africa's sustained economic growth and development. The southern African region, including South Africa, is beset by the critical challenges of perennial load-shedding, which impedes economic growth and aggravates unemployment. This has led to the insecurity of electricity supplies and degraded the quality of life. The parallel operation of high-voltage direct current (HVDC) and flexible AC technology systems (FACTS) controllers is gaining traction as system conditions become more complex, such as weak power networks which requires increased stability requirements, resulting in load-shedding and power outages. These adversely affect business productivity and adversely affect GDP and economic growth. Thus, the application of innovative technologies such as HVDC links can stabilize weak power systems. It is established that HVDC delivery systems reduce losses in long transmission lines transporting bulk power compared with high-voltage alternating current (HVAC) transmission lines for power wheeling. This paper evaluates the parallel operation of the Cahora Bassa 1414 km bipolar HVDC link and a weak parallel 400/330 kV alternating current (AC) link. It demonstrates the use of FACTS controllers to enhance the technical performance of an existing network, such as voltage control, and technical loss reduction. It combines an HVDC line commutated converter (LCC) and HVAC transmission lines, in hybrid notation to increase the voltage stability of the system by controlling the reactive power with a Static Var Compensator (SVC). These modern tools can increase the transmission power controllability and stability of the power network. In this study, HVDC–LCC was used with a setpoint of 1000 MW in conjunction with the 850 MVAr SVC. The results show that the technical losses were reduced by 0.24% from 84.32 MW to 60.32 MW as Apollo 275 kV SVC was utilized for voltage control. The network analysis was performed using DIgSILENT PowerFactory software that is manufactured by DIgSILENT GmbH at Gomaringen, Germany [ABSTRACT FROM AUTHOR]

Reliability and safety must be carefully considered in today's power systems, which are rapidly evolving toward ever higher penetration of renewable, inverter-based generation units. Power systems are constantly stressed by active power disturbances, which can be exacerbated by wind and solar systems that are subject to rapid fluctuations in primary energy. In this framework, a comparative technical analysis of solutions to improve transient stability, both rotor angle stability and frequency stability, is carried out. These solutions can be adopted by the transmission system operator (e.g., an additional parallel transmission line), by the generation companies (e.g., a fast excitation system), or by both, such as SVC (static VAR compensator) and STATCOM (static synchronous compensator). Sensitivity analyses were carried out to assess the impact of the location of the wind turbines in the buses of the grid on their rated power and level of production. On the basis of these analyses, the worst-case fault was considered, and the critical fault recovery time was determined as an engineering parameter to compare the different solutions. For the numerical analysis, a modified IEEE 9-bus system was considered, and the PowerWorld software tool was used. Rotor angle and frequency stability analyses were performed. [ABSTRACT FROM AUTHOR]

This article reports a relay algorithm based protection of static var compensator (SVC) based compensated transmission line utilizing artificial neural networks (ANN). The sequentially involved four artificial neural networks (ANNs) are used. The first ANN detects fault and the second ANN classifies it as either a ground or a phase fault. The faulted phases are then detected using ground fault ANN or phase fault ANN, depending on the situation. A transmission line (100 km, 230 kV, 50Hz) is simulated with SVC at the midpoint using a sampling frequency of 1 kHz in PSCAD/EMTDC. The sequence current ratios are used in fast protection algorithm with 100% accuracy in 4 milliseconds and identify them as phase or ground faults in 8 milliseconds. Finally, the identification of the faulted phase/phases requires just 13 milliseconds. Further, the number of thyristor-switched capacitors (TSC) in SVC depends on several factors such as thyristor valve, reactive power output, and electrical network type. However, the effect of the number of TSCs on the SVC reliability and criticality is not found in the existing literature. The reliability of SVC is increased is reported in this work by varying the number of TSC branches. The observations found increase of 15.47% in the SVC reliability by increasing TSC branches from one to three. In this way, the number of TSC branches in SVC can be optimized to increase the system's reliability with minimum cost. [ABSTRACT FROM AUTHOR]

The adoption of a DFIGs generator in a WECs is characterized by several advantages: robust and flexible system, energy generation in a wide operating range of wind turbines, simplicity of the control system and cost-efficient operation. Despite most DFIG control strategies discussed in literature refer to a nominal operating condition, a smooth startup procedure must be also envisioned to avoid high transient currents in the stator windings resulting from excessive mismatch between grid and open-stator voltages. Most DFIG control schemes rely on the integration of the stator voltage equation to estimate the stator flux vector for the needed d-q frame orientation. [Extracted from the article]

Developing control methods that have the ability to preserve the stability and optimum operation of a wind energy generation unit connected to power systems constitutes an essential area of recent research in power systems control. The present work investigates a novel control of a wind energy system connected to a power system through a static VAR compensator (SVC). This advanced control is constructed via integration between the model predictive control (MPC) and an artificial neural network (ANN) to collect all of their advantages. The conventional MPC needs a high computational effort, or it can cause difficulties in implementation. These difficulties can be eliminated by using Laguerre-based MPC (LMPC). The ANN has high performance in optimization and modeling, but it is limited in improving dynamic performance. Conversely, MPC operation improves dynamic performance. The integration between ANN and LMPC increases the ability of the Neuro-MPC (LMPC-ANN) control system to conduct smooth tracking, overshoot reduction, optimization, and modeling. The new control scheme has strong, robust properties. Additionally, it can be applied to uncertainties and disturbances which result from high levels of wind speed variation. For comparison purposes, the performance of the studied system is estimated at different levels of wind speed based on different strategies, which are ANN only, Conventional MPC strategy, MPC-LQG strategy, ANN- LQG strategy, and the proposed control. This comparison proved the superiority of the proposed controller (LMPC-ANN) for improving the dynamic response where it mitigates wind fluctuation effects while maintaining the power generated and generator terminal voltage at optimum values. [ABSTRACT FROM AUTHOR]

Today, Flexible AC Transmission Systems (FACTS) devices provide local reactive power support in load centers and keep bus voltages within safe operating limits. In particular, the single use of parallel FACTS devices may not improve the safe operating conditions of the system depending on the load conditions. Therefore, avoiding parallel FACTS devices' high costs is crucial and determining their optimal places in the system. For this, Static Var Compensator (SVC), one of the parallel FACTS devices, is used. This study investigated the effects of multiple uses of SVC on different load buses on the maximum load parameter of the multi-machine system in a 3-machine 9-bus power system. Moreover, bus-voltage profiles and their changes in active-reactive power are studied in detail. In this study, three analysis methods were used. These are the no SVC, the single use of SVC, and the multiple uses of SVC. The Power Systems Analysis Program (PSAT) was preferred for this simulation study. As a result of the study, using multiple SVCs increases the maximum loading parameter value and improves the bus-voltage profiles and active-reactive power changes compared to others. [ABSTRACT FROM AUTHOR]

With the exponential growth of data traffic in wireless networks, edge caching has been regarded as a promising solution to offload data traffic and alleviate backhaul congestion, where the contents can be cached by an unmanned aerial vehicle (UAV) and user terminal (UT) with local data storage. In this article, a cooperative caching architecture of UAV and UTs with scalable video coding (SVC) is proposed, which provides the high transmission rate content delivery and personalized video viewing qualities in hotspot areas. In the proposed cache-enabling UAV-D2D networks, we formulate a joint optimization problem of UT caching placement, UAV trajectory, and UAV caching placement to maximize the cache utility. To solve this challenging mixed integer nonlinear programming problem, the optimization problem is decomposed into three sub-problems. Specifically, we obtain UT caching placement by a many-to-many swap matching algorithm, then obtain the UAV trajectory and UAV caching placement by approximate convex optimization and dynamic programming, respectively. Finally, we propose a low complexity iterative algorithm for the formulated optimization problem to improve the system capacity, fully utilize the cache space resource, and provide diverse delivery qualities for video traffic. Simulation results reveal that: i) the proposed cooperative caching architecture of UAV and UTs obtains larger cache utility than the cache-enabling UAV networks with same data storage capacity and radio resource; ii) compared with the benchmark algorithms, the proposed algorithm improves cache utility and reduces backhaul offloading ratio effectively. [ABSTRACT FROM AUTHOR]

This paper proposes a coordinated voltage control scheme for transmission systems based on linearized power flow functions to determine the set points of local control voltage devices. The scheme considers models and interactions between different devices to attain the appropriate performance (non-optimal or optimal) of the whole power system. The sensitivity analysis is used to formulate a partly linearized model that relates the voltage variations of buses to the reactive power variation of synchronous machines, settings of static VAr compensators (SVCs), shunt capacitors susceptance, and tap position of load tap changers (LTCs) to determine the set of the settings of the voltage control devices. Two formulations are proposed by considering the susceptance of SVCs or the slope and reference voltage of characteristics of SVCs as control variables. The developed formulation based on the linearized power flow functions provides the possibility of the practical implementation of the coordinated voltage control scheme, especially the optimal one, by reducing the model complexity and solving time. The performance of the proposed formulations is investigated by some studies of voltage control and an optimally coordinated problem on the IEEE 30-bus and IEEE 118-bus test systems. • Coordinated voltage control of a wide variety of voltage control devices dispersed on the transmission network. • Formulating a partly linearized model based on a sensitivity analysis of nonlinear power flow functions. • Formulations by considering two different models for SVC. • Applicable to both non-optimal coordinated or optimal coordinated problems. • Considering a complete set of objectives, including operation indices of the network and fast and slow voltage control devices. [ABSTRACT FROM AUTHOR]

The depletion of conventional fuel reserves and the high carbon emissions have alarmed the energy sector drivers. The integration of renewable energy resources (RERs) towards power system transformation is an obvious approach for a new-zero future. However, this integration also brings challenges in terms of voltage stability and power losses due to the variable output of RERs. To address these challenges, this work proposes a novel approach utilizing photovoltaic (PV) inverters and static var compensators (SVCs) for reactive power control in power distribution networks (PDNs). It enhances voltage stability and minimizes power losses. The proposed study deploys a proximal policy optimization (PPO) algorithm for real-time communication and control between reactive power devices. Performance evaluation was made on an IEEE-33 Bus system to demonstrate the effectiveness of the proposed scheme in integrating RER-based distributed generators (DGs). The proposed system achieved 68 % voltage control, keeping the voltage within a certain range of ±5 % while minimizing power losses. The proposed system also reduced the voltage out-of-control ratio to 0.044, which indicates minimum voltage deviation from the standard value. The proposed study provides a promising solution for controlling the voltage of DGs integrated PDN, which can potentially enhance the efficiency and reliability of the power system. • This paper introduces PV inverters and SVC-based reactive power voltage regulation for renewable DG-integrated systems. • Reactive power control in the DG-integrated system is adopted using Reinforcement Learning-Driven PPO. • The validation of the proposed method uses the IEEE-33 bus system to integrate RERs-based DGs and achieve PPO-based control. • The proposed method achieved 68% voltage control, reduced power loss, and reduced the voltage out-of-control ratio to 0.044. • This research compares the suggested approach to different methodologies to demonstrate its validity and applicability. [ABSTRACT FROM AUTHOR]

Numerous assumptions and approximations are employed when translating satellite-derived radiance to surface remote sensing reflectance ($R_{\mathrm {RS}}$) for ocean color applications. Among these is the vicarious calibration coefficient ($g$) of the “long” near infrared band (NIR $_{\mathrm {L}}$) used for atmospheric correction. For this band, the prelaunch calibration has always been deemed sufficient [thus $g$ (NIR $_{\mathrm {L}}) =1.00$ ] as long as other bands are vicariously calibrated. Recent research, however, suggests that Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua $R_{\mathrm {RS}}$ time series is quite sensitive to $g$ (NIR $_{\mathrm {L}}$) (and associated vicarious gains in other bands). In this work, we assessed the sensitivity of Visible Infrared Imaging Radiometer Suite onboard the Suomi National Polar-orbiting Partnership satellite (VIIRS/SNPP) $R_{\mathrm {RS}}$ to NIRL calibration and compared our results to previous MODIS/Aqua and Sea-viewing Wide Field-of-View Sensor onboard OrbView2 (SeaWiFS)/OrbView2 analysis. In doing so, we note that $g$ (NIR $_{\mathrm {L}}$) sensitivities of mission-averaged $R_{\mathrm {RS}}$ time series are lower for VIIRS and SeaWiFS, relative to MODIS. At the scale of monthly climatologies (MCs), however, all sensors show prominent $g$ (NIR $_{\mathrm {L}}$) sensitivity with that of SeaWiFS being the most substantial. These findings informed simulation analyses, whereby we identified signal-to-noise ratio (SNR) and radiant path geometry, as well as their interaction, as having notable impacts on $g$ (NIR $_{\mathrm {L}}$) sensitivity. As such, $g$ (NIR $_{\mathrm {L}}$) sensitivity is a necessary consideration for reflectance uncertainty budgets, especially for sensors with higher NIR SNR or particular prevailing radiant path geometries. Given the geometry components embedded within $g$ (NIR $_{\mathrm {L}}$) sensitivity, such studies should be coupled with cross-sensor intercalibrations [e.g., using simultaneous same view (SSV) measurements] toward minimizing NIRL errors between satellite instruments, but such efforts will not completely remediate remaining cross-sensor biases in $R_{\mathrm {RS}}$. [ABSTRACT FROM AUTHOR]

High-voltage direct-current (HVDC) systems using voltage source converters (VSCs) have been developed to suppress voltage fluctuations in offshore grids due to the intermittent power generation of offshore wind farms (OWFs). This paper proposes a new strategy for the optimal secondary voltage control of HVDC-linked OWFs. In the proposed strategy, optimal coordinated control of an HVDC system and OWFs is achieved to minimize real-time voltage fluctuations throughout an offshore grid. A full-order dynamic model of HVDC-linked OWFs is implemented, and its unobservable and uncontrollable state variables are then eliminated using a model reduction algorithm. Given the dynamic model, a linear quadratic Gaussian regulator is designed for optimal coordinated control, and an eigenvalue analysis is conducted focusing on the effects of communication time delays on the stability of the proposed strategy. Simulation case studies are also carried out to verify that the proposed strategy more effectively improves real-time regulation of offshore grid voltages, compared to conventional strategies, while ensuring voltage stability even for relatively large delays in communications systems. [ABSTRACT FROM AUTHOR]

Spatially varying exposure (SVE) is a promising choice for high-dynamic-range (HDR) imaging (HDRI). The SVE-based HDRI, which is called single-shot HDRI, is an efficient solution to avoid ghosting artifacts. However, it is very challenging to restore a full-resolution HDR image from a real-world image with SVE because: a) only one-third of pixels with varying exposures are captured by camera in a Bayer pattern, b) some of the captured pixels are over- and under-exposed. For the former challenge, a spatially varying convolution (SVC) is designed to process the Bayer images carried with varying exposures. For the latter one, an exposure-guidance method is proposed against the interference from over- and under-exposed pixels. Finally, a joint demosaicing and HDRI deep learning framework is formalized to include the two novel components and to realize an end-to-end single-shot HDRI. Experiments indicate that the proposed end-to-end framework avoids the problem of cumulative errors and surpasses the related state-of-the-art methods. Related codes and datasets will be provided at https://github.com/yilun-xu/SVEHDRI/. [ABSTRACT FROM AUTHOR]

Worldwide, due to the abrupt growth of population, the load demand has been rising dramatically in the last few years. This led to an increase in branch overloads, voltage deviations, and power losses. These problems may result in line outages or the occurrence of blackouts. Flexible AC transmission system (FACTS) devices can be installed in the power system to ensure increased power flow capability and flexible voltage control to address these issues. In this paper, one of the most used FACTS is utilised. It is called Static VAR Compensator (SVC). This controller is one of the most commonly used shunt FACTS controllers due to its low cost in comparison to others, ease of operation, and integration into the power grid. Two Optimization algorithms are combined to form a hybrid optimization approach: Cuckoo Search (CS) and Antlion Optimization (ALO). This hybrid approach employs the exploration of ALO to adjust the optimum allocation and size for SVCs in the power system. This study proposes the IEEE 57 bus scheme as a fairly large structure, with the 50 and 41 branch outages considered the worst-case scenarios for line outages in this system. The simulation results show that the proposed methodology balances exploring the research space and exploiting the best existing solutions compared to some of the other introduced approaches in the literature. [ABSTRACT FROM AUTHOR]

A constant worldwide growing load stress over a power system compelled the practice of a reactive power injection to ensure an efficient power network. For this purpose, multiple technologies exist in the knowledge market out of which this paper emphasizes the usage of the flexible alternating current transmission system (FACTS) and presents a comparative study of the static var compensator (SVC) with the static synchronous compensator (STATCOM), inducted in a real electric substation. The aim is to improve the power factor (PF) and power quality and to encounter reliably extreme conditions. A 220 kV electric substation was opted for the analysis, and both the static and dynamic conditions were observed with the help of a power system analysis tool termed PowerFactory-DIgSILENT. Multiple aspects were investigated via software simulations to assess the performance of the aforementioned FACTS devices, such as the voltage profile evaluation via the load flow analysis method (LFA), the harmonic response via the power quality and harmonic analysis tool, and the short-circuit response via the RMS simulation tool. The outcomes were verified and compared with permissible values included in the universal standards, such as IEC and IEEE. The superiority of the STATCOM over the SVC was proven in light of the simulative results. [ABSTRACT FROM AUTHOR]