KNOWLEDGE-BASED NEURAL NETWORK FOR LINE FLOW CONTINGENCY SELECTION AND RANKING

The Line flow Contingency Selection and Ranking (CS & R) is performed to rank the critical contingencies in order of their severity. An Artificial Neural Network based method for MW security assessment corresponding to line outage events have been reported by various authors in the literature. One way to provide an understanding of the behaviour of Neural Networks is to extract rules that can be provided to the user. The domain knowledge (fuzzy rules extracted from Multi-layer Perceptron model trained by Back Propagation algorithm) is integrated into a Neural Network for fast and accurate CS & R in an IEEE 14-bus system, for unknown load patterns and are found to be suitable for on-line applications at Energy Management Centers. The system user is provided with the capability to determine the set of conditions under which a line-outage is critical, and if critical, then how severe it is, thereby providing some degree of transparency of the ANN solution

Impact Assessment of Hypothesized Cyberattacks on Interconnected Bulk Power Systems

The first-ever Ukraine cyberattack on power grid has proven its devastation by hacking into their critical cyber assets. With administrative privileges accessing substation networks/local control centers, one intelligent way of coordinated cyberattacks is to execute a series of disruptive switching executions on multiple substations using compromised supervisory control and data acquisition (SCADA) systems. These actions can cause significant impacts to an interconnected power grid. Unlike the previous power blackouts, such high-impact initiating events can aggravate operating conditions, initiating instability that may lead to system-wide cascading failure. A systemic evaluation of "nightmare" scenarios is highly desirable for asset owners to manage and prioritize the maintenance and investment in protecting their cyberinfrastructure. This survey paper is a conceptual expansion of real-time monitoring, anomaly detection, impact analyses, and mitigation (RAIM) framework that emphasizes on the resulting impacts, both on steady-state and dynamic aspects of power system stability. Hypothetically, we associate the combinatorial analyses of steady state on substations/components outages and dynamics of the sequential switching orders as part of the permutation. The expanded framework includes (1) critical/noncritical combination verification, (2) cascade confirmation, and (3) combination re-evaluation. This paper ends with a discussion of the open issues for metrics and future design pertaining the impact quantification of cyber-related contingencies

Online Static Security Assessment of Power Systems Based on Lasso Algorithm

As one important means of ensuring secure operation in a power system, the contingency selection and ranking methods need to be more rapid and accurate. A novel method-based least absolute shrinkage and selection operator (Lasso) algorithm is proposed in this paper to apply to online static security assessment (OSSA). The assessment is based on a security index, which is applied to select and screen contingencies. Firstly, the multi-step adaptive Lasso (MSA-Lasso) regression algorithm is introduced based on the regression algorithm, whose predictive performance has an advantage. Then, an OSSA module is proposed to evaluate and select contingencies in different load conditions. In addition, the Lasso algorithm is employed to predict the security index of each power system operation state with the consideration of bus voltages and power flows, according to Newton-Raphson load flow (NRLF) analysis in post-contingency states. Finally, the numerical results of applying the proposed approach to the IEEE 14-bus, 118-bus, and 300-bus test systems demonstrate the accuracy and rapidity of OSSA.Comment: Accepted by Applied Science

Power system contingency ranking using Newton Raphson load flow method and its prediction using soft computing techniques

The most important requirement and need of proper operation of power system is maintenance of the system security. Power system security assessment helps in monitoring and in giving up to date analysis regarding currents, bus voltages, power flows, status of circuit breaker, etc. This system assessment has been done in offline mode in which the system conditions are determined using ac power flows. The use of AC power flows is it gives information of power flows in terms of MW and MVAR , line over loadings and voltage limit violation with accurate values. Contingency selection or contingency screening is a process in which probable and potential critical contingencies are identified for which it requires consideration of each line or generator outage. . Contingency ranking is a procedure of contingency analysis in which contingencies are arranged in descending order, sorted out by the severity of contingency. Overall severity index (OPI) is calculated for determining the ranking of contingency. Overall performance index is the summation of two performance index , one of the performance index determines line overloading and other performance index determines bus voltage drop limit violation and are known as active power performance index and voltage performance index respectively. Here in this proposed work the contingency ranking has been done with IEEE 5 bus and 14 bus system. But the system parameters are dynamic in nature, keeps on changing and may affect the system parameters that are why there is need of soft computing techniques for the prediction purpose. Fuzzy logic approach has also been used. Two model of Artificial Neural Network namely, Multi Layer Feed Forward Neural Network (MFNN) and Radial Basis Function Network (RBFNN) have been considered. With these soft computing techniques the prediction method helps in obtaining the OPI with greater accuracy

Evaluación de la seguridad dinámica en línea de una micro-red usando lógica difusa y procesamiento distribuido

La evaluación de la seguridad dinámica en línea se define como la habilidad de un sistema de potencia a soportar contingencias repentinas y sobrevivir el transitorio y llegar a un nuevo estado estacionario aceptable. Durante la operación del sistema la evaluación del nivel de seguridad dinámica es esencial para tomar medidas de control preventivas con el objetivo de llevar al sistema, en caso de que sea necesario, a un estado de operación más seguro. Debido a la gran complejidad de los sistemas de potencia y al gran número de componentes, la evaluación de la seguridad es computacionalmente compleja lo que la hace poco útil. Esto es más complejo cuando se desea evaluar la seguridad dinámica considerando las nuevas micro redes. Para afrontar este problema, se presenta un nuevo enfoque de evaluación de la seguridad dinámica en línea de micro redes. La propuesta emplea procesamiento distribuido y técnicas de inteligencia artificial para reducir los tiempos de cálculo lo que permite su ejecución en línea con la operación del sistema.Dynamic security assessment (DSA) is defined as the ability of a power system to withstand sudden contingencies and to survive the transient and to reach an acceptable steady-state condition. During system operation, the on-line assessment of the dynamic security level is essential in order to take adequate countermeasures aimed to restore the system, if necessary, to a more secure operating condition. Due to both the great complexity of latest power systems and the large number of components, the on-line DSA leads to excessive computational complexity which makes it not fully operational, particularly with the inclusion of complex emerging grid-tied AC micro grids. To overcome this problem, a new approach of on-line DSA of micro grids is presented in this paper. The proposal employs distributed processing and artificial intelligence (AI) techniques in order to reduce the computing times; thus allowing its execution on-line.Fil: Schweickardt, Gustavo Alejandro. Universidad Tecnologica Nacional. Facultad Regional Concepcion del Uruguay; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gimenez Alvarez, Juan Manuel. Universidad Nacional de San Juan. Facultad de Ingenieria. Departamento de Ingenieria Electromecanica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Risk-based dynamic security assessment for power system operation & operational planning

open6noAssessment of dynamic stability in a modern power system (PS) is becoming a stringent requirement both in operational planning and in on-line operation, due to the increasingly complex dynamics of a PS. Further, growing uncertainties in forecast state and in the response to disturbances suggests the adoption of risk-based approaches in Dynamic Security Assessment (DSA). The present paper describes a probabilistic risk-based DSA, which provides instability risk indicators by combining an innovative probabilistic hazard/vulnerability analysis with the assessment of contingency impacts via time domain simulation. The tool implementing the method can be applied to both current and forecast PS states, the latter characterized in terms of renewable and load forecast uncertainties, providing valuable results for operation and operational planning contexts. Some results from a real PS model are discussed.openCiapessoni, Emanuele; Cirio, Diego; Massucco, Stefano*; Morini, Andrea; Pitto, Andrea; Silvestro, FedericoCiapessoni, Emanuele; Cirio, Diego; Massucco, Stefano; Morini, Andrea; Pitto, Andrea; Silvestro, Federic

Reliable Power System Operation Plan: Steady State Contingency Analysis

Steady state contingency analysis focuses at the evaluation of the risk certain contingency possibly causes to an electrical network. This analysis is used to review the outage of elements such as transmission lines, transformers and generators, and investigation of the resulting effects on line power flows and bus voltages in Sabah, Malaysia grid transmission system. This is an extremely significant duty for network operators since network stability issues become essentially critical in electricity deregulation. In this paper, the analysis is performed to ensure the system meets grid code standards during normal operations and variety of contingencies condition. Therefore, this paper intended to put forward issues and recommendations towards attaining a steady power system operation plan. Steady state contingency analysis is to calculate power flows in outage states in which one or more system components are out of service. A transmission system must satisfy security criteria in both normal and outage states. This paper presented the steady state contingency analysis for the period of year 2015. The contingency analysis are performed by using the Siemens PTI software, Power System Simulator for Engineering (PSS/E)

Assessment and Enhancement of Power System Security using Soft Computing and Data Mining Approaches

The power system is a complex network with numerous equipment’s interconnected for it’s reliable operation. These power system networks are forced to operate under highly stressed conditions closer to their limits. One of the key objective of the power system operators is to provide safe, economic and reliable power to it’s consumers. However, such network experiences perturbations due to many factors. These perturbations may lead to system collapse or even black out, which impacts the reliability of the system. Thus, one of the major aspect for the secure operation of the system can be achieved through security assessment. In this context, the power system static security assessment is necessary to evaluate the security status under contingency scenario. One of the approach for the security assessment is by contingency ranking, where the severity of a specific contingency is computed and ranked with highest severity to the lowest one. Initially, this approach is implemented using several load flow methods in order to identify the limit violations. However, these approaches are complex, time consuming and not feasible for real time implementation. These approaches are applied to a specific system operating condition. Thus in this context, this thesis focusses to implement soft computing and data mining approaches for security assessment by contingency ranking and classification approach. Along with the security assessment, this thesis also focusses on a control mechanism approach for the security enhancement under contingency scenario using evolutionary computing techniques. In this thesis, the various aspects of the power system security such as it’s assessment, and it’s enhancement are studied. The conventional contingency ranking approach by NRLF method is presented for the security assessment. In order to predict the system severity, a ranking module is designed with two neural network models namely, MFNN and RBFN for security assessment under different load conditions. Both neural network models are quite accurate in predicting the performance indices in less time. Another aspect of power system static security assessment is by classification approach, where the security states are classified into secure, critically secure, insecure and highly insecure. This approach helps in proper security monitoring. Thus, this thesis also presents the design and implementation of two security pattern classifier models namely the decision tree and the random forest classifiers. The classifiers are trained and tested with several security patterns generated in an offline mode. The proposed models are compared with MLP, RBFN and SVM classifier models in order to prove their efficiency in classifying the security levels. Further, this thesis work also focusses on a control mechanism for security enhancement under N-1 line outage contingency scenario. Initially contingency analysis is carried out under N-1 line outage case and critical contingencies are identified. The objective is to reschedule the generators with minimum fuel cost in such a way that the overloaded lines are relieved from stress. In order to enhance the power system security, an evolutionary computing algorithm, namely an enhanced cuckoo search algorithm is proposed for the contingency constrained economic load dispatch. To study the robustness and effectiveness of the proposed algorithm, the results are compared with CS, BA and PSO algorithms