Efficient method to identify saddle‐node and limit‐induced bifurcation points of power system

High intermittency in today's renewable‐rich power systems, and the prohibitive cost of upgrading the network infrastructure along with the load growth, has rendered voltage instability an imminent threat for many power systems. This necessitates faster and more efficient ways of identifying the voltage stability (VS) limits, associated with specific bifurcation points of power system model, which are suitable for real‐time applications. To date, continuation power flow (CPF) has conventionally been used to identify bifurcation points of power systems, through plotting power–voltage ( P – V ) curves. However, existing CPF methods are complex and computationally demanding. To tackle this issue, in this study, accurate identification of both saddle‐node and limit‐induced bifurcation points of power systems is carried out by using a new and efficient continuous power flow algorithm, in which all the complexities associated with the existing CPF methods are relaxed. Low execution time (as compared to the existing CPF methods), ease of implementation, and automated applicability, make the proposed algorithm highly suitable for fast and accurate VS assessment of renewable‐rich, uncertain, power systems. Experiments, carried out on several different size power systems, verify that the proposed method can be effectively used to identify the VS limits of practical real‐life power systems, despite its ease of implementation and lower computational burden.