This study explores different Linear Parameter Varying (LPV) modeling approaches and optimization methodology for a nonlinear hydro power plant. The overall hydro plant dynamics is assumed to be decomposable to its subsystems whose overall characteristics involve different dynamical behaviors related to two real-time time-varying parameters that can be measurable in future periods. The hydro plant dynamics are expressed in terms of an LPV model with two time-varying parameters to efficiently characterize the plant dynamical variations to compare as well as achieve superior modeling, analysis and control frameworks, especially in contemporary smart grid networks. The two-parameter LPV hydro plant model control system configurations and corresponding simulations illustrate a valuable computational tool for nonlinear power plant optimization.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.