This paper describes the new eigenvalue algorithm exploiting the Implicit Restarted Arnoldi Method (IRAM) and its application to power systems. IRAM is a technique for combining the implicitly shifted mechanism with a k-step Arnoldi factorization to obtain a truncated form of the implicitly shifted QR iteration. The numerical difficulties and storage problems normally associated with the Arnoldi process are avoided. Two power systems, one of which has 36 state variables and the other 150 state variables, have been tested using the ARPACK program, which uses IRAM, and the eigenvalue results are compared with the results obtained from the conventional QR method.