Optimal network reduction of electrical distribution communities
Abstract
Network reduction has been demonstrated as a practical technique that simplifies complex electrical networks to ad- dress computational and analytical challenges posed by large- scale electrical grids. Traditional network reduction methods are based on a pre-defined set of nodes or lines to remain in the reduced network. To address these challenges, we propose an optimal network reduction approach for large-scale distribution networks, with a focus on power flow studies. Our method combines Mixed Integer Linear Programming with Kron reduction to maintain equivalent impedance among kept nodes. This approach enables the determination of the desired level of reduction with respect to voltage deviation.
Primary Faculty Mentor Name
Jackson Anderson
Status
Graduate
Student College
College of Engineering and Mathematical Sciences
Program/Major
Electrical Engineering
Primary Research Category
Engineering and Math Science
Optimal network reduction of electrical distribution communities
Network reduction has been demonstrated as a practical technique that simplifies complex electrical networks to ad- dress computational and analytical challenges posed by large- scale electrical grids. Traditional network reduction methods are based on a pre-defined set of nodes or lines to remain in the reduced network. To address these challenges, we propose an optimal network reduction approach for large-scale distribution networks, with a focus on power flow studies. Our method combines Mixed Integer Linear Programming with Kron reduction to maintain equivalent impedance among kept nodes. This approach enables the determination of the desired level of reduction with respect to voltage deviation.
