Abstract: Power system security analysis is the most time demanding process due to large number of possible contingencies that need to be analyzed. In a power system, any contingency resulting in security violation such as line overload or low voltage may occur for a number of reasons at any time. To efficiently rank a contingency, both probability and the extent of security violation must be considered so as not to underestimate the risk associated with the contingency. This paper proposed a contingency ranking method that take into account the probabilistic nature of power system and the severity of contingency by using a newly developed method based on risk factor. The proposed technique is implemented on IEEE 24-bus system.
Abstract: This paper presents a genetic algorithm based
approach for solving security constrained optimal power flow
problem (SCOPF) including FACTS devices. The optimal location of
FACTS devices are identified using an index called overload index
and the optimal values are obtained using an enhanced genetic
algorithm. The optimal allocation by the proposed method optimizes
the investment, taking into account its effects on security in terms of
the alleviation of line overloads. The proposed approach has been
tested on IEEE-30 bus system to show the effectiveness of the
proposed algorithm for solving the SCOPF problem.