Estimation of Transmission Reliability Margin using statistical methods and intelligent techniques

Dadi, Swathi; Mathew, Seema; Khatavkar, V. V.

doi:10.1109/icacdot.2016.7877716

Cited by 2 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Finally, to help security assessment, [150] uses neural networks to estimate the transmission reliability margin. On the other hand, [151] proposes a method to predict total transfer capability (available amount of power that can be transferred on the tie-lines), which is an ensemble model with adaptive hierarchical GA-based neural networks.…”

Section: A Prediction Of Power Flowsmentioning

confidence: 99%

Recent Developments in Machine Learning for Energy Systems Reliability Management

2020

View full text Add to dashboard Cite

This paper reviews recent works applying machine learning techniques in the context of energy systems reliability assessment and control. We showcase both the progress achieved to date as well as the important future directions for further research, while providing an adequate background in the fields of reliability management and of machine learning. The objective is to foster the synergy between these two fields and speed up the practical adoption of machine learning techniques for energy systems reliability management. We focus on bulk electric power systems and use them as an example, but we argue that the methods, tools, etc. can be extended to other similar systems, such as distribution systems, micro-grids, and multi-energy systems.

show abstract

Section: A Prediction Of Power Flowsmentioning

confidence: 99%

Recent Developments in Machine Learning for Energy Systems Reliability Management

2020

View full text Add to dashboard Cite

show abstract

“…To mitigate the influence of system uncertainties on the electricity market activities and to minimize hourly schedule curtailments due to unexpected system events, the ISO usually implement TRM. TRM is the amount of transfer capability reserved for the system security, it is reserved for change in system operating condition and the associated system uncertainties in order to ensure reliable system operation . The associated uncertainties may be due to the loss of system components such as the loss of a critical unit.…”

Section: Total Transfer Capability and Transfer Capability Marginsmentioning

confidence: 99%

“…Accurate evaluation of TRM enables reliable power transfer and serves as an index for congestion management. The factors influencing the TRM value are load forecast, transmission line contingencies, generation patterns, and uncertainties associated with system operations and configuration . For the purpose of limited space and the intending focus of this paper, readers can refer to the several techniques which have been proposed in literature to evaluate TRM; details about TRM evaluation can be found in the literature …”

Section: Total Transfer Capability and Transfer Capability Marginsmentioning

confidence: 99%

Available transfer capability calculation methods: A comprehensive review

Mohammed

Mustafa

Mohammed

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

Summary The ceaseless efforts by power system industries to promote sustainable and competitive electric power market structure in the deregulated environment have given rise to enormous research in the area of transfer capability of transmission networks. Due to high demand for electricity, transmission components are stressed to operate close to their operating limits, and this leads to a decrease in transmission efficiency. To address this issue, efficient evaluation of available transfer capability (ATC) is crucial for system planning, operation, and control. Several approaches have been proposed for ATC computation. Surprisingly, a comprehensive literature review on ATC computation is yet to be efficiently presented. Researchers have been able to come up with fast algorithms, but most of these algorithms are not accurate, and the presented accurate techniques are not fast enough for online applications. This paper presents a comprehensive review of the different approaches for ATC determination. It provides the concepts, methods, and the features of the ATC. For each technique, the state of the art of the several contributions made by researchers has been highlighted. This review reveals that there are issues regarding ATC calculation methods that need attention: the development of fast and accurate algorithm incorporating system dynamics and system uncertainties in ATC determination. Additionally, efforts on the incorporation of renewable energy generation in the ATC evaluation need to be intensified. This review will serve as one in all for researchers as well as a guide for the entrants in this field.

show abstract

Estimation of Transmission Reliability Margin using statistical methods and intelligent techniques

Cited by 2 publications

References 5 publications

Recent Developments in Machine Learning for Energy Systems Reliability Management

Recent Developments in Machine Learning for Energy Systems Reliability Management

Available transfer capability calculation methods: A comprehensive review

Contact Info

Product

Resources

About