In this paper, we propose a method to solve the distributed optimal power flow problem and discuss the associated implementation. We have combined this method with a projected Jacobi (PJ) method and a modified parallel block scaled gradient (MPBSG) method possessing decomposition effects. With the decomposition, our method can be parallel processed and is computationally efficient. We have tested our method for distributed OPF problems on numerous power systems. As seen from the simulation results, our method achieved a dramatic speed-up ratio compared with the commercial IMSL subroutines.

In this paper, we propose two techniques to solve the nonlinear constrained optimization problem in large scale mesh-interconnected system. The first one is a diagram-method-based decomposition technique which decomposes the large scale system into some small subsystems. The second technique is a projected-Jacobi-based parallel dual-type method which can solve the optimization problems in the decomposed subsystems efficiently. We have used the proposed algorithm to solve numerous examples of large scale constrained optimization problems in power system. The test results show that the proposed algorithm has computational efficiency with respect to the conventional approach of the centralized Newton method and the state-of-the-art Block-Parallel Newton method.