Steady-state Security Assessment Research Articles

State of the art approach for comprehensive power system security assessment—Real case study

Power system security assessment plays a critical role in ensuring the safety and stability of the electric grid, evaluated by the operating state’s proximity to the loadability limits. However, with the increasing integration of intermittent renewable energy sources and rising electricity demands, there is a growing need for fast and reliable algorithms to perform power system security assessments effectively. This work reviews state-of-the-art approaches for steady-state security assessment and demonstrates the advantages of the recently proposed Transversality Enforced Newton Raphson (TENR) algorithm. The algorithm provides better computational tractability, scalability, and the capability to incorporate various technological constraints like limits on voltage setpoints, transmission line thermal limits, generator power outputs, etc. This work presents a generalization of the TENR algorithm, proof of convergence, and an adaptive step-size strategy with improved computational performance. The proposed algorithm was used to study maximum loadability, maximum boundness of the nodal power injections, and total transfer capability on a realistic case study of the Russian Far-East power system model, which expects substantial development in the nearest future.

Stochastic Steady-State Security Assessment for Power System Operation by Chance Constrained Optimal Power Flow-Based Load Shedding

The operational uncertainty of the power system is significantly increased by the high penetration of renewable energy and diversification of load behavior, which have aroused the novel research on stochastic steady-state security assessment (SSSA) urgently when the operational condition gets worse and contingency happens more frequently. First of all, a novel contingency analysis model has been proposed based on chance constrained optimal power flow (CCOPF) in this work, which is able to give a comprehensive consideration on conventional generator outage, uncertainty of system operation and load shedding of interruptible loads (ILs). Moreover, the proposed model is very practical and can be solved much efficiently by an iteration method so that the purpose of secure system operation after contingency can be better realized. Second, to further enhance the steady-state security of the system, a novel pricing method for ILs has been developed here. In addition, a composite contingency ranking index has been also established to reflect the severity of generator outage more accurately. Finally, extensive study results based on a modified IEEE-39 test system have demonstrated the validity of the proposed model, which can hold a good balance amongst security, economy, controllability, and maneuverability.

Steady-state security assessment in distribution systems with high penetration of distributed energy resources

Modern Electric Power Systems are evolving from a centralized generation model toward a complex infrastructure with the presence of Distributed Energy Resources (DER). The transformative changes are especially pronounced at the level of the distribution system. The emergence of new generation technologies as solar, for example, affects the customer profile, expansion planning, and operation procedures of distribution utilities. Therefore, this paper describes a new methodology based on steady-state security regions concept for the security assessment of distribution systems with the presence of DER. The main objective of the proposed methodology is to allow an effective evaluation of the operating conditions of distribution systems with high penetration of DER, focusing on the intermittence of the new generation resources. The proposed methodology has been tested using two distribution systems. The first one is a tutorial 13-bus system, which is a small tutorial feeder, and the second one is a real large-scale model of a distribution network. The results presented indicate the effectiveness of the proposed technique in the distribution system security analysis. The proposed methodology is implemented using the Python language and uses the OpenDSS software as a power flow solver.

Novel Data-Driven Distributed Learning Framework for Solving AC Power Flow for Large Interconnected Systems

Recent advancement in power systems induces complexity in large-scale interconnected systems and poses challenges in performing security assessment studies at various operating conditions. Traditional model-based methods are computationally intensive and may not meet the requirements for real-time applications. This paper presents a novel data-driven framework for accelerating the process of obtaining multiple AC power flow (ACPF) solutions for large systems using deep convolutional neural networks (DCNN). DCNN models are designed and trained using various representative power flow cases from a system, whose outputs can be used to perform steady-state security assessment studies. Distributed training with multiple Graphical processing units (GPU)s is implemented using TensorFlow to reduce computation time. The proposed framework is implemented to identify critical buses and recognize the ACPF cases expected to cause steady-state bus voltage violations. The efficacy and feasibility of the proposed framework are evaluated on the Western Electricity Coordinating Council (WECC) 2028 system. Results demonstrate that the proposed framework is highly accurate and possess good interpretability in performing various transmission planning and operation assessment studies for large scale power networks.

An advanced method for steady-state security assessment considering dynamic thermal capacities of grid assets

The ( $n-1$ ) criterion is a commonly used criterion for secure grid operation. Violations of this criterion lead to remedial actions in the short term and the construction of additional transmission capacities in the long term to reduce congestions in the grid. An alternative strategy in reducing necessary interventions is to consider the natural dependency of the transmission capacity of an installed grid component from its environmental conditions. The application of dynamic component rating is offering additional transmission capacities for system operation. For the consideration of these capabilities in the day-ahead operation planning, forecasting the trend of the component ratings is needed. The implementation of such methods, especially for overhead lines, is tested by different system operators around the world. A further strategy in enhancing transmission capacity for the operation is to utilize the thermal inertia of a component for small and short exceedances of the ratings without violating the component’s thermal limits. Currently available static emergency ratings of components respect this capability. Component ratings as well as emergency ratings are dependent on environmental conditions. Furthermore, the available emergency operation duration is dependent on the development of the loading current in the recent past. By equipping assets with real-time monitoring systems, utilization of the component’s current transmission capacity is possible for the different operation states. This paper presents a method to consider the thermal transmission capacity of power system components, enabled by real-time monitoring systems, in the contingency analysis. The approach is an assessment at system level combined with a time-domain simulation for the evaluation of the impact of an examined contingency on a component’s relevant thermal parameters. The result of the method is compatible with the current binary statement but extended with an availability duration if a contingency occurs in the examined grid. Introducing this duration can assist the planning of curative remedial actions for the operation. Further, three specific durations were proposed for benchmarking a contingency in the different levels of analysis. These durations are the result of the time-domain simulation. The presented method is capable of analysing a network consisting of assets equipped with a monitoring system and assets without such a system. The second part of this paper presents the operation simulation of an exemplary grid for one operational year to illustrate the effect of the approach on the results of the contingency analysis in day-ahead planning.

Can key interest rates decrease output gaps?

The difference in the GDP levels is crucial for the macroeconomic forecasting to develop adequate and supportive fiscal and monetary policies. Most mismeasurements under current geoeconomics challenges can be explained by the difficulty in predicting recessions and the overestimation of the economy’s potential capacity. The research aims to consider the GDP gap’s effectiveness for the possible forecasting of the monetary policy, particularly the central bank’s interest rate. The study uses quantitative methods, particularly VAR modeling. The VAR model is chosen as a proven useful tool for describing the dynamic behavior of economic time series and forecasting. The data sample is chosen as Eurozone, the United States, and Japan. The similarity is detected on output gaps implementation in the considered states; however, the variety in the responses to the financial crisis is revealed. This difference is due to the different sensitivity of economies on the impact of monetary instruments. In particular, the Japanese economy has a relatively low level of sensitivity to changes in monetary instruments. In terms of the reactions of central banks to the current economic crisis caused by COVID-19, then due to the global lockdown and the incredible decline in economic activity, almost all countries are in a situation of negative GDP gap according the paper’s approach. However, the measures to mitigate it will vary in different states. AcknowledgmentThe paper is done in the framework of scientific faculty research 16КF040-04 “Steady-state security assessment: a new framework for analysis” (2016–2021), Taras Shevchenko National University of Kyiv (Ukraine).

Steady-state Security Assessment Based on K-Means Clustering Algorithm and Phasor Measurement Units

Background: The security assessment plays a crucial role in the operation of the modern interconnected power system network. Methods: Hence, this paper addresses the application of k-means clustering algorithm equipped with Principal Component Analysis (PCA) and silhouette analysis for the classification of system security states. The proposed technique works on three principal axes; the first stage involves contingency quantification based on developed insecurity indices, the second stage includes dataset preparation to enhance the overall performance of the proposed method using PCA and silhouette analysis, and finally the application of the clustering algorithm over data. Results: The proposed composite insecurity index uses available synchronized measurements from Phasor Measurement Units (PMUs) to assess the development of cascading outages. Considering different operational scenarios and multiple levels of contingencies (up to N-3), Fast Decoupled Power Flow (FDPF) have been used for contingency replications. The developed technique applied to IEEE 14-bus and 57-bus standard test system for steady-state security evaluation. Conclusion: The obtained results ensure the robustness and effectiveness of the established procedure in the assessment of the system security irrespective of the network size or operating conditions.

Simulation of an adaptive artificial neural network for power system security enhancement including control action

This paper presents a new method for enhancing power system security, including a remedial action, using an artificial neural network (ANN) technique. The deregulation of electricity markets is still an essential requirement of modern power systems, which require the operation of an independent system driven by economic considerations. Power flow and contingency analyses usually take a few seconds to suggest a control action. Such delay could result in issues that affect system security. This study aims to find a significant control action that alleviates the bus voltage violation of a power system and to develop an automatic data knowledge generation method for the adaptive ANN. The developed method is proved to be a steady-state security assessment tool for supplying possible control actions to mitigate an insecure situation resulting from credible contingency. The proposed algorithm is successfully tested on the IEEE 9-bus and 39-bus test systems. A comparison of the results of the proposed algorithm with those of other conventional methods reveals that an ANN can accurately and instantaneously provide the required amounts of generation re-dispatch and load shedding in megawatts.

Reserve Setting and Steady-State Security Assessment Using Wind Power Uncertainty Forecast: A Case Study

This paper reports results and an evaluation methodology from two new decision-aid tools that were demonstrated at a Transmission System Operator (REN, Portugal) during several months in the framework of the E.U. project Anemos.plus. The first tool is a probabilistic method intended to support the definition of the operating reserve requirements. The second is a fuzzy power flow tool that identifies possible congestion situations and voltage violations in the transmission network. Both tools use as input probabilistic wind power predictions.

Power System Steady State Monitoring Using Artificial Neural Network

This article presents the application of Artificial Neural Network (ANN) for steady state monitoring of a power system. In steady state monitoring of a power system, it is important to predict the line flows and bus voltages for different operating conditions. In this article ANN has been proposed as an alternative method to solve the power system problems where the desired speed has not been achieved by conventional methods. The proposed method describes an adoptive pattern recognition approach based on highly parallel information processing. We provide a pattern of system description parameters to a neural network and net returns an estimate of line flows and bus voltages. Training data were obtained by Newton Rapson load flow simulation using Mipower Software Simulation Package for different system topologies over a range of load levels and the results were compiled to form the training data set. A back propagation algorithm was used for training ANN. Results of this approach help the power system operator to successfully handle the topologically independent steady state security assessment. To illustrate the proposed approach, IEEE-14 Bus system was considered. The difference between the actual and the estimated power flows and bus voltages was found to be good in terms of accuracy.

An unified external network equivalent in steady-state security assessment

The basic objective of this paper is to present the relevant methodological and practical aspects of forming the unified external network equivalent. This equivalent consistently respects the effects of primary voltage and frequency control of external power system, including the real possibilities and limitations, as well as the effects of possible action of under frequency load shedding or under frequency protection of generator. The first practical experience in the application of the equivalent has been gained on an example of the synchronous parallel operation of the 2nd UCTE Synchronous Zone. The results obtained show a very good accuracy of unified external network equivalent formed and also show the very high speed of steady-state security assessment in context of real interconnection.

Learning to recognize vulnerable patterns due to undesirable Zone‐3 relay operations

AbstractUndesirable zone 3 relay operations caused by unexpected loading conditions can contribute to the cascaded events, leading to catastrophic outages. Identifying the basic patterns of zone 3 relay operations in advance is an effective way to help prevent cascaded events. The postcontingency impedances seen by zone 3 relays can be calculated on line in a steady state security assessment framework. However, their accuracy is inadequate compared with the postcontingency apparent impedance obtained from off‐line time domain dynamic simulations. This paper proposes a fuzzy inference system (FIS) to correct discrepancies between the postcontingency apparent impedances obtained from the results of steady state security assessment and the corresponding values obtained by time‐domain simulations. The postcontingency apparent impedances obtained from the results of steady state security assessment can be corrected on line using correction terms provided by the FIS. The dynamic model of a 200‐bus system is used to validate the performance of the proposed FIS. Copyright © 2009 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

On-Line Steady State Security Assessment of Power Systems by SMES

The response-based on-line steady state security assessment method of power systems can prevent influences of inaccuracy of models and parameters used in theoretical calculations and numerical simulations. With the aid of a grid model SMES system producing the specially designed disturbance signals, experiments were carried out in a simple power system to demonstrate the feasibility of the method. The results of experiments are then compared with that of calculations and simulations. The study indicates that the response signal of the power system being disturbed contains information of low-frequency oscillation modes and can be used as an index to the degree of steady state security of power systems.

An advanced methodology for steady‐state security assessment of power systems

AbstractThe basic objective of this paper is to present the relevant aspects of an advanced methodology for steady‐state security assessment of power systems. This methodology consists of the following relevant parts: procedure for forming the unified external network equivalents, with adaptive buffer system selection, procedure for fast contingency selection and simple method for the fast and sufficiently accurate assessment of dynamic variation of power system frequency during the time of its primary control. For the potentially critical contingency, the continuation of iterative procedure is performed. Full contingency analysis is based on specially developed method, which enables successive solution of the load‐flow problem for a set of characteristic post‐dynamic quasi‐stationary states. The characteristics of the developed methodology are tested on the example of the existing electric power interconnection in the Balkans.

Applying array-based logic to substation control for switch interlocking

Array-based logic is a novel technology based on algebraic-geometrical formulations where logical truth-values are considered as physical measurements. The preliminary study on which this paper is based shows how array-based logic can be applied to an existing substation control system resulting in a mathematically consistent and complete description of a substation interlocking scheme for steady-state security assessment. This study also showed that building a complete system rule-base in array-based logic is resembling the design of electrical networks: knowledge descriptions for each component are joined in agreement with the system topology. The knowledge description for each component, a 'primitive', is a logical description of the legality of each component state. The technology of array-based logic described in this paper is now incorporated in functioning expert system shells for personal computers. Because of the potentials of this technology a number of suggestions made by the preliminary study are being investigated in a research project.

Wind speed simulation in wind farms for steady-state security assessment of electrical power systems

Two methods are proposed to assess the impact of multiple wind farms on a large electrical power system. The methods are based on the Monte Carlo simulation of the wind speed occurring in each wind farm, taking into account measurements of mean values and correlations. The first method is based on the wind speed distribution, assumed to be Rayleigh, and on the correlation matrix, obtained from previously known simultaneous wind speed series. The second method is based on the application of the simulation to the wind speed series, taking into account the previously obtained conditional probabilities of the wind speeds as functions of other wind speeds in wind farms.

Implementation of steady state security assessment function on vector computers

A vector implementation of a complete N-1 steady state security assessment function is presented in this paper. The function includes three components: contingency screening, contingency analysis, and fast remedial action planning. In order to fully exploit the power of vector processors, the security assessment formulation is restructured and the effects of various data storage schemes are investigated. Several vectorization issues in implementing the security assessment function are addressed in this paper. Test results using the Alliant FX/80 and Convex 3840 machines are presented. The vectorization techniques and associated data structures used during the simulations are described.

Implementation of network sensitivity calculation on vector computers

Abstract A vector implementation of sensitivity computation that can be used in the remedial action planning of N‐1 steady state security assessment function is presented in this paper. In order to exploit the power of vector processors, the formulations of sensitivity calculation are restructured to minimize the execution time and the effects of data storage scheme are investigated. Tests of the proposed schemes are conducted on Alliant FX/80 and Convex 3840 machines. Test results have shown that the execution time required for obtaining a large set of sensitivity factors can be greatly reduced by using the proposed schemes on vector computers.

95/00501 On-line steady-state security assessment of power systems

95/00501 On-line steady-state security assessment of power systems

95/00476 A compact algorithm for the steady-state security assessment of power systems

Widespread applications of pressurized SF6 gas and its mixtures as insulating media in many electric power apparatus are the result of recent advances in modern technologies. Partial discharge (PD) is a natural phenomenon occurring in such gas-insulated electric power systems, which invariably contains tiny defects and non-uniformities. The quality of an electrical insulation system can be characterized by PD measurements, which serve to identify the type and status of a defect. A review on the insulation and PD monitoring for gas-insulated switchgear/transmission lines (GIS/GITL) is presented with focusing on the measurement techniques. Since PD monitoring systems can generate a large amount of data, therefore computer-aided interpretation and classification of defects are also discussed.