Semidefinite Programming for Power System State Estimation

State Estimation (SE) plays a key role in power system operation and management. For AC power system state estimation, SE is usually formalized mathematically as a Weighted Least Square or Weighted Least Absolute Value problem, and solved by Newton's method. Although computationally tractable, Newton's method is highly sensitive to the initial point, as it is essentially a local search algorithm. In this paper, we propose a Semidefinite Programming (SDP) approach to effectively obtain a good initial state to improve the performance of the existing Newton's method. Our simulation results not only show that the SDP initial guess is much better than the currently used flat start on the IEEE standard bus systems, but also demonstrates approximately globally optimal results, with a lower bound provided in this paper.