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Flexibility assessment tool by failure-based uncertainty management in power systems

Title	Flexibility assessment tool by failure-based uncertainty management in power systems
Author	Poyrazoğlu, Göktürk, Dolu, Uğur
Publication Date:	2019
Publication Place	- IEEE
Subject	Flexibility, Power systems, Uncertainty, Empirical weighting, Probability
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-1-5386-8218-0
Record ID	e1fc3f34-d49d-4398-af6e-b0690fca541e
Library Location	Electrical & Electronics Engineering
Date	2019
Notes	TÜBİTAK
Sample Text	Flexibility in power systems operations is the capability to operate the system under secure conditions even after a sudden change in the system conditions. One of the sudden change may be considered as the failure of components in any power plants and the resultant loss of energy supply. This study provides a framework to manage the uncertainty associated with failures by evaluating the historical failure data. A novel empirical weighting methodology is presented consists of a supervised machine learning and probability techniques and a real dataset of Turkey's power systems is used to demonstrate the success of the developed flexibility assessment tool to manage the near future uncertainty on the supply side of the system.
DOI	10.1109/ISGTEurope.2019.8905676

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Özyeğin University

Flexibility assessment tool by failure-based uncertainty management in power systems

Author Poyrazoğlu, Göktürk, Dolu, Uğur

Publication Date 2019

Publication Place - IEEE

Subject Flexibility, Power systems, Uncertainty, Empirical weighting, Probability

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-1-5386-8218-0

Record ID e1fc3f34-d49d-4398-af6e-b0690fca541e

Library Location Electrical & Electronics Engineering

Date 2019

Notes TÜBİTAK

Sample Text Flexibility in power systems operations is the capability to operate the system under secure conditions even after a sudden change in the system conditions. One of the sudden change may be considered as the failure of components in any power plants and the resultant loss of energy supply. This study provides a framework to manage the uncertainty associated with failures by evaluating the historical failure data. A novel empirical weighting methodology is presented consists of a supervised machine learning and probability techniques and a real dataset of Turkey's power systems is used to demonstrate the success of the developed flexibility assessment tool to manage the near future uncertainty on the supply side of the system.

DOI 10.1109/ISGTEurope.2019.8905676