Hybrid genetical swarm optimization for power system observability via limited measurement

The size and complexity of power network and the cost of monitoring equipment, make it unfeasible to monitor the whole system variables. Conventional system analyzers use voltages and currents of the network. Hence, monitoring scheme affects the system analysis, control and protection. To monitor the whole system using limited measurements, strategic placement of them is needed. This paper improves a topological circuit observation method to find essential monitors. Besides the observability of the normal network, observability of abnormal network is considered. Consequently, a high level of system reliability is carried out. The reliability is maintained by observability under bad current data and single-line outage. Thus, all possible single line outages and CT error are plausible. These limitations operate an hybrid genetical particle swarm optimization (HGPSO) to minimize monitoring cost and removing unobservability under abnormal condition. The algorithm is tested in IEEE 14 and 30-bus test systems and Iranian (Mazandaran) Regional Electric Company 24-bus (MREC).