Kong, Jiasi (2009) Optimization methods applied to electric power systems. Masters thesis, Memorial University of Newfoundland.
- Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
The modern power system has been facing a tremendous challenge for utilities to maintain an economical, reliable and secure operation due to the increasing fuel cost, long distance transmission and intense market competition. This work investigates the application of optimization methods in power systems. Specifically, optimization methods to minimize total fuel cost and transmission loss for a specified load are considered. Multiobjective optimization focusing on the constraints related to the steady state operation including security constraints in power system is studied. Optimal Power Flow (OPF) including economic dispatch, security constrained optimal power flow and multiobjective optimization are the three key concepts of this thesis. Sequential quadratic programming is proposed and implemented as an optimization method for carrying out this research. Weighted sum method, a conventional multiobjective optimization method, is applied and implemented by Matlab Optimization Toolbox. A series of mutiobjective OPF case studies are presented in this research to show the performance and applications of the proposed optimization methods. The results from the case studies presented show that the tools are able to determine feasible, non-dominated optimal operation points that allow a system to operate economically and safely under a specified load demand.
|Item Type:||Thesis (Masters)|
|Additional Information:||Includes bibliographical references (leaves 130-133).|
|Department(s):||Engineering and Applied Science, Faculty of|
|Library of Congress Subject Heading:||Electric power systems--Management; Electric power systems--Mathematical models; Mathematical optimization|
Actions (login required)