Estimation methods for voltage stability limits in power systems

With the rapid development of the Chinese power grid, its dynamic behavior becomes increasingly complex. How to prevent voltage instability and voltage collapse at the receiving-end system has become an urgent problem at present. To prevent voltage collapse, the key is to determine the stability margin at the operating point of the power system, and the load margin is the most basic and widely accepted voltage stability margin indicator. Considering the role of medium and long-term slow-acting elements in the actual system that affect the system voltage stability, this paper combines the static voltage stability analysis with the transient, medium, and long-term dynamic voltage stability analysis based on whole process simulation, and uses time-domain simulation methods to evaluate the voltage stability of the actual system. By analyzing the various dynamic characteristics of generator overexcitation limits and transformer on-load regulation on the development process of voltage-collapsing accidents, this paper proposes an evaluation index for the whole process dynamic stability margin of the receiving-end system. On this basis, the whole process dynamic defense system of the power grid is also constructed. The proposed method is validated by using a provincial power grid in China as an example.

This paper discusses voltage stability analysis of power systems using two static voltage stability analyses: voltage sensitivity, modal analysis including participation factor. These methods determine how far the power system is from its break point providing relative measure of voltage instability proximately. Results show all method indices share voltage stability margins having a precise voltage collapse point when a power system is subjected to sudden load increase. The application has been demonstrated on the IEEE 14-bus System.

In recent decades, voltage instability has become an important contributor to large-scale power outages globally. Periodic voltage security assessments are key for the secure operation of power systems. There are various indicators which have been implemented in different types and complexity of systems to provide a measure of closeness to voltage collapse, but some of these algorithms may require advanced computational resources or may not perform well, depending on the prevailing conditions. Expanding interconnected power systems is needed like never before due to the increasing world demand for electricity, and voltage stability is therefore a worth consideration. The growing demand penetration of solar photovoltaic (PV) systems has some potential stability challenges due to their intermittent characteristics. Existing research evaluates the test systems of voltage stability and does not optimize using Intelligent models, which have variable power generation from Solar PV and Wind, as well as uncertainties in load demand and the initial step considering the evaluation of the model have to cover either inputs. A feed–forward back propagation artificial neural network (ANN) for voltage stability assessment to classify the operating scenario of a power system into one of two states, i.e. safe or unsafe. Neural network input data is generated from load flow analysis using Newton-Raphson (NR), and stability indices are computed over different scenarios. Line Stability Index (Lmn), counts the stability of a transmission line in power systems and provides an indication of its potential voltage collapse. The Fast Voltage Stability Index (FVSI), which also estimates line stability through reactive power and impedance characteristics. Voltage Collapse Proximity Index (VCPI) assesses system proximity to voltage collapse and identifies weak transmission lines. Values approaching 1 suggest voltage collapse conditions. The FVSI, VCPI, and Lmn are compared to a baseline NR stability index. Moreover, self-organizing map (SOM) neural network is used for stability results classification. Multi-objective grasshopper optimization algorithm (MOGOA) has been employed as an optimization network on the dual axis solar PV and wind turbine-based hybrid power generation system to analyze technical, economic, as well as environmental relations of energy conversion. The findings reveal that the adapted grid-tied solar-wind composite power system substantially mitigates the power deficiencies, reduces the real-power outages, diminishes the motion voltage small amendments, maximizes voltage prosperity, and improves power system resilience. The main findings show a significant reduction in real power loss, which went from 289,391.30 kW to only 5.43 kW, and a remarkable decrease in voltage deviation, which reduced from 0.56 p.u to 0.0493 p.u. Ensures Improved Service Quality and Enhanced Equipment Protection While gas generation costs increased by a small amount, it is important to note that this is an acceptable trade-off for a more robust and sustainable system, with costs per kWh of $0.142 vs $0.2881 per kWh, respectively. In addition, stability index was substantially decreased from 0.7666 to 0.0768, indicating better grid and resilience to disturbances. Findings emphasize the contribution of embedding MOGOA in conjunction with machine learning models including ANN and Self Organizing Maps (SOM) to fulfill the primal requisites of stability, efficiency and sustainability in modernized power systems, illustrating a coupled advancement in the realm of power systems engineering and optimization.

With the large-capacity DC transmission and various types of power electronic equipment widely used in power systems, the voltage stability problem has once again been closely watched. Voltage stability can be divided into static, transient and dynamic stability. The static voltage stability accident, Generally speaking, the grid load is slowly increased, causing the load terminal bus voltage to slowly drop. Near the critical value, any small disturbance will cause an irreversible sudden drop in the load bus voltage, this is a voltage collapse. The article first analyzes the static voltage stability margin index and related technical standards. Comparative analysis of several static voltage stability margin calculation methods. Second, take the planning grid of a very large city as an example. Using PSS/E software to simulate the static voltage stability margin of the system under various conditions. Analysis of the static voltage stability margin characteristics of the urban power grid. And the reactive power compensation optimization scheme is proposed for the weak voltage link.

Voltage instability and voltage collapse have been considered as a major threat to present power system networks due to their stressed operation. It is very important to do the power system analysis with respect to voltage stability. Flexible AC Transmission System (FACTS) is an alternating current transmission system incorporating power electronic-based and other static controllers to enhance controllability and increase power transfer capability. A FACTS device in a power system improves the voltage stability, reduces the power loss and also improves the load ability of the system. FACTS have made the power systems operation more flexible and secure. Amongst the several FACTS controllers, the Unified Power Flow Controller (UPFC) is most effective to improve the enhancement of voltage stability and reduces the power loss. This study investigates the application of Particle Swarm Optimization (PSO) to find sizing of Unified Power Flow Controller (UPFC) device to minimize the voltage stability index, total power loss, load voltage deviation, and cost of FACTS devices to improve voltage stability in the power system. A new model is proposed in this thesis to improve existing power-based model by using the Norton Equivalent Theorem. The proposed model can be integrated with the Equivalent Current Injection (ECI) power flow model easily. By ECI algorithm, it is much quickly and precisely to implement power flow calculations. Finally It is observed from the results that the voltage stability margin is improved, the voltage profile of the power system is increased and real power losses also reduced by optimally sizing UPFC device in the power system. Index Terms: Voltage stability, Unified Power Flow Controller (UPFC), Equivalent -Current Injection (ECI), Modified particle swarm optimization (MPSO)

Stress on the generation and transmission capability of the power system increased as the energy demand increases. Distributed generation (DG), which is usually placed near the load centre has the capability to meet these energy increment in demands. Hence, for making the power system highly durable and reliable, Distributed generations are interconnected with the existing power system. Based on the nature of the primary source of generation and the energy conversion technology these types of generation have important impacts on power system voltage stability. One of the most significant threats considered for a secure operation of the power system is voltage instability problem. Voltage collapse might occur in an interconnected power system due to voltage instability and thus lead to power blackouts. Hence in an interconnected power system it is essential to know the strength of the buses to monitor and improve the stability of the system. This paper focuses on voltage stability analysis of an interconnected distributed photovoltaic system with IEEE 30 bus system. The voltage stability of the system assessed by evaluating voltage stability indicators at each bus of interconnected power systems. Fast Voltage Stability Index value of each bus is evaluated under normal and critical load conditions. The index value helps to identify the weakest or the bus which is likely to get voltage collapse due to voltage instability problem in the interconnected system.

Power systems are being operated close to their voltage security limit which makes their reliable operation more challenging. Voltage stability has been a major problem faced by utilities now a days. Many blackout have been reported around the world related to voltage instability problem. Many voltage stability analysis methods have been presented up till now. Here artificial neural network based approach for voltage stability analysis of power system is presented. Voltage stability analysis of power system has been done in terms of voltage stability margin. Voltage stability margin is calculated by estimating distance from current operating point to maximum voltage stability point according to loading parameter. Principal Component Analysis is an efficient feature selection method used here to find few input variables required to estimate voltage stability margin with sufficient accuracy and execution speed. Major drawback of previously published work is they need to train new neural network whenever change in system topology occur which is very time consuming process. Therefor in this paper single ANN has been prepared for estimating VSM for several system configuration. Feed forward neural network and radial basis function neural network have been used for voltage stability analysis of power system. The final result indicate that proposed method provide an efficient and compact ANN model for different system configuration as well as base case operating condition with lowest possible input required.

Static voltage stability improvement with battery energy storage considering optimal control of active and reactive power injection

Many technological advancements in the modern era have made actual use of electrical power and the constrained operating of power systems within stability limits. Some expeditious load variations and rising power demands initiate complications in voltage stability and can put stress on performance, leading to voltage instability. Voltage Stability Indices can be used to perform voltage stability assessment. This review evaluates various VSIs based on mathematical derivations, assumptions, critical values, and methodology. VSIs determine the maximum loadability, voltage collapse proximity, stability margin, weak areas, and contingency ranking. Stability indices can also specify the optimal placing and sizing of Distributed Generators. Thus, VSIs play a vital role in power system voltage stability. This review is a comprehensive survey of various indices and analyses their accuracy in determining the instability of power systems. Voltage stability is a crucial concern in operating a reliable power system, and the systematic evaluation of voltage stability is essential in a power system. This review considered and analyzed 34 indices from 138 articles from the literature for their significant performance in various power system stability problems. Of 33 indices, were 22 derived from transmission line parameters, referred to as line indices, and 12 from bus and line parameters, referred to as bus indices.

Due to rising energy consumption, electrical power system networks are frequently exposed to severe stress and operate close to their maximum stability limits. Consequently, these systems are becoming less secure, and voltage instability is becoming a constant concern. The operators must have a precise understanding of how the current system is operating. Voltage stability indices are one of the most powerful tools for evaluating power system stability. In order to avoid voltage instability and collapse, PMU-based real-time voltage stability assessment is one of the novel concepts. The line stability index (Lmn), fast voltage stability index (FVSI), line stability factor (LQP), line index (L-index), voltage collapse proximity index (VCPI-P and VCPI-Q), line voltage stability index (LVSI), and critical voltage (Vcr) were all taken into account in this study. This paper is unique in that it computes and compares these standard line voltage stability indices on a static load model with the help of PMU recordings to identify the weak areas. Under steady-state operating conditions, these indices are computed on the classic WSCC 3-machine 9-bus system. These findings could be extremely useful to system operators to improve the static voltage stability margin, grid planning, and protection to prevent future blackouts.

Static compensators (STATCOMs) are able to provide rapid and dynamic reactive power support within a power system for voltage stability enhancement. While most of previous research focuses on only an either static or dynamic (short‐term) voltage stability criterion, this study proposes a multi‐objective programming (MOP) model to simultaneously minimise (i) investment cost, (ii) unacceptable transient voltage performance, and (iii) proximity to steady‐state voltage collapse. The model aims to find Pareto optimal solutions for flexible and multi‐objective decision‐making. To account for multiple contingencies and their probabilities, corresponding risk‐based metrics are proposed based on respective voltage stability measures. Given the two different voltage stability criteria, a strategy based on Pareto frontier is designed to identify critical contingencies and candidate buses for STATCOM connection. Finally, to solve the MOP model, an improved decomposition‐based multi‐objective evolutionary algorithm is developed. The proposed model and algorithm are demonstrated on the New England 39‐bus test system, and compared with state‐of‐the‐art solution algorithms.

Comprehensive evaluation of voltage stability based on EW-AHP and Fuzzy-TOPSIS

Voltage collapse is a problem that may happen when power systems are overloaded. An accurate estimation of critical operating conditions is necessary to prevent voltage collapses in power grids. Accurately predicting voltage collapse in the network will help the operators take timely rectification by monitoring the system and its closeness to the voltage collapse. This article suggests a more accurate voltage collapse prediction for identifying weak buses and critical lines based on a new proposed index termed Modern Voltage Stability Index (MVSI). The proposed index ignores the line resistance partially, i.e., the method consists of zeroing the resistance of a part and not entirely of the exact formula of the system to develop an approximate and fast collapse prediction index. It indicates that entirely ignoring the line resistance creates an erroneous voltage collapse prediction that may exceed 70%. For verification purposes, this study compared the existing stability indices (Lmn, FVSI, LQP, NLSI, VSLI and NVSI) with the proposed index based on the variables contained in each index, simulation results and percent errors. Determining the influences of the relative directions of real and reactive power-flow in the branches is one of the most important considerations of the proposed index to predict voltage collapse. Different load conditions have been used to examine the feasibility and performance of the proposed index in collapse predictions. Under several load conditions, the performance of MVSI has been compared with the performance of Lmn, FVSI, LQP, NLSI, VSLI and NVSI to determine the highest performance among them in collapse predictions. Usually, the voltage stability is very sensitive to reactive power-flow. Therefore, the maximum reactive power loads in each particular bus have been determined in this article based on a new proposed index (MVSI). The bus which can withstand the lowest maximum reactive power before the collapse is ranked as the highest ranking, and it is considered the weakest bus in the system. The proposed index is examined on IEEE 30-bus to validate its practicability. The weak areas of EPSN have been diagnosed, studied, and evaluated by the smooth method with the help of the MATLAB environment.

High voltage direct current (HVDC) transmission offers several operation advantages over high voltage alternating current (HVAC) transmission systems. HVDC transmission lines have no frequency and hence minimal problems of harmonics, oscillations or transients; they actually damp out transients with effective controllers. Precise and fast power control in either direction is easier to achieve in HVDC than HVAC systems as dc power is minimally affected by reactance. This curtails system instability, cascading effect or voltage collapse. The ease of power flow control in HVDC lines makes it easy to achieve the maximum power and thermal capacity of transmission lines. It is also simple to control active power transfer at a predetermined level or even to modulate this to improve system damping. For weak AC grids, voltage source converter (VSC) based HVDC systems offer better controllability and grid flexibility for integrating intermittent renewable energy sources such as wind and solar-power. HVDC systems offer technical advantages: all angular stability problems disappear and even connection of systems at different frequency is feasible. The problems of cable charging current are eliminated. Thus cables can readily be used for underwater crossings. HVDC is the established technology of choice for long distance transmission and subsea electrical power transmission systems. In this paper, an investigation of voltage stability margin on Eskom high voltage eastern grid is carried out. Using the Newton Raphson iterative method, the impact of HVDC link controller and transformer tap changers on voltage stability were evaluated on Athene substation of Eskom eastern grid, an area of rapid load growth. Results obtained show that by introducing HVDC line, transmission capacity is enhanced, with lower line losses and improved voltage profile. Simulations were carried out using DigSILENT PowerFactory.

The identification of voltage collapse (VC) is crucial to prevent a possible collapse of the preventive control actions and voltage security evaluation. Selecting the critical buses in the network can assist in determining the locations where voltage collapses may occur. VC initially manifests at the weakest bus in a serious emergency case. So, for operational and planning purposes, it is essential to detect critical buses in an electric power system. The analysis of the power system in view of voltage stability (VS) was performed under different loading conditions using voltage stability indices (VSIs). The line voltage stability indices in terms of the fast voltage stability index (FVSI) and line stability index (LMN) are utilized in this paper to identify the weakest bus in the network. The suggested procedure is tested on a standard network (IEEE 14-bus system) at different overloading conditions (25 – 100 % overload) utilizing power system analysis toolbox (PSAT) software. The results proved that this index has a higher standard for predicting the point of voltage collapse and identification the weakest bus in the network, so consider more reliable and accurate relative to other indices.