Adaptive Clonal Algorithm and Its Application for Optimal PMU Placement

To build a measuring system with the optimal PMUs (phasor measurement unit) placement (OPP), a bilevel programming model is given, and a recursive procedure is proposed to judge the observability. The model is simplified to an ingenious objective function and an adaptive clonal algorithm (CLONALG) is proposed to find the globally optimal solution(s) and the approximately optimal solutions. In additional to imitating the clonal selection and the receptor editing mechanism of immune systems to realize the optimization, the algorithm adaptively adjusts the number of the cycle supplement population and the probabilities of hypermutation and recombination operators, according to the close level of the PMU numbers of the antibodies in the population. These adjustments can accelerate the optimizing process and prevent the search from locally optimal traps. The examples based on IEEE 14-bus/57-bus indicate that the proposed algorithm is more applicable to OPP problems than the other heuristic algorithms such as adaptive GAs and the original CLONALG