Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
MDP based real time restoration for earthquake damaged active distribution systems
Date
2023-05-01
Author
Arpalı, Onur Yigit
Yılmaz, Uğur Can
GÜLDÜR ERKAL, BURCU
Aydın Göl, Ebru
Göl, Murat
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
155
views
0
downloads
Cite This
After a disaster, presence of electricity becomes even more crucial compared to its role in daily life. In this paper, an online decision support method is developed to restore medium voltage active distribution systems after an earthquake. The proposed method employs Markov Decision Process (MDP) to determine the sequence of actions which minimizes the expected restoration time. The method firstly predicts the health condition of the system components based on the Probability of Failure (Pf). These Pf values were priorly computed and plotted against Peak Ground Acceleration (PGA) values. Then a sequence of restoration actions, i.e. the restoration strategy, for the system operator is determined by considering the prediction of health conditions and power flow analysis results. During the field operation, if an unexpected situation, i.e. unexpected state of a component or a significant variation in electrical quantities, is encountered by the system operator, the proposed method updates the restoration strategy by considering those variations from the initial prediction.
Subject Keywords
Decision support
,
Disaster management
,
Distribution systems
,
Markov Decision Process
,
State estimation
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85148545746&origin=inward
https://hdl.handle.net/11511/102662
Journal
Electric Power Systems Research
DOI
https://doi.org/10.1016/j.epsr.2023.109230
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
MDP based Decision Support for Earthquake Damaged Distribution System Restoration
Arpalı, Onur Yigit; Aydın Göl, Ebru; Göl, Murat (2020-12-16)
As the society becomes more dependent on the presence of electricity, the resilience of the power systems gains more importance. This paper develops a decision support method for distribution system operators to restore electricity after an earthquake to the maximum number of customers in the minimum expected duration. The proposed method employs Markov Decision Process (MDP) to determine the optimal restoration scheme. In order to determine the probability of the field component damage due to the earthquak...
A Novel MDP Based Decision Support Framework to Restore Earthquake Damaged Distribution Systems
Aydın Göl, Ebru; Göl, Murat (2019-01-01)
Electric power network expanded rapidly in recent decades due of the excessive need of electricity in every aspect of life, including critical infrastructures such as medical services, and transportation and communication systems. Natural disasters are one of the major reasons of electricity outage. It is extremely important to restore electrical energy in the shortest time possible after a disaster. This paper proposes a decision support method for electric system operators to restore electricity to the cr...
PERFORMANCE IMPROVEMENT FOR SITUATIONAL AWARENESS AND RESTORATION OF DISTRIBUTION SYSTEMS
Yılmaz, Uğur Can; Göl, Murat; Department of Electrical and Electronics Engineering (2021-6-30)
Electricity has a crucial role in modern life, and its absence may cause catastrophic complications. Restoration of distribution systems requires an efficient decision support mechanism as well as an accurate real-time operation. Considering the utmost importance of fast restoration of the distribution system to provide uninterrupted electricity, a decision support mechanism is required to employ an efficient analysis of the system. Therefore, it is crucial to analyze the system in a fast manner. This thesi...
Application of a Hybrid Machine Learning model on short term electricty demand prediction
Assar, Ahmed Khaled Ahmed Farouk; Fahrioğlu, Murat; Sustainable Environment and Energy Systems (2022-2)
Electricity demand forecasting is an important procedure in the electricity market and plays a great role in assuring a sustainable and efficient operation chain. By accurately forecasting the demand, one can see a considerable reduction in production costs as well as saving energy resources. Therefore, optimizing the demand forecasting techniques became an inseparable goal of power economics, leading to the introduction of machine learning to this sector that proved to be superior to other pre-defined alte...
Performance Analysis of Data Mining Techniques for Improving the Accuracy of Wind Power Forecast Combination
Koksoy, Ceyda Er; Ozkan, Mehmet Baris; Küçük, Dilek; Bestil, Abdullah; Sonmez, Sena; Buhan, Serkan; Demirci, Turan; Karagöz, Pınar; Birturk, Aysenur (Springer International Publishing, 2015)
Efficient integration of renewable energy sources into the electricity grid has become one of the challenging problems in recent years. This issue is more critical especially for unstable energy sources such as wind. The focus of this work is the performance analysis of several alternative wind forecast combination models in comparison to the current forecast combination module of the wind power monitoring and forecast system of Turkey, developed within the course of the RITM project. These accuracy improve...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
O. Y. Arpalı, U. C. Yılmaz, B. GÜLDÜR ERKAL, E. Aydın Göl, and M. Göl, “MDP based real time restoration for earthquake damaged active distribution systems,”
Electric Power Systems Research
, vol. 218, pp. 0–0, 2023, Accessed: 00, 2023. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85148545746&origin=inward.