DC power flow analysis incorporating interval input data and network parameters through the optimizing-scenarios method

Abstract

DC power flow analysis is based on a linear approximation model for AC power flow equations, and represents an efficient approach for acquiring the bus angles and active transmission power of a power grid. However, the input data and network parameters of the power grid are uncertain due to numerous internal and external factors. Therefore, the DC power flow model should be considered as an uncertain problem, which makes deterministic DC power flow analysis methods unworkable. The present work overcomes this problem by regarding uncertain input data and network parameters as interval values, respectively, and establishes the interval DC power flow (IDCPF) models considering interval input data only (denoted as IDCPF01), and IDCPF model including both interval input data and network parameters (denoted as IDCPF02). Analyses based on the IDCPF models seek to obtain conservative ranges of bus angles and active transmission power flow, which can be employed by dispatchers to develop strategies for ensuring the operational security of the power system. The optimizing-scenarios method (OSM) is employed here to solve the IDCPF models. In addition, it is proven that the lower (or upper) bounds of the bus angles of the IDCPF01 model are simultaneously obtained when the injected power is set as its lower (or upper) interval bounds. This fact greatly improves the efficiency of the OSM for solving the IDCPF models. The results obtained by the proposed method are compared with those obtained by Monte Carlo simulation, the AA-based method, and the interval AC power flow method. The overall simulation results demonstrate the effectiveness and robustness of the proposed method.