A Lagrange-Multiplier-Based Reliability Assessment for Power Systems Considering Topology and Injection Uncertainties
Zeyu Liu, Puting Tang, Kai Hou, Lewei Zhu, Junbo Zhao, Hongjie Jia, Wei Pei
Abstract
With the expansion of power grids and the growth of renewable energy generation, more uncertainties of topology (e.g., components outages) and injection (e.g., renewable energy outputs variations) need to be analyzed. As a result, large numbers of system states have to be evaluated by optimal power flow (OPF) and this brings a significant challenge to the efficiency of reliability assessment. To address this, a Lagrange-multiplier-based reliability assessment method (LM-T&I) is proposed to accelerate the evaluation of system states. The Lagrange-multiplier-based function is constructed to obtain the optimal load shedding of topology changes and injection variations, avoiding time-consuming OPF computations. Moreover, combined with the impact-increment-based state enumeration method (IISE), the computational efficiency can be further improved. Case studies are conducted on the RTS-79 and IEEE 118-bus systems. The scalability of the LM-T&I method is verified on the practical Brazilian system. The results demonstrate that the LM-T&I method has a superior performance on the reliability assessment compared with traditional methods.