Optimal meter placement using genetic algorithm to maintain network observability

This paper presents a genetic algorithm based method by which measurement system can be optimally determined and upgraded to maintain network observability. Accurate monitoring of power system operation has become one of the most important functions in today's deregulated power markets. State estimators are the essential tools of choice in the implementation of this function. Determination of the best possible combination of meters for monitoring a given power system is referred to as the optimal meter placement problem. The proposed algorithm yields a measurement configuration that withstands any single branch outage and/or loss of single measurement, without losing network observability. The proposed algorithm is based on the measurement Jacobian and sparse triangular factorization in its numerical part and based on artificial intelligence in the decision making part. Details of the algorithm are presented using two case studies.