Routing Line Personnel for Restoration of Disrupted Power Distribution Network

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Golla, B. G. (2017). Routing Line Personnel for Restoration of Disrupted Power Distribution Network. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Natural disasters such as storms, floods, earthquakes cause a great deal of damage to human lives and properties, and this damage is aggravated by disruptions to some critical infrastructures, such as transport system, electricity and water supplies. The primary impact of natural disasters on power systems would be severe power outages. When the period of power outage is prolonged the suffering of the customers becomes far more worsened. Consequently, it is desired to restore power distribution systems promptly. In this thesis, we are concerned with a so-called repair crew scheduling problem that minimizes the total restoration time by adequately scheduling repair personnel.Given information about fault locations and estimated repair times along with travel time data between locations, we investigate mathematical optimization models, specifically two mixed-integer programming (MIP) models. The first MIP model is formulated in analogy to the identical multiple machine scheduling problem, while the second model is proposed in an effort to reduce solution times. Noting that the repair crew scheduling problem is NP-hard, a heuristic method is also proposed. A numerical study was conducted to compare computational performances of the aforementioned exact models and the heuristic method. The computational results revealed that the second MIP model is promising when time allows. It is also observed that the heuristic method can be practically implemented under time pressure. Based on this observation, we propose an implementation plan that combines the second MIP and the heuristic method in a dynamic circumstance.

Details
Author

Golla, Bhavish Gokul

Title

Routing Line Personnel for Restoration of Disrupted Power Distribution Network

Physical Description

1 online resource (59 pages) : PDF

Date

2017

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Natural disasters such as storms, floods, earthquakes cause a great deal of damage to human lives and properties, and this damage is aggravated by disruptions to some critical infrastructures, such as transport system, electricity and water supplies. The primary impact of natural disasters on power systems would be severe power outages. When the period of power outage is prolonged the suffering of the customers becomes far more worsened. Consequently, it is desired to restore power distribution systems promptly. In this thesis, we are concerned with a so-called repair crew scheduling problem that minimizes the total restoration time by adequately scheduling repair personnel.Given information about fault locations and estimated repair times along with travel time data between locations, we investigate mathematical optimization models, specifically two mixed-integer programming (MIP) models. The first MIP model is formulated in analogy to the identical multiple machine scheduling problem, while the second model is proposed in an effort to reduce solution times. Noting that the repair crew scheduling problem is NP-hard, a heuristic method is also proposed. A numerical study was conducted to compare computational performances of the aforementioned exact models and the heuristic method. The computational results revealed that the second MIP model is promising when time allows. It is also observed that the heuristic method can be practically implemented under time pressure. Based on this observation, we propose an implementation plan that combines the second MIP and the heuristic method in a dynamic circumstance.

Genre

masters theses

Subjects--Topics

Industrial engineering
Operations research

Degree

M.S.

Keywords

HILF Events
Mixed Integer Programming Formulations
Reapir Crew Scheduling
Total Restoration Time
Traveling Salesman Problem

Subject Area

Engineering Management

Advisor(s)

Lim, Churlzu

Committee Members

Chowdhury, Badrul
Sireli, Yesim

Degree Note

Thesis (M.S.)--University of North Carolina at Charlotte, 2017.

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Rights Holder Information

Copyright is held by the author unless otherwise indicated.

Identifier

Golla_uncc_0694N_11600

Permalink

http://hdl.handle.net/20.500.13093/etd:873