Mixed variable metamodeling and optimization and application to power transfer capability analysis of manitoba-ontario electrical interconnections

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Modern product design, such as design of an aircraft or electrical system, is very complex, often involving multiple disciplines, and computation-intensive processes for analysis and simulation.  The complexity of commercial analysis codes, such as finite element analysis (FEA) and computational fluid dynamics (CFD), seems to keep pace with computing advances.   In recent years, the approximation-based optimization method has attracted many attentions. This approach approximates computation-intensive models with simple analytical models.  The simple model is often called a metamodel; and the process of constructing a metamodel is called metamodeling. With a metamodel, classic optimization methods can then be effectively applied to search for the optimum.  Current research in metamodeling and associated optimization techniques, however, is focused on problems in which all the optimization variables are continuous.  In practice, discrete variables are commonly seen, e.g., the number of teeth of a gear and the number of power generation stations.  As a result, practical system analysis and optimization problems often involve both continuous and discrete variables, which are referred as mixed variable metamodeling and optimization problems.  Power transfer capability analysis is conventionally performed by solving numerous simultaneous equations, if the system inputs are given. The transfer capability, as a function of all the inputs, is however unknown.  As the trend of power systems' deregulation progresses, to be able to understand such a function and thus maximize the power transfer capability is economically significant.  This research attempts to develop mixed variable metamodeling and optimization methods and then apply them to the power transfer capability analysis problem for Manitoba Hydro. This research examines closely the power transfer between Manitoba power network and that of Ontario.   The results are expected to be able to apply to other inter-state power connections and other electrical power vendors.