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Increasing demand for electricity and the modernization of power systems within competitive markets has induced power systems to operate close to their stability limits. Therefore, the continuous monitoring and control of power systems through voltage stability indices is urgently needed. This is the first-ever effort to examine more than 40 voltage stability indices based on their formulation, application, performance, and assessment measures. These indices are sorted based on a logical and chronological order considering the most recent indices to be applied worldwide. However, the generalizability of these indices in terms of multivariable objectives is limited. Despite its limitation, this study systematically reviews available indices in the literature within the past three decades to compile an integrated knowledge base with an up-to-date exposition. This is followed by a comparative analysis in terms of their similarity, functionality, applicability, formulation, merit, demerit, and overall performance. Also, a broad categorization of voltage stability indices is addressed. This study serves as an exhaustive roadmap of the issue and can be counted as a reference for planning and operation in the context of voltage stability for students, researchers, scholars, and practitioners.

This study presents a procedure for placing static var compensators (SVC) in an EPS using the fuzzy c-means clustering technique. For this purpose, the optimal power flow (OPF) is initially quantified to obtain the sensitivity array of the system based on the Jacobian of the system. Then, the attenuation and electrical distance matrices are estimated. Subsequently, the fuzzy c-means clustering algorithm is used with the initially estimated cluster identification criterion to obtain the voltage control areas (VCAs). On the other hand, the criterion of minimizing the installation costs of the SVCs is used in conjunction with the linear voltage stability index (LVSI) for the ideal arrangement of the compensators. This is applied to each VCA created. The technique described is applied to the 14-node and 30-node schemes to check their effectiveness. Additionally, the results obtained are compared with the Power Factory software and with similar studies. Finally, the proposed technique proves to be effective for the creation of VCAs and for the optimal placement of SVC equipment.

This paper proposes a load shedding program for evaluating and distributing the minimum load power to be curtailed required to bring the frequency and voltage, after the system was subjected to a heavy disturbance, to the allowable range for each load bus. The quantity of load shedding was estimated to restore the power system's frequency, taking into account the turbine governor's primary control and the generators' reserve power for secondary control. Calculation and review of the load bus's voltage stability indicator (Li) to prioritize the load shedding quantity at these locations. The lower the voltage stability indicator on the load bus, the less load shedding can occur, and vice versa. The frequency and voltage values are still within allowable ranges with this approach, and a significant amount of load shedding can be prevented, resulting in a reduction in customer service interruption. The proposed method's efficacy was demonstrated when it was checked against the IEEE 30 bus 6 generators power system standard simulated in MATLAB environment and it minimize the power to be shed by around 20% of the conventional load shedding schemes.

Integration of Distributed Generation (DG) into a distribution network reduces the costs of network expansion and increases the network reliability by reducing the voltage magnitude deviations. This study proposes a Symbiotic Organisms Search (SOS)-based technique for determining the best size and position of DG in radial distribution networks to improve their voltage profile and voltage security state. The objective is to minimize the bus voltage variation and maximize Voltage Stability Index (VSI) of the network as a multi-objective optimization problem in the presence of source and load uncertainties. In addition, the uncertainty regarding the solar power, wind power, and load is modeled using 2m point estimate method along with SOS algorithm. To better illustrate the effect of the DG placement on the voltage security state of the distribution system, the system was classified into three states depending on the VSI values. The simulation results obtained from two standard (IEEE) radial distribution networks confirm the efficiency and accuracy of the proposed SOS method. The results of the SOS-based method are compared with those obtained by some other techniques proposed in recent literature based on which it can be concluded that the SOS algorithm outperforms other standard optimization techniques,

Voltage stability improvement is a challenging issue in planning and security assessment of power systems. As modern systems are being operated under heavily stressed conditions with reduced stability margins, incorporation of voltage stability criteria in the operation of power systems began receiving great attention. This study presents a novel voltage stability constrained optimal power flow (VSC-OPF) approach based on static line voltage stability indices to simultaneously improve voltage stability and minimise power system losses under stressed and contingency conditions. The proposed methodology uses a voltage collapse proximity indicator (VCPI) to provide important information about the proximity of the system to voltage instability. The VCPI index is incorporated into the optimal power flow (OPF) formulation in two ways; first it can be added as a new voltage stability constraint in the OPF constraints, or used as a voltage stability objective function. The proposed approach has been evaluated on the standard IEEE 30-bus and 57-bus test systems under different cases and compared with two well proved VSC-OPF approaches based on the bus voltage indicator L-index and the minimum singular value. The simulation results are promising and demonstrate the effectiveness of the proposed VSC-OPF based on the line voltage stability index.

This article delves into the eco-friendly operation of a smart microgrid, highlighting its ability to maintain voltage security through a flexible renewable hybrid system. The framework incorporates wind and bio-waste energy sources to produce electricity, while leveraging electric vehicles as mobile storage units and flexibility resources. The hybrid system is also capable of managing reactive power. The design focuses on two core Objectives: minimizing operational costs and bolstering voltage security in the grid. To ensure these goals are met, several critical constraints are addressed, including the AC optimal dispatch model, security limitations of the smart microgrid, management of hybrid resources and storage operations, and restrictions related to system flexibility. A single-objective optimization approach uses weighted functions alongside a fuzzy decision-making method to achieve a compromised solution. Stochastic programming is applied to accurately account for uncertainties linked to renewable energy production, load fluctuations, energy pricing, and electric vehicle integration. The research stands out for introducing a multi-objective energy scheduling approach that combines a flexible-renewable hybrid system with the adaptability of electric vehicles and the operational capabilities of bio-waste systems. Numerical simulations emphasize the effectiveness of this design in improving both the technical performance and economic feasibility of smart microgrids and hybrid systems. Noteworthy findings reveal that mobile storage units can fully meet the flexibility requirements of the hybrid system. In comparison with conventional load flow studies, this optimized system delivers enhancements in voltage stability, economic efficiency, and operational capacity by approximately 20%, 33%-65%, and 41%, respectively.

In this work, the indicators of electrical power network stability and voltage stability (VS) are discussed and developed with the aim of using a power transfer stability index (PTSI) indicator as a predictor for voltage stability (VS) in electrical power networks. The power transfer stability index (PTSI) was thus used to detect abnormally weak voltages in buses within such power system networks (weak). The target data are obtained using the Newton Raphson method (NR) and include magnitude, phase angle, and active and reactive power. A new adaptive particle swarm optimization-neural network algorithm based on a guiding strategy (GSAPSO-NN) was also used to achieve the goal of the paper by improving the mixed particle updates and the weightings of the neural network to decrease the search time. All results were then compared with actual values as calculated using the PTSI NR method. The final results show only simple differences or approximately the same values using both the proposed and the classical methods. The MATLAB-PSAT package was employed to obtain most of these results and the testing of the new method was done on the IEEE14 bus system as well as the Iraqi 24-bus power system. The effectiveness validation of the new hybrid method for assessing voltage stability was thus achieved.

Wind power plants penetration into power grids has grown considerably due to the fact of being cheap and clean. As a result, many countries require that the wind turbines must be capable of offering ancillary services such as reactive power control and voltage regulation. Furthermore, some voltage stability indices rely on both reactive and active power; consequently, it is useful to take also into account the active power during the planning stage so as to fulfil the load requirement and to enhance the voltage stability. The present study intends to present an optimization algorithm permitting to diminish the electrical losses and enhance the voltage profile by getting the fittest allocation of active power production of traditional generators and wind power plants. Besides, wind farms reactive power injection is determined. To verify the proposed algorithm, a 40 MW wind farm (WF) made up of doubly fed induction generator (DFIG) and the 14 IEEE bus system are used. In the case study, three different metaheuristic methods are used to resolve the objective function. Finally, the simulation results are reported.

Kinetics of passivity and chloride-induced depassivation of iron exposed to simulated concrete pore solutions were studied using electrochemical quartz crystal nanobalance (EQCN), electrochemical impedance spectroscopy (EIS), and open circuit potential (OCP) monitoring. Passivation followed a two-stage logarithmic film formation process: protective film mostly formed within the first 10 min to 20 min of exposure to the passivating solutions as indicated by a sharp mass increase accompanied by impedance and phase angle data showing trends toward passivation. After this initial passivation period, mass continued to increase, albeit at a significantly slower rate. Electrochemical indicators during this period remained relatively constant and stable, suggesting that the iron remained passive. The mass increase during the post-passivation period was indicative of the formation of additional oxides, while relative stability of the OCP, impedance and phase angle measurements suggested that these oxides were likely more porous, and therefore, less protective than those that had formed during the first 10 min to 20 min. Chloride addition initially caused mass gain while all electrochemical indicators indicated stable passivity, suggesting an induction period before the first signs of pitting. Mass increase during this period supports the predictions of depassivation models that hypothesize the adsorption and ingress of chlorides though the outer layers of oxides.