Voltage Instability In Power Systems Research Articles

A Comprehensive Review on Voltage Stability in Wind-Integrated Power Systems

The fast growth of the world’s energy demand in the modernized world has stirred many countries around the globe to focus on power generation by abundantly available renewable energy resources. Among them, wind energy has attained significant attention owing to its environment-friendly nature along with other fabulous advantages. However, wind-integrated power systems experience numerous voltage instability complexities due to the sporadic nature of wind. This paper comprehensively reviews the problems of voltage instability in wind-integrated power systems, its causes, consequences, improvement techniques, and implication of grid codes to keep the operation of the network secure. Thorough understanding of the underlying issues related to voltage instability is necessary for the development of effective mitigation techniques in order to facilitate wind integration into power systems. Therefore, this review delves into the origin and consequences of voltage instability, emphasizing its adverse impacts on the performance and reliability of power systems. Moreover, it sheds light on the challenges of integrating wind energy with existing grids. This manuscript provides a comprehensive overview of the essential features required for critical analysis through a detailed examination of Voltage Stability Indices (VSIs). To address voltage stability issues in wind-integrated power systems, this review examines diverse techniques proposed by researchers, encompassing the tools utilized for assessment and mitigation. Therefore, in the field of power system operation and renewable energy integration, this manuscript serves as a valuable resource for researchers by comprehensively addressing the complexities and challenges associated with voltage instability in wind-integrated power systems.

Deep Reinforcement Learning for Load Shedding Against Short-Term Voltage Instability in Large Power Systems.

We introduce an innovative solution approach to the challenging dynamic load-shedding problem which directly affects the stability of large power grid. Our proposed deep Q-network for load-shedding (DQN-LS) determines optimal load-shedding strategy to maintain power system stability by taking into account both spatial and temporal information of a dynamically operating power system, using a convolutional long-short-term memory (ConvLSTM) network to automatically capture dynamic features that are translation-invariant in short-term voltage instability, and by introducing a new design of the reward function. The overall goal for the proposed DQN-LS is to provide real-time, fast, and accurate load-shedding decisions to increase the quality and probability of voltage recovery. To demonstrate the efficacy of our proposed approach and its scalability to large-scale, complex dynamic problems, we utilize the China Southern Grid (CSG) to obtain our test results, which clearly show superior voltage recovery performance by employing the proposed DQN-LS under different and uncertain power system fault conditions. What we have developed and demonstrated in this study, in terms of the scale of the problem, the load-shedding performance obtained, and the DQN-LS approach, have not been demonstrated previously.

Comprehensive review on control schemes and stability investigation of hybrid AC-DC microgrid

The utility grid integration of distributed generation units is seen as one of the most accomplished through the use of microgrid. Control methods and stability analyses in the microgrid are continuously being investigated in the field of hybrid microgrid. The most reviewed control method is hierarchical control, consisting of primary, secondary, and tertiary layers. This paper reviews multiple schemes of primary control for current or voltage regulation, secondary control for voltage or current error correction, power-sharing in microgrid, and tertiary control for power flow and energy management in a hybrid microgrid system. Additionally, this study examines the benefits and drawbacks of several control architectures that function as distributed, centralized, and decentralized controls. The principle of operation and effectiveness of each microgrid architecture control method have been discussed. Specific control factors are investigated in this paper, including mode transition and coordinated control between numerous interlinking converter and energy storage systems. System stability is the main concern of microgrid for system engineer thorough knowledge of control strategies is the upmost requirement. Thus, this paper highlights control strategies, rotor angle, voltage and frequency instability in power systems, and methods for improving stability in microgrid are also reviewed.

Knowledge-enhanced deep reinforcement learning for intelligent event-based load shedding

Event-based load shedding (ELS) is an important emergency countermeasure against transient voltage instability in power systems. At present, the formulation of ELS measures is usually determined offline by the experience of experts, which is inefficient, time-consuming, and labor-intensive. This paper proposes a knowledge-enhanced deep reinforcement learning (DRL) method for intelligent ELS. Firstly, the Markov decision process (MDP) of the knowledge-enhanced DRL model for ELS is established based on transient stability simulation. Different from traditional response-based MDP, this MDP is event-based. Then, compared to conventional exponential decision space, a linear decision space of the DRL agent is established to reduce the decision space and training difficulty. Furthermore, the knowledge of removing repeated and negative actions is fused into DRL to improve training efficiency and decision quality. Finally, the simulation results of the CEPRI 36-bus system show that the proposed method can accurately give effective ELS measures. Compared with the pure data-driven DRL method, the knowledge-enhanced DRL method is more efficient.

Physical test study on power system voltage collapse

In order to test and verify the phenomena of power system voltage collapse, this article chooses a single-load infinite-bus system and a single-machine single-load system as the sample systems based on the PS-5G test system to carry out the voltage stability physical tests, and an induction motor and an adjustable resistor are used to constitute the comprehensive load. The test results show that in the single-load infinite-bus system, with the decrease of the adjustable resistance gradually, the comprehensive load active power is gradually increasing and the load bus voltage is gradually decreasing; and the slight adjustment for the adjustable resistance can cause the load bus voltage collapse when the induction motor has the locked-rotor. In the single-machine single-load system, the locked-rotor of the induction motor can lead to the occurrence of the reactive power limit-induced bifurcation, it causes the terminal voltage of the synchronous generator and the load bus voltage to have an instantaneous collapse. The test results are conducive to comprehend the mechanisms of voltage instability and collapse in power systems.

ASSESSMENT OF THE VOLTAGE STABILITY LOAD INDEX OF ELECTRIC NETWORKS BASED ON THE ECHO STATES NETWORK USING THE PHASOR UNIT

The issue of power system voltage stability, which is one of the key issues in the process of planning and operation of the power system, is considered in the paper. It is noted that neural networks have now been tested in a number of technological incidents in the form of power system voltage instability in various countries. The problem of possible risk of voltage failure due to the loss of its stability in the energy system during its operation is investigated. It is noted that in this regard, conducting a voltage stability analysis is an important procedure in order to timely identify buses with low reliability within the power system. Thus, the control personnel of the power system should take certain measures to avoid any cases of voltage drop within the system. The purpose of this paper is to present a new method for estimating the voltage stability load index (L-index) for a power system using data from optimally placed phasor units (PMUs). The voltage stability load index is evaluated in the work using a recurrent neural network known as the echo state network (ESN). The PMU optimal placement is made taking into account the island operating conditions. The results of the PMUs optimal placement for normal and boundary operating conditions, as well as the evaluation of the L-index using ESN in the IEEE 14 bus system, are presented. A technique for estimating the voltage stability load index in a power system based on a network of echo states using PMU measurements is presented. An estimate of the ESN performance for the L-index has been performed; the results have shown a high accuracy of its estimate under normal and disturbed conditions. It has been proven that ESN development is efficient and provides an accurate evaluation in computations.

A novel load shedding methodology to mitigate voltage instability in power system

Aim. A novel technique for detecting imminent voltage instability is proposed in this paper, accompanied by a novel load shedding approach to protect the system from voltage instability. Methodology. The proposed methodology utilizes the computation of nodal reactive power loss to voltage sensitivities with load increments in the system. Originality. The nodal reactive power loss to voltage sensitivity is a novel computation and is explored to detect the likelihood of voltage instability in this work. Results. If the system is experiencing an unprecedented load growth and if all the measures reach their limits, then load shedding is the last resort to safeguard the system against instability. The sudden change in nodal reactive power loss to voltage sensitivities is utilized to devise the quantity of load to be cut in the system. Practical value. The time-based simulations performed in New England 39 bus test system (NE-39 bus), the simulated results show that nodal reactive power loss to voltage sensitivities can be used as a trusted indicator for early diagnosing of menacing voltage instability and the timely implementation of load shedding developed from nodal reactive power loss to voltage sensitivities on the system ensures voltage stability.

Voltage instability curtailment and quality improvement with phasor measurement unit in power system

PurposeThe earlier methods are more resilient to improvements such as load shift and path change. This results in problems such as a voltage drop and a high reactive flux. In addition, due to the delay, congestion or interruption of the transmission, the system cannot receive all phasor measurement unit (PMU) measurements at the relevant time as well as the presence of noise in the received data.Design/methodology/approachWith the development of wide area measurement system technologies, it seems to be possible to track voltage stability online via time-stamped PMUs. As the voltage instability causes a voltage decomposition, voltage instability is one of the most important problems when monitoring the power supply.FindingsThis harmonic distortion significantly decreases the data quality in the grid. As a result, instability ascertainment based on PMU has been suggested as a method for detecting voltage instability in power systems monitored with PMU. In addition, a technique called instability amendment via load dropping has been proposed to keep the device from collapsing due to voltage failure.Originality/valueTo improve the power output, the power prominence melioration technique was developed. This proposed system has been implemented in MATLAB Simulink and compared with the recent researches.

A graph attention networks-based model to distinguish the transient rotor angle instability and short-term voltage instability in power systems

Digital simulation is significant for the operating mode and control decision-making of power systems. In the process of simulation data analysis, stability analysis is an essential part. One of the most challenging tasks is to distinguish between transient rotor angle instability and short-term voltage instability. This paper proposes a graph attention networks (GATs)-based method to overcome this ticklish problem via integrating power grid topology information into the neural networks. Compared with the conventional graph convolutional networks (GCNs), the attention mechanism is introduced into the GATs to learn the weights among different neighbor vertices in the graph. Due to the difficulty of distinguishing between the rotor angle instability and voltage instability in some samples, a label-smoothing method is adopted to alleviate the influence caused by label inaccuracy. Case studies are conducted on an 8-machine 36-bus system and Northeast China Power System. Simulation results show that the proposed method has better performance than conventional GCNs and other machine learning methods.

Vulnerability assessment for voltage stability based on solvability regions of decoupled power flow equations

This paper proposes a novel method of identifying buses vulnerable to power system voltage instability. Unlike traditional sensitivity and modal analysis methods, the proposed method can preserve the nonlinearity of power flow equations, and visually pinpoint the vulnerable buses in advance for any possible load increasing scenarios. Based on the power flow equations on decomposed two-bus equivalent channels from the power network, a vulnerability index is introduced and visualized for each channel in the solvability region of its decoupled power flow equations bounded by a parabola. It is found that the arrival at the parabolic boundary indicates a potentially vulnerable bus but not necessarily results in voltage collapse. Thus, a criterion on the gradient of vulnerability index trajectory is proposed to discover and differentiate two types of potentially vulnerable buses: one type has trajectories that are tangent to the boundary but stay inside the solvability region; the other type has trajectories crossing the boundary to result in unsolvable power flow equations, which are identified as the vulnerable buses. The proposed method is validated on the IEEE 14-bus, IEEE 118-bus, and New England power systems with comparison to the traditional methods, and the test results show that the proposed method performs better than the traditional methods with satisfactory robustness under voltage fluctuation. In particular, the proposed method is 33.3% and 66.7% more accurate than the voltage sensitivity method in prospective operating conditions on the IEEE 14-bus and 118-bus systems, respectively.

Investigation of Disruptive Effect on Voltage Stability Caused by Line Contingency in Power Systems and Improvement of System Stability

There are many situations that cause voltage instability in power systems. One of these situations is line contingency that may occur in power systems. In this study, the effects of line contingency on the steady state are investigated in the IEEE 9 buses power system. Firstly, the static and dynamic analyses of the power system are made in normal operating condition. Continuous power flow analysis was used as static analysis and time domain simulation method were used as dynamic analysis. Then each transmission line is deactivated and the analyses are repeated. The changes in the maximum loading capacity and voltage stability of the system are investigated in case of each transmission line contingency. Finally, Static Var Compensator (SVC) is connected to the power system to improve the stability level. When the SVC is connected to the power system, the maximum loading capacity of the system is examined and the effects of this situation on the voltage stability are analyzed. All analyses are performed in the MATLAB® PSAT (Power System Analysis Toolbox). The results showed that the line contingency reduces the maximum loading capacity and deteriorates the voltage stability. It has been observed that both the problems can be eliminated with the SVC integration into the power system.

Research on improving transient voltage stability of wind power grid connected system by SFCL and STATCOM

Aiming at the problem of transient voltage instability in the grid-connected wind power system, a combined method of superconducting fault current limiter (SFCL) and static synchronous compensator (STATCOM) was proposed to suppress voltage saps. In this method, a superconducting fault current limiter (SFCL) is connected in series on the transmission line, and a static synchronous compensator (STATCOM) is connected in parallel on the bus of the wind farm. SFCL shows zero impedance when the system is in normal operation, and quickly shows high impedance when the fault occurs, so as to effectively suppress the short-circuit current and provide the bus voltage support. At the same time, STATCOM provides reactive power during the fault period, so that the system voltage can quickly recover. By establishing the corresponding simulation model, SFCL and STATCOM are used to jointly improve the voltage stability of the wind power grid-connected.

Nonparametric preventive/corrective voltage stability enhancement of active distribution systems with integrated electric vehicles charging facilities

The increasing penetration of electric vehicles (EVs) and renewable energy resources (RESs) have raised concerns about the voltage instability in distribution power systems. Thus, some probabilistic algorithms are needed by decision-makers to quickly yet accurately evaluate the voltage stability margin in smart distribution systems. This paper proposes a nonparametric preventive control to mitigate the risk of voltage instability in the active distribution systems consisting of EVs and RESs. First, a framework is developed to evaluate EVs' degree of participation in preventive control by estimating potential achievable power capacity (PAPC). To estimate the probability density function (PDF) of the system voltage stability margin, Bernstein density estimator (BDE) is utilized due to its capability to handle the boundary effect. Finally, a preventive/corrective control model based on the model predictive control (MPC) is developed considering the dynamic behavior of EVs and RESs. The capability of the proposed algorithm is tested on the modified IEEE 33-node system.

Evaluation of Geomagnetic Induced Current on 275 kV Power Transformer for a Reliable and Sustainable Power System Operation in Malaysia

Geomagnetic induced current (GIC) occurs as a direct consequence of abnormal space weather which starts from the sun and may flow into a power system network through neutral grounding connections. The flow of GIC through grounded neutral power transformer has been a major concern to researchers since it can potentially affect power system equipment. Most of the previous research was focused on high and mid latitude countries only. However, it has been proven that the GIC is not only limited to high and mid latitudes, but also extends to power systems at lower geographic latitudes. This paper aims to investigate the impacts of GIC on selected 275 kV subpower system networks in Peninsular Malaysia, which is among the low latitude countries. Its impact in terms of magnitude and duration is also assessed together with the use of neutral earthing resistor (NER) as a potential blocking component to reduce the impact of GIC on the Malaysian power system network. Results demonstrated that when GIC exists in the power system, power transformers undergo half-cycle saturation that may lead to a reactive power loss and power system voltage instability. In this case, the power transformer can only withstand a maximum GIC value of 7 A, and beyond this value, if prolonged, may lead to voltage instability. It turned out that GIC magnitude had more impact compared to duration. However, long duration with high magnitude of GIC is the most hazardous to power transformers and could potentially cause major faults in the power system network. As part of mitigation, NER with a value of 315.10 Ω can be used to limit the GIC current flow and thus provide protection to the power system network. Clearly, the issue of GIC undoubtedly affects the reliability, security and sustainability of power system operation, especially networks with highly critical load and capacity and, therefore, thorough studies are required to assess and mitigate this issue.

A Hierarchical Data-Driven Method for Event-Based Load Shedding Against Fault-Induced Delayed Voltage Recovery in Power Systems

Load shedding (LS) is an effective control strategy against voltage instability in power systems. With increasing uncertainties and complexity in modern power grids, there is a pressing need for faster and more accurate control decisions. In this article, a hierarchical data-driven method is proposed for the online prediction of event-based load shedding (ELS) against fault-induced delayed voltage recovery. The ELS problem is hierarchically modeled as a multi-output classification subproblem for identifying the best shedding location and a regression subproblem to predict the minimum shedding amount. To solve the two subproblems, the weighted kernel extreme learning machine is adopted to construct a direct mapping between the system pre-fault operating conditions and the corresponding control variables. The method is tested on the ELS database, which is analytically generated via a novel adaptive sensitivity-based process on the New England 39-bus system. Compared with other methods, the proposed method is very accurate in prediction with excellent control performance, which maintains superior prediction ability under an imbalanced data distribution.

Voltage Stability Improvement and Loss Minimization by Optimal Placement of STATCOM using Teaching- Learning Based Optimization Technique

In the modern power system voltage instability is the most prevalent issue which occurs continually and mandates the system operator to find the remedy in order to have the efficient and reliable operation of equipment con-nected to the system. This literature emphasizes on the voltage instability issue of power systems and also an approach which can overcome the problem when-ever the system is subjected to an aforementioned problem which is usually ac-complished by deploying compensation device of suitable size. In this paper, teaching learning-based optimization technique is used to find the appropriate size of the compensatory device, whenever the voltage violation occurs due to the increased demand for active power as well as reactive power in the system. dv/dq index is preferred to find the location of compensatory device allocation. In this literature, STATCOM is used as a compensatory device and this ap-proach is validated for IEEE 30 bus system on the MATLAB platform.

Power system voltage instability risk mitigation via emergency demand response-based whale optimization algorithm

In recent years, due to the economic and environmental issues, modern power systems often operate proximately to the technical restraints enlarging the probable level of instability risks. Hence, efficient methods for voltage instability prevention are of great importance to power system companies to avoid the risk of large blackouts. In this paper, an event-driven emergency demand response (EEDR) strategy based on whale optimization algorithm (WOA) is proposed to effectively improve system voltage stability. The main objective of the proposed EEDR approach is to maintain voltage stability margin (VSM) in an acceptable range during emergency situations by driving the operating condition of the power system away from the insecure points. The optimal locations and amounts of load reductions have been determined using WOA algorithm. To test the feasibility and the efficiency of the proposed method, simulation studies are carried out on the IEEE 14-bus and real Algerian 114-bus power systems.

Voltage instability analysis based on modal analysis technique and artificial neural network

<span>One of the paramount importance in the operation of electrical power system operation order to sustain the equilibrium of the system is the stability of the load buses’ voltages. If the load buses voltages are not stable, this can cause serious problem especially power system blackout. This paper presents the analysis of voltage instability in electric power system by using modal analysis technique. However, one of the challenges of modal analysis is the intencive and complex calculation procedures. In order to overcome that, this paper implements Artificial Neural Network (ANN) to improve the implementation of modal analysis technique. ANN is used to determine the participation factors obtained from the modal analysis technique. The results show that modal analysis technique is able to show which bus is close towards experiencing voltage instability. In addition, the results also show that ANN is able to predict the values of participation factors. A load bus is considered a weak bus if the bus has high tendency towards experiencing voltage instability. IEEE-14 bus test power system has been chosen as the test power system.</span>

Techniques for the Identification of Critical Nodes Leading to Voltage Collapse in a Power System

AbstractThis paper proposes two techniques for the identification of critical buses in a power system. The technique of Network Structural Theory Participation Factor (NSTPF) depends on the network structural interconnection of buses as captured by the admittance matrix of the system and is formulated based on the fundamental circuit theory law using eigenvalue decomposition method. Another power flow based technique which depends on the system maximum loadability, the system step size among other factors is also proposed. Traditional power flow based techniques are used as benchmarks to determine the significance of the proposed methods. To ensure voltage stability enhancement, STATCOM FACTS device is installed at the selected weak load buses of the practical Nigerian 24 bus and IEEE 30 bus test systems. The results of the simulation obtained show that, the suggested approach of NSTPF is more suitable in the identification of weak buses that are liable to voltage instability in power systems as it requires less computational burden and also saves time compared to techniques based on power flow solutions.

New Performance Indices for Voltage Stability Analysis in a Power System

The frequent occurrence of voltage instability in a modern power system is alarming and thus, has been of great concern to power system utilities. In this paper, a new performance index based on the power flow solutions for voltage stability assessment of a power system is presented. First, the voltage deviation with respect to reactive power load variation at each load bus is found. Thereafter, the performance voltage bus index for each load bus is computed. An improved modal analysis technique (IMAT) is used to identify weak nodes that are liable to voltage instability in a power system. This technique uses a submatrix of the full Jacobian matrix for voltage stability analysis. Comparison of the proposed method is done with existing voltage stability indices and the conventional modal analysis technique (CMAT). The effectiveness of all the approaches presented are tested on both Western system coordinating Council (WSCC) 9-bus, IEEE 30 bus and IEEE 57 bus test systems. Results obtained show that the proposed techniques can serve as an alternative tool to other conventional techniques for voltage stability assessment in a power system and can be of tremendous benefits in the planning and operation of a power system by system operators.