Application of distributed optimization technique for large-scale optimal power flow problem

Eghbalpour, Hamid (2019) Application of distributed optimization technique for large-scale optimal power flow problem. Masters thesis, Memorial University of Newfoundland.

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Abstract

Optimal Power Flow (OPF) is one the most basic problems in power system analysis. In the last decades many studies have been done to provide a robust and fast solution for OPF. The main goal of the Optimal Power Flow problem is determining an operating point that minimizes the power system objectives such as generation cost, emission or power loss. The conventional optimization algorithms for Optimal Power Flow are centralized algorithms. These conventional centralized algorithms encounter two challenges. First, most times the generation units in a power network belong to different owners that do not want to share their confidential information with other power generation companies. Second, when the number of buses significantly increase the optimization problem will be very complicated. In these cases, finding the optimal solution takes time and in some cases even the solution does not converge. In order to solve the large-scale Optimal Power Flow problem in power networks and deal with the problems brought by the system size, distributed parallel processing algorithms, which are known distributed optimization techniques, are sought. In distributed parallel algorithms, each processor tries to solve a sub-problem independently based on limited information communication. This research discusses a consensus-based Alternating Direction Method of Multipliers (ADMM) approach for solving the OPF problem. In distributed optimization, the whole power system should be split into some partitions. Sub-problems which are related to partitions should be solved by their assigned local processors in parallel. The local processors have to be networked. In the proposed distributed optimization technique, the optimal point of the whole system can be obtained throughout the ADMM iterative process. In this thesis, ADMM implementation on an OPF problem for some IEEE cases has been presented and the optimal solution obtained by ADMM and MATPOWER (a MATLAB base program) are compared.

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