Date of Award
Doctor of Philosophy
Electrical and Computer Engineering
James D. Mccalley
Decision-making for operations, maintenance, and investment planning of electric power
systems must handle a great deal of uncertainty.
In the work described here, the enhanced risk index is used to describe these uncertainties,
and the Benders decomposition algorithm plays the role of integrating three components of
the decision making problem: economy, reliability, and risk.
A decomposed security-constrained optimal power flow is developed to demonstrate the
significant speed enhancement of the chosen algorithm. The risk-based optimal power flow,
risk-based unit commitment problem, risk-based transmission line expansion, and risk-based
Var resource allocation are formulated and demonstrated.
A general Benders decomposition structure is developed to cover most of the decision making
problems encountered in everyday use within the power industry. In order to facilitate this
algorithm, a service oriented architecture (SOA) is introduced and a Benders decomposition
and SOA based computation platform is designed.
Li, Yuan, "Decision making under uncertainty in power system using Benders decomposition" (2008). Graduate Theses and Dissertations. 10649.