Multiobjective optimization for power quality monitoring allocation considering voltage sags in distribution systems

In this research, a multiobjective optimization approach is proposed to help allocate Power Quality (PQ) monitors in Distribution Systems (DS), focusing on: minimizing the cost of monitoring; minimizing topological ambiguity; maximizing the load monitoring; maximizing the amount of monitored extensions; minimizing the amount of Voltage Sags (VS) that are not monitored and maximizing the monitoring redundancy of the VS. A Multiobjective Evolutionary Algorithm with Tables (MEAT) was used to solve the problem. Results from the IEEE test systems showed that the MEAT provided the Pareto Fronts with diversified and well-distributed solutions, which made them relevant for planning monitoring systems for PQ in DS. The proposed model enables power companies to evaluate investments needed for continuous monitoring of PQ, ensuring greater flexibility in the monitoring plan and a better analysis of the cost/benefit ratio considering the six objectives presented.