An AGC Reformulation for the Decomposed Security-Constrained ACOPF Problem

Muhammad Waseem, Saeed D. Manshadi

Published 2020-12-24Version 1

This paper presents a reformulation for the automatic generation control (AGC) formulation in a decomposed convex relaxation algorithm to find an optimal solution to the AC optimal power flow (AC-OPF) problem which is secure against a large set of contingencies. First, the master problem, which represents the system without contingency constraints, is convexified by applying the second-order cone relaxation approach. Second, the contingencies are filtered for corrective or preventive actions. The contingencies for preventive security check sub-problems are evaluated in a parallel computing process to improve computational efficiency. The AGC is modeled by a set of proposed valid constraints, so the solution obtained in each security check sub-problem is the physical response of the system during a contingency. Third, Benders optimality cuts are generated for the sub-problems with mismatches. The cuts are passed to the master problem to encounter the security-constraints. The proposed convex relaxation for the master problem ensures the convergence of the decomposition algorithm. The effectiveness of the presented valid AGC constraints and scalability of the proposed algorithm are illustrated in several case studies.