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Optimal power flow (OPF) has been considered as an important problem in power systems. Although several excellent algorithms, such as Newton method and interior point method, have been developed to solve the OPF problem, divergences still often occur. Till now, few works have focused on the solv- ability identification and feasibility restoring of divergent OPF problems. In this paper, we propose a systematic approach to identify the solvability of divergent OPF problems, and restore a feasible solu- tion for unsolvable OPF cases. The proposed approach consists of two phases: solvability identifica- tion phase (SIP) and feasibility restoring phase (FRP). In SIP, a novel methodology based on problem transformation and active set is adopted to identify the solvability of divergent OPF problem. If a fea- sible solution can be obtained in SIP, then this divergent OPF problem is solvable, otherwise, FRP is used to restore a feasible or optimal solution by relaxing soft constraints and load shedding. In FRP, a feasibility restoring model is presented, and a priority-listing strategy of restoring actions is proposed to restore the unsolvable OPF problems. Numerical studies indicate that the proposed SIP and FRP are reliable to diagnose the solvability of the divergent OPF problems, give an index to measure the un- solvability, and restore an unsolvable OPF case.
Optimal power flow (OPF) has been considered as an important problem in power systems. Several several excellent algorithms, such as Newton method and interior point method, have been developed to solve the OPF problem, divergences still often occur. Till now, few works have focused on the solv- ability identification and feasibility restoring of divergent OPF problems. In this paper, we propose a systematic approach to identify the solvability of divergent OPF problems, and restore a can solu- tion for unsolvable OPF cases. of two phases: solvability identification phase (SIP) and feasibility restoring phase (FRP). In SIP, a novel methodology based on problem transformation and active set is adopted to identify the solvability of divergent OPF problem. If a fea- sible solution can be obtained in SIP, then this divergent OPF problem is solvable, otherwise, FRP is used to restore a feasible or optimal solution by relaxing soft constraints and load shedding. In FRP, a feasibility-restoring model is presented, and a priority-listing strategy of restoring actions is restituted to restore the unsolvable OPF problems. Numerical studies indicate that the proposed SIP and FRP are reliable to diagnose the solvability of the divergent OPF problems. , give an index to measure the un-solvability, and restore an unsolvable OPF case.