Authors:
Y. Shi
1
;
H.D. Tuan
1
and
A. V. Savkin
2
Affiliations:
1
University of Technology Sydney, Australia
;
2
The University of New South Wales, Australia
Keyword(s):
Three-phase Optimal Power Flow (TOPF), Smart Grids, Rank-one Matrix Constraint, Nonsmooth Optimization, Semi-definite Programming (SDP).
Related
Ontology
Subjects/Areas/Topics:
Architectures for Smart Grids
;
Energy and Economy
;
Energy Management Systems (EMS)
;
Energy-Aware Systems and Technologies
;
Load Balancing in Smart Grids
;
Smart Grids
Abstract:
Optimal power flow is important for operation and planning of smart grids. The paper considers the so called
unbalanced thee-phase optimal power flow problem (TOPF) for smart grids, which involves multiple quadratic
equality and indefinite quadratic inequality constraints to model the bus interconnections, hardware capacity
and balance between power demand and supply. The existing Newton search based or interior point algorithms
are often trapped by a local optimum while semidefinite programming relaxation (SDR) even fails to locate a
feasible point. Following our previously developed nonsmooth optimization approach, computational solution
for TOPF is provided. Namely, an iterative procedure for generating a sequence of improved points that
converges to an optimal solution, is developed. Simulations for TOPF in unbalanced distributed networks are
provided to demonstrate the practicability and efficiency of our approach.