Theses and Dissertations


Jian Wu

Issuing Body

Mississippi State University


Schulz, Noel N.

Committee Member

Ginn III, Herbert L.

Committee Member

Bruce, J.W.

Committee Member

Dandass, Yoginder S.

Date of Degree


Document Type

Dissertation - Open Access


Electrical Engineering

Degree Name

Doctor of Philosophy


James Worth Bagley College of Engineering


Department of Electrical and Computer Engineering


Simulation of power system behavior is a highly useful tool for planning, analysis of stability, and operator training. Traditionally, small power system studies are dominated by the time taken to solve the machine dynamics equations, while larger studies are dominated by the time taken to solve the network equations. With the trend towards more sophisticated and realistic modeling, the size and complexity of simulations of a power system grow tremendously. The ever-increasing need for computational power can be satisfied by the application of distributed simulation. Also power systems are distributed in nature. The terrestrial power systems are divided into groups and controlled by different Regional Transmission Organization (RTO). Each RTO owns the detailed parameter for the area under control, but only limited data and boundary measurement of the external network. Thus, performing power system analysis in such case is a challenge. Also, simulating a large-scale power system with detailed modeling of the components causes a heavy computational burden. One possible way of relieving this problem is to decouple the network into subsystems and solve the subsystem respectively, and then combine the results of the subsystems to get the solution. The way to decouple a network and represent the missing part will affect the result greatly. Also, due to information distribution in the dispatch centers, a problem of doing power system analysis with limited data available arises. The equivalents for other networks need to be constructed to analyze power system. In this research work, a distributed simulation algorithm is proposed to handle the issues above. A history of distributed simulation is briefly introduced. A generalized coupling method dealing with natural coupling is proposed. Distributed simulation models are developed and demonstrated in Virtual Test Bed (VTB). The models are tested with different network configurations. The test results are presented and analyzed. The performance of the distributed simulation is compared with the steady state result and time domain simulation result. Satisfactory results are achieved.