A parallel primal-dual interior-point method for DC optimal power flow
Optimal power flow (OPF) seeks the operation point of a power system that maximizes a given objective function and satisfies operational and physical constraints. Given real-time operating conditions and the large scale of the power system, it is demanding to develop algorithms that allow for OPF to be decomposed and efficiently solved on parallel computing systems. In our work, we develop a parallel algorithm for applying the primal-dual interior point method to solve OPF. The primal-dual interior point method has a much faster convergence rate than gradient-based algorithms but requires solving a series of large, sparse linear systems. We design efficient parallelized and iterative methods to solve such linear systems which utilize the sparsity structure of the system matrix.