Brazilian System Operator online security assessment system

Neto, Costa; Quadros, M. A.; Santos, Marcelos Groetaers dos; Jardim, Jorge L.

doi:10.1109/pes.2010.5590039

Cited by 22 publications

(17 citation statements)

References 6 publications

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“…Literature have reported about a 10 times speed up when compared to the fixed time-step integration [36].…”

Section: Variable Time-step Integration and Early Termination Methodsmentioning

confidence: 99%

“…EEAC formulation uses the classical generator model. Since it was originally proposed, many variations have been proposed in literature to enhance the performance of the EEAC method and has been implemented in various DSA applications in its original form or including modifications [36,40,41].…”

Section: Dynamic Equivalencing Techniquesmentioning

confidence: 99%

“…Distributed and parallel processing has become an essential technique in modern online DSA systems [36,[42][43][44][45][46]. This technique can effectively accomplish significant speed improvement as the TSA usually includes the assessment of many contingencies.…”

Section: High Performance Computingmentioning

confidence: 99%

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Application of energy-based power system features for dynamic security assessment

Geeganage

Annakkage

Weekes

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

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To date, the potential of on-line Dynamic Security Assessment (DSA)-to monitor, alert, and enhance system security-is constrained by the longer computational cycle time. Traditional techniques requiring extensive numerical computations makes it challenging to complete the assessment within an acceptable time. Longer computational cycles produce obsolete security assessment results as the system operating point evolves continuously. This thesis presents a DSA algorithm, based on Transient Energy Function (TEF) method and machine learning, to enable frequent computational cycles in on-line DSA of power systems.The use of selected terms of the TEF as pre-processed input features for machine learning demonstrated the ability to successfully train a contingency-independent classifier that is capable of classifying stable and unstable operating points. The network is trained for current system topology and loading conditions. The classifier can be trained using a small dataset when the TEF terms are used as input features. The prediction accuracy of the proposed scheme was tested under the balanced and unbalanced faults with the presence of voltage sensitive and dynamic loads for different operating points. The test results demonstrate the potential of using the proposed technique for power system on-line DSA. Power system devices such as HVDC and FACTS can be included in the algorithm by incorporating the effective terms of a corresponding TEF.An on-line DSA system requires the integration of several functional components.Some of these components already exist and the others are newly introduced to the i power system. The practicality of the proposed technique in terms of a) critical data communications aspects b) computational hardware requirements; and c) capabilities and limitations of the tools in use was tested using an implementation of an on-line DSA system. The test power system model was simulated using a real-time digital simulator. The other functional units were distributed over the Local Area Network (LAN). The implementation indicated that an acceptable computational cycle time can be achieved using the proposed method.In addition, the work carried out during this thesis has produced two tools that can be used for a) web-based automated data generation for power system studies; and b) testing of on-line DSA algorithms.ii

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“…Literature have reported about a 10 times speed up when compared to the fixed time-step integration [36].…”

Section: Variable Time-step Integration and Early Termination Methodsmentioning

confidence: 99%

Section: Dynamic Equivalencing Techniquesmentioning

confidence: 99%

See 1 more Smart Citation

Application of energy-based power system features for dynamic security assessment

Geeganage

Annakkage

Weekes

et al. 2015

2015 IEEE Power &Amp; Energy Society General Meeting

View full text Add to dashboard Cite

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“…In Fisch et al and Sun et al, power system security region has been identified by considering N‐k contingencies, uncertainty in power system loads, and soft security limits. Neto et al introduced an effective tool to monitor the Brazilian power system security . By using this tool, static and dynamic security evaluations can be performed.…”

Section: Introductionmentioning

confidence: 99%

“…Neto et al introduced an effective tool to monitor the Brazilian power system security. 15 By using this tool, static and dynamic security evaluations can be performed. However, security region has been constructed without considering information content of the operating space that as regards the nigh and direct relation between security region and efficacious decision of operator especially in unforeseen and large disturbances, it can be a considerable problem.…”

Section: Introductionmentioning

confidence: 99%

Information extraction from effective descriptor variables in reconstruction of power system security region by considering correlation between loads

Javan

Mashhadi

Armin

2017

Int Trans Electr Energ Syst

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Summary In a power network, timely and accurate security assessment has been noted as the major concern of operators in secure operation of the power system. In this paper, power system security region has been constructed by using the retrieval of power system's hidden information. In fact, variables of a power system contain information regarding the status of power system security. Therefore, in order to overcome the complexity and experience‐based selection problems, descriptor variables of the power system security have been extracted by using feature extraction techniques. Also, taking the correlation between the load busses of power system into account, a realistic load modeling has been considered based on the copula modeling technique. These methods have been analyzed to opt the most effective approach, based on the mutual information index, average correlation coefficient index, and generalization error rate. The simulation results for the IEEE 9‐bus, IEEE 118‐bus, and IEEE 300‐bus test systems have demonstrated the effectiveness of the proposed method in the security region reconstruction with high information content (HIC). Rigorous analyses have also shown the interdependency of load correlation towards the complexity of implementation, which as a result, achieving a lower‐dimensional dataset with a lower classification error and a more obvious separation among the security classes is attainable.

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A new particle swarm optimization‐based methodology for determining online static security regions

Tinoco

Filho

Peres

et al. 2021

Int Trans Electr Energ Syst

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Summary A static security region is a tool that provides information on the steady‐state security conditions, for a given operating point, of a power system in an efficient way. Although this tool aims to be used in the online environment, one of its main characteristics is the high computational time required in the construction process. In this context, this article proposes a new methodology to construct these regions based on the particle swarm optimization (PSO) algorithm to improve computational performance. The proposed adjustments for the PSO algorithm parameters are detailed as well as the process to generate the initial population. The proposed methodology is validated through the study of two power systems. The first one is the well‐known New England system, and the second one is an equivalent of the southern Brazilian system. The presented results validate and clearly indicate the effectiveness of the proposed technique.

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Brazilian System Operator online security assessment system

Cited by 22 publications

References 6 publications

Application of energy-based power system features for dynamic security assessment

Application of energy-based power system features for dynamic security assessment

Information extraction from effective descriptor variables in reconstruction of power system security region by considering correlation between loads

A new particle swarm optimization‐based methodology for determining online static security regions

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