Abstract
This paper presents a multi-objective adaptive clonal selection algorithm (MOACSA) to minimise generation cost, transmission losses and voltage stability index (L-index) when voltage source converter (VSC) based flexible alternating current transmission systems (FACTS) devices are embedded in power systems. In this algorithm, a non-dominated sorting and crowding distance have been used to find and manage the Pareto optimal front. Further, a fuzzy based mechanism has been used to select best compromise solution from the Pareto set. Two types of VSC based FACTS devices such as static synchronous compensator (STATCOM) and static synchronous series compensator (SSSC) are considered and incorporated them as power injection models in multi-objective optimization problem. The proposed MOACSA has been tested on standard IEEE 30-bus test system with integration of these FACTS devices. The results are analyzed and compared with implementation of a standard nondominated sorting genetic algorithm-II(NSGA-II).
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