A Search Space Reduction Algorithm Applied for Transient Stability Constrained Optimal Power Flow

Transient stability constrained optimal power flow (TSC-OPF) is a well known problem in the literature. Several nu-merical based and heuristic based approaches have been applied to solve this problem so far. In the literature, it is shown that meta heuristic-population based methods are fast and effective in handling this problem. This paper proposes a heuristic method based workflow known as, search space reduction algorithm (SSRA) based workflow to solve the TSC-OPF problem. The SSRA based TSC-OPF solution make changes in active power generations of the generators in the power system such that both the goals, system economy of operation and stability requirements are reconciled, satisfying both the static and dynamic constraints. The proposed method is tested on 10 machine 39 bus system and results indicates that the proposed approach has capability to explore and exploit efficiently, the search range to reach a near global optimal point. The results are compared with different evolutionary algorithms like PSO and GWO, and the comparison results shows that the proposed method achieves more near global optimum compared with its counterparts. Further, the effect of the algorithm tuning parameters on its convergence characteristics has also been investigated in a systematic manner.