Title page for ETD etd-03302007-232205

Type of Document Dissertation
Author Zhu, Dan
URN etd-03302007-232205
Title Electric Distribution Reliability Analysis Considering Time-varying Load, Weather Conditions and Reconfiguration with Distributed Generation
Degree PhD
Department Electrical and Computer Engineering
Advisory Committee
Advisor Name Title
Broadwater, Robert P. Committee Chair
Arthur, James D. Committee Member
Cyre, Walling R. Committee Member
Liu, Yilu Committee Member
Tam, Kwa-Sur Committee Member
  • Time-varying Load.
  • Reconfiguration for Restoration
  • DG
  • Power Distribution System
  • Reliability Improvement
  • Storm Outage Prediction
  • Reliability Analysis
Date of Defense 2007-03-27
Availability unrestricted
This dissertation is a systematic study of electric power distribution system

reliability evaluation and improvement. Reliability evaluation of electric power systems

has traditionally been an integral part of planning and operation. Changes in the electric

utility coupled with aging electric apparatus create a need for more realistic techniques

for power system reliability modeling.

This work presents a reliability evaluation technique that combines set theory and

Graph Trace Analysis (GTA). Unlike the traditional Markov approach, this technique

provides a fast solution for large system reliability evaluation by managing computer

memory efficiently with iterators, assuming a single failure at a time. A reconfiguration

for restoration algorithm is also created to enhance the accuracy of the reliability

evaluation, considering multiple concurrent failures. As opposed to most restoration

simulation methods used in reliability analysis, which convert restoration problems into

mathematical models and only can solve radial systems, this new algorithm seeks the

reconfiguration solution from topology characteristics of the network itself. As a result

the new reconfiguration algorithm can handle systems with loops.

In analyzing system reliability, this research takes into account time-varying load

patterns, and seeks approaches that are financially justified. An exhaustive search scheme

is used to calculate optimal locations for Distributed Generators (DG) from the reliability

point of view. A Discrete Ascent Optimal Programming (DAOP) load shifting approach

is proposed to provide low cost, reliability improvement solutions.

As weather conditions have an important effect on distribution component failure

rates, the influence of different types of storms has been incorporated into this study.

Storm outage models are created based on ten years’ worth of weather and power outage

data. An observer is designed to predict the number of outages for an approaching or on

going storm. A circuit corridor model is applied to investigate the relationship between

power outages and lightning activity.

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