Power System Voltage Stability Research Articles

Enrichment of voltage stability in power system through novel generalized approximate reasoning based intelligent control with african buffalo optimization approach

Enrichment of voltage stability in power system through novel generalized approximate reasoning based intelligent control with african buffalo optimization approach

Coupled single-port method based voltage stability assessment with inverter-based generators

With the increase of inverter-based generators in the power system, the proportion of traditional generators is decreasing, and their voltage support ability to the power system is weakening, the power system operation is approaching to its voltage stability limit. It is of great significance to study on-line analysis of power system voltage stability under different control manners of inverter-based generators. Firstly, impedance matching theory and coupled single-port circuit theory are introduced. Secondly, coupled single-port method based voltage stability assessment method with inverter-based generators is proposed. Then, use the impedance matching condition and proposed method to analyze the influence of inverter-based generators on voltage stability in different control manners. The proposed method can reveal the voltage stability margin of power system with inverter-based generators in the current running state, and is suitable as an on-line voltage stability approach to evaluate the proximity of voltage collapse in real time. The various scenario simulations experiment validate the effectiveness and accuracy of the proposed method. Meanwhile, experimental analysis results show that different control manners of inverter-based generators not only affect voltage stability margin but also change the weakest bus of power system.

Editorial to the Inaugural Issue

Dear editors, reviewers, authors, readers, and other members of the whole scientific and professional community, Welcome to this inaugural issue of Journal of Intelligent Systems and Control (JISC)! On behalf of the editorial office, I am writing with great pleasure and sincere privilege to present the first issue of the journal JISC. The past few years has witnessed a growing necessity for advanced intelligent systems, as artificial intelligence penetrate virtually all fields of science, industry, and life. There are many indicators of nature and social systems, some of which conflict with each other. Intelligent systems and smart control methods are urgently needed to resolve the potential conflicts. However, it is very challenging to develop such systems and methods, facing the uncertainties of the environment, the limited time, and the lack of financial resources. Against this backdrop, it is necessary to design intelligent systems based on intelligent and automatic control strategies. Such intelligent systems would save personnel costs, make our society more efficient, and enable proper decision-making. This first issue aims to answer many important questions related to the scope of the journal. Seven very interesting high-quality papers are selected for publication. These papers apply decision models in various fields: in the lateral transfer inventory optimization technique for auto spare parts, in the wind-solar hydrogen storage coupled power generation system, in the automatic car pedal pressing system, and in the cargo transportation of cranes. Additionally, the micro-positioning stage, the data sharing of multi-cloud storage server, and the power system voltage stability, are also discussed in this issue, providing important insights into various intelligent systems. Journal of Intelligent Systems and Control (JISC) (ISSN 2957-9805) is an international open access scholarly journal addressing the theories, methods, and applications underlying intelligent systems and system control. The mission of the journal is to foster new thinking and research, and facilitate the understanding of operating and control mechanisms of economic, engineering, management, and technological systems. We welcome original submissions in various forms, including review articles, regular articles, short communications, as well as Special Issues on particular subjects. The journal encourages contributions related to the new developments in theory and practice that can improve the performance and control of various systems. We follow principle of international diversity regarding the editorial board, reviewers and authors. Therefore, we invite and welcome submissions from around the world. All information related to JISC journal are available in our website: https://www.acadlore.com/journals/JISC.

Continuation Power Flow Analysis of Power System Voltage Stability with Unified Power Flow Controller

The rising power demand has forced power systems all over the world to operate very close to their stability limits. When power systems are overloaded, faulty, or in lack of reactive power, voltage collapses would ensue. The capacity of a power system to keep the voltage of every bus constant under disturbances is called voltage stability. This dynamic phenomenon hinges on the load features. It is commonly known that flexible AC transmission systems (FACTS) can improve voltage stability. This paper puts forward a load flow model with the unified power flow controller (UPFC), and relies on the model to investigate the voltage stability of a power system through continuation power flow (CPF) method. The validity of the model was verified through a simulation, using the power system analysis toolbox (PSAT) in MATLAB/Simulink environment.

Research and Application of Combined Reactive Power Compensation Device Based on SVG+SC in Wind Power Gathering Area

With the increasing proportion of wind power access year by year, it brings many challenges to the voltage stability of power systems. In order to maintain the stability of the voltage in the power grid, it is impossible to take into account the regulation ability and economy when a single reactive power compensation device is installed. In this paper, a combined reactive power compensation device was installed, which is composed of a static var generator (SVG) and a parallel capacitor bank. The SVG has the characteristics of fast and smooth adjustment, and the application of the capacitor bank reduces the overall investment cost and has a great economy. The modal analysis method was used to find the optimal installation position for the reactive power compensation device. The improved particle swarm algorithm was used to optimize the capacity of the optimal reactive power compensation device to ensure the best performance of the compensation device. Finally, by formulating the control strategy of the combined reactive power compensation system, the reliable switching of the compensation device is controlled. The PSCAD simulation software was used to model the power grid in the Hami area, and six different configuration programs were set for static voltage stability simulation verification and three different configurations. The program was simulated and verified for transient voltage stability, and comparative analysis showed that the proposed method was correct, which strongly supports the voltage stability of the region and meets the demand of reactive power compensation of the power grid. This provides a good reference program for other wind power gathering areas.

A Reserve Constrained Optimum Reactive Power Dispatch in Wind-Integrated Power Systems Using Coronavirus Herd Immunity Optimizer

The optimal reactive power dispatch (ORPD) plays a significant role in planning stable and secure power system operations. The challenges associated with the stable operation of power system networks increase with the rise in wind energy penetration into the system. To guarantee the secure operation of wind-integrated power system networks, a scenario-based reserve constrained optimal reactive power dispatch (RC-ORPD) approach is proposed in this work. For this, the effect of uncertain wind power penetration on the effective reactive reserve (ERR) and voltage stability indicator (L-index) is assessed. The threshold ERR required to retain in the system is evaluated, and is incorporated as an additional constraint to the conventional ORPD problems. The proposed problem is modeled as a scenario-based non-linear complex optimization problem and is solved using a newly developed meta-heuristic called “Coronavirus Herd Immunity Optimizer (CHIO)”. Programs are developed in MATLAB and tested on the wind-integrated IEEE 30, IEEE 118, and practical Indian 62 bus systems. The anticipated strategy is validated through several case studies and comparisons. The comparison reveals that the newly added constraint improves the voltage stability of the wind-integrated power systems without negotiating much on the numerical values of the objectives. Also, the efficacy of the CHIO is verified through statistical studies and comparisons with other contemporary algorithms.

Scenario-based line switching for enhancing static voltage stability with uncertainty of renewables and loads

The fast-growing renewables, such as wind power and photovoltaic, introduce a large number of uncertainties into the power grid. The uncertainty of renewables, coupled with that of load, increases the complexity of the analysis of static voltage stability of power systems. In this paper, the nonlinear impact of the uncertainties from both renewables and loads on static voltage stability (limited by two types of typical bifurcations, i.e., saddle-node bifurcation and structure-induced bifurcation) is investigated and illustrated. To model the uncertainties, a scenario-based scenario construction method is presented to obtain the representative scenarios tailored for the static voltage stability problem which can avoid the mis-elimination of the extreme scenarios. Then, a stochastic line switching problem is formulated to maximize the load margin to the static voltage stability of the look-ahead power system. To fast identify the line solutions, a three-stage methodology, including a scenario construction stage, the identification stage, and the evaluation stage, is proposed to balance the speed and accuracy. Finally, the computational results based on the IEEE 118-bus power system, 1648-bus power system, and 3120-bus power system demonstrate the efficiency of the proposed methodology.

Static Voltage Stability Assessment Using a Random UnderSampling Bagging BP Method

The increase in demand and generator reaching reactive power limits may operate the power system in stressed conditions leading to voltage instability. Thus, the voltage stability assessment is essential for estimating the loadability margin of the power system. The grid operators urgently need a voltage stability assessment (VSA) method with high accuracy, fast response speed, and good scalability. The static VSA problem is defined as a regression problem. Moreover, an artificial neural network is constructed for online assessment of the regression problem. Firstly, the training sample set is obtained through scene simulation, power flow calculation, and local voltage stability index calculation; then, the class imbalance problem of the training samples is solved by the random under-sampling bagging (RUSBagging) method. Then, the mapping relationship between each feature and voltage stability is obtained by an artificial neural network. Finally, taking the modified IEEE39 node system as an example, by setting up four groups of methods for comparison, it is verified that the proposed method has a relatively ideal modeling speed and high accuracy, and can meet the requirements of power system voltage stability assessment.

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 concept for discrimination of electrical fault from cyber attack in smart electric grid

Abstract This letter proposes a concept to discriminate an electrical fault from a cyber attack in the modern power system. A cyber attack factor is introduced which may mislead the bus voltage stability virtually at load buses. The proposed cyber attack models are validated by executing multiple cyber attacks at a time on Western system coordinating council (WSCC) 9 bus test power system by using Siemens PSS/E and MATLAB softwares. Further, the impact of electrical fault and cyber attack on the WSCC 9 bus test power systems voltage stability has been analysed to develop a discrimination algorithm in reference to chosen load index. Despite its simplicity, the proposed discrimination algorithm is robust, accurate and quite suitable to develop intelligent measures for mal-operations against cyber attacks in the smart electric grid.

Justification of the need to improve emergency control systems for preventing disturbances of voltage stability in power systems

This article is aimed at justifying the need to modernize the existing systems that ensure voltage stability in the Unified Power System of Russia under the conditions of its permanent development, structural complication and active implementation of distributed generation. To this end, an analysis of the existing systems of emergency control used in the Unified Power System of Russia was conducted by considering their efficiency during major system accidents, including those in 2005 and 2017. In addition, specific features of operating power system facilities in the northern part of the Irkutsk Oblast were investigated from the standpoint of voltage stability. The conducted analysis of the operation of emergency control systems in the context of system accidents, including possible incorrect actions, identified their following disadvantages: insufficient fault tolerance, weak adaptability to emergency disturbances (including abnormal situations), as well as a lack of coordination between local devices and the discreteness of regulation. These shortcomings can be eliminated by introducing intelligent automation systems based on artificial neural networks and machine learning, as well as high-performance multi-agent systems into the structure of the emergency management of the Unified Power System of Russia. The results obtained indicate the need to modernize the existing voltage stability systems operated in the Unified Power System of Russia, both their software and hardware components. The proposed implementation of intelligent systems is expected to improve the existing systems at the same time as maintaining the current effective hierarchical principles of emergency management.

Impact Analysis of a Battery Energy Storage System Connected in Parallel to a Wind Farm

Increasing wind generation insertion levels on electrical grids through power converters may cause instabilities in the AC grid due to the intermittent wind nature. Integrating a Battery Electric Energy Storage System (BESS) in wind generation can smooth the power injection at the Common Coupling Point (PCC), contributing to the power system voltage and frequency stability. In this article, it is proposed to analyze the operation of a lithium-ion battery technology based 1 MW/1.29 MWh BESS connected in parallel with wind generation with a capacity of 50.4 MW. The main characteristics investigated are power smoothing and power factor correction. Experimental results show that BESS contributes to smoothing the active power and correcting the power factor of wind generation, improving the quality of electrical energy at the PCC.

Distributed Integrated Synthetic Adaptive Multi-Objective Reactive Power Optimization

Reactive power is the core problem of voltage stability and economical operation in power systems. Aiming at the problem that multi-objective normalization reactive power optimization function is dependent on weight, an integrated synthesis of adaptive multi-objective particle swarm optimization (ISAMOPSO) is proposed to achieve weight adaptive. Through seven test functions and three algorithm comparison experiments, it is proved that the ISAMOPSO algorithm has stronger global search capability and better convergence. Considering the optimal access position and capacity of distributed generation (DG), the ISAMOPSO algorithm is used for three-objective reactive power optimization. Finally, the results indicate that the ISAMOPSO algorithm can not only provide a variety of optimization schemes to meet different needs, but also realize dynamic reactive power optimization, which further proves that the algorithm can provide effective technical support for solving reactive power optimization problems in practical engineering.

Assessment of the voltage stability index of electric networks supplying charging stations using a multilayer perceptron

Ensuring power system voltage stability is one of the key challenges in power system planning and operation. At the moment, as a result of a number of technological incidents in the form of a violation of the stability of the voltage of the power system, multilayer perceptrons were tested on the territory of various countries.PURPOSE. Development of an intelligent approach to assessing the Load Stability Index (LSI) in the power system using computational intelligence methods (neural networks).METHODS. In the course of these studies, a method for estimating the ISI was used, which is used to monitor the stability of voltage in the power system using the "Smart Park" calculation method.RESULTS. The results of providing the development stage are obtained, which substantiate the possibility of using the Multilayer Perceptron (MLP) for estimating the IEL with a high degree of accuracy.CONCLUSION. In the course of these studies, the authors of the article put forward the following conclusions: an approach based on a multilayer perceptron (MPP) neural network with feed-forward is presented; an assessment of the ISI was carried out on the example of a power system using the calculation method "Smart Park"; the presented neural network approach does not depend on the open-circuit voltage on a particular load bus; the presence of indicators of active power, reactive power and voltage on the load bus is sufficient to assess the IPL; The MSP approach allows for an accurate assessment of the ISI even when the topology and operating conditions change. The obtained indicators can be applied in changing the methodology for assessing the stability of voltage in electrical systems and complexes and calculating their operating modes.

Voltage Stability Analysis of a Power System with Wind Power Based on the Thevenin Equivalent Analytical Method

The traditional black-box Thevenin equivalent method cannot analyze the influence mechanism of wind power integration on Thevenin equivalent parameters. With the increase in wind power penetration, it will be difficult to accurately assess the voltage stability of power systems with wind power. Therefore, a Thevenin equivalent analytical method is proposed to analyze the voltage stability of a power system with wind power. This method adopts the equivalent model of wind power integration based on the current source model. It establishes the Thevenin equivalent analytical model for power systems with wind power by dividing the node types. Then, the analytical expressions of the Thevenin equivalent parameters are derived based on two equivalent modes to characterize the mechanism of wind power integration on the Thevenin equivalent parameters. In addition, the calculation flow chart of the voltage stability criterion is formulated based on the analytical value of the Thevenin equivalent impedance under different load growth ratios and wind power penetrations. Finally, a case study is conducted on the improved IEEE 39 node system with wind power. The results demonstrate the feasibility and effectiveness of the proposed Thevenin equivalent analytical method, which can more accurately judge the voltage stability of the power system with wind power.

A method for monitoring the load margin of power systems under load growth variations

The load margin is an important safety measure used in operation centers to assess the voltage stability of power systems. Usually this measure is calculated considering a single load growth direction and voltage stability requirements. However, oscillation modes with low damping rates can compromise the small-signal stability of power systems and different load growth directions can also affect load margin estimates. Thus, these two factors must be considered to provide adequate load margin for power system operation. This paper proposes a load margin monitoring scheme based on Artificial Neural Networks (ANN) considering voltage stability requirements and small-signal stability and load growth variations. Thus, the power system operator will have real-time load margin information considering voltage stability requirements and small-signal stability requirements. ANN uses as input data the voltage magnitude and voltage angle measurements provided by Phasor Measurement Units (PMUs) installed in system buses. A method to select a reduced set of buses for the monitoring system is proposed and evaluated. Case studies are presented and the results achieved provide indications of the applicability of the proposed scheme in the real-time operation of power systems.

WAMS Based Real-Time Voltage Stability Monitoring for Various Load Models in the Presence of a DFIG Integrated Wind Farm

With rising global energy demand, transmission lines are operated at their limits, causing electrical grids to operate under extreme voltage instability conditions. To meet the increased load-demand and the forced tendency across the globe of tilting towards even more renewable generation, solar and wind farms are integrated with increased size and capacity. These uncontrolled natural power injection again may affect the system’s voltage stability. To avoid blackouts and to achieve the maximum voltage stability of power systems, operators need to do effective real-time grid monitoring and control at load terminals. Load models are important in the analysis of voltage stability, and accurate load models are useful in analysing the voltage stability conditions. Phasor-measurement-unit (PMU) based wide-area monitoring and smart-automation is an innovative technology for measuring load voltage magnitude, phase angle, and frequency variations in a DFIG integrated large wind power system. This research paper focuses on estimating the real-time voltage stability through the use of linear, nonlinear, and dynamic load models in presence of a DFIG based wind-farm in WSCC three-machine nine-bus power network using PMU data. This study is carried out using MATLAB-Simulink software.

Dynamic Phasor Model of Grid-Connected Photovoltaic System in MATLAB/Simulink Considering Low Voltage Ride through Characteristics for Voltage Stability Analysis of Power System

This paper proposes a model of grid-connected photovoltaic (PV) system with low voltage ride through (LVRT) characteristic in MATLAB/Simulink based on dynamic phasor approach. Unlike all PV system models available in MATLAB/Simulink using detailed model with small capacity, the proposed model focuses on control loops of PV system to simulate a large capacity system that is appropriate for voltage stability analysis of power system installing high penetration level of PV generation. An intuitive and convenient tool for adjusting the LVRT characteristics of the PV system is also developed. The effectiveness of dynamic phasor model and the impact of the LVRT characteristic of the PV system on voltage stability are examined through MATLAB/Simulink simulations conducted on IEEE 9-bus test system. The simulation results provide an insight of how the system integrated with a large PV generation behaves under the disturbances. It also points out that the LVRT of the PV system is very important to the power system voltage stability.

Probabilistic Load Shedding Scheme for Power System Voltage Stability Enhancement Using Discrete Group Search Optimization Algorithm

This paper presents a discrete heuristic algorithm to improve voltage stability margins of the power system, during under frequency conditions. Discrete group search optimization algorithm is proposed for the first time in this work and applied to a load shedding problem. Sometimes, after initial frequency drop following severe disturbances, the system frequency might return to its acceptable value, however, the system might become unstable due to voltage problems. This paper proposes discrete group search optimization algorithm to solve the load shedding problem as well as returning system frequency to the acceptable range. The objective of proposed method is to enhance voltage stability margins of the power system. Furthermore, in the paper the load uncertainty as the most critical source of uncertainty in power system is handled using point estimation approach. The proposed method is implemented on the modified IEEE 14-Bus test system as well as 39 bus New England Network to demonstrate its applicability and effectiveness. The performance of discrete group search optimization method is also compared with several methods in terms of enhancing voltage stability margins. The results confirm that the proposed method provides a considerable enhancement in the power system voltage stability margin.

Deep learning-driven evolutionary algorithm for power system voltage stability control

The voltage stability problem has strong nonlinearity and sensitive to dimensionality, which makes it hard to balance accuracy and efficiency in its control. To enhance voltage stability margin (VSM) precisely and rapidly, a surrogate control algorithm with back propagation neural network (BPNN) embedded is carried out. Firstly, BPNN is adopted to parameterize a nonlinear voltage stability boundary mapped by operational variables. Further, benefited from the speed and precision ability of BPNN calculation, BPNN is embedded into preventive control model to replace the time-consuming calculation process of VSM. In doing so, an efficient and nonlinear simplified control model oriented to voltage stability can be constructed to enable efficiency for load margin enhancement. Besides, non-dominated sorting genetic algorithm (NSGA-II) is proposed to solve the VSM control model with the advantages of fast running speed and good convergence of solution set. At last, numerical studies on 118-bus systems testify that BPNN can achieve VSM evaluation with high accuracy and rapidly assist in NSGA-II improving the static voltage stability margin.