Abstract
The general difficulty of power and energy optimization problems has a direct impact on power and energy systems management. This is one of the most fundamental concerns that must be dealt with in electrical power system management. In fact, there is a critical and urgent need for developing smart and robust OPF solvers since the conventional options currently available for OPF problems are quite limited. This research is based on AC Optimal Power Flow (ACOPF) with active and reactive quadratically constrained quadratic programming optimization problems of a form that arises in operation and planning applications of the power system. Besides being nonconvex, these problems are identified to be NP-hard. This paper combines successive linear programming (SLP) based on semidefinite programming (SDP) relaxation with rank-one reduction algorithm to get a globally optimal solution for ACOPF. Also, this paper briefly introduces the research about utilizing minimum number of W terms in the objective function to improve the computation efficiency. The proposed algorithm is tested on the three test case systems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
