A Data-Driven Optimal Power Flow Model under Partial Observability - Penghua LI; Zhuoran SONG; Wenchuan WU (Zhongguo dianli)
The linearized power flow (PF) model is mainly used to make the optimal power flow (OPF) problem convex. However, existing data-driven linear PF models are mostly based on complete system measurement data. Moreover, the systems are usually partially observable due to limited measuring devices for economical installation. This paper addresses the partial observability issue by proposing a data-driven linear PF model, which can be embedded in OPF. The model is robust against bad data in measurements, with its accuracy verified by numerical tests.